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cpse Centre for Process Systems Engineering Annual Report 2014–2015
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Contents 2014–2015 CPSE Annual Report
Introduction 4 Highlights 2014–2015 5
Industrial Consortium 9
CPSE Research Programme 11
Competence Areas 13 Product Process and Design 14
Operations and control 16
Modelling and Model Solution Tools 20
Computational Optimisation and Machine Learning 22
Application Domains 26 Chemical Manufacturing Systems 27
Molecular Systems Engineering 30
Biological Systems Engineering 32
Energy Systems Engineering 34
Environmental Systems Engineering 36
Supply Chains of the Future 40
Academic Profiles 41 CPSE Academics and Staff Directory 84
CPSE Research Project List 86
PhD Graduates 2014–2015 96
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Welcome to the 2014–2015 CPSE Annual Report Professor Nilay Shah CPSE Director
“It has been a great pleasure to see CPSE grow in size and breadth, while continuing to excel in both fundamentals and applications.” 4
Introduction 2014–2015 CPSE Annual Report
The Centre for Process Systems Engineering draws upon the world-leading skills of Imperial College London and University College London
Three spin-out companies have been established. One of these, Understanding the Performance Process Systems Enterprise Limited (PSE), received the Royal of Complex Systems Academy of Engineering’s MacRobert Award in 2007; this is the UK’s highest award for innovation in engineering. We have a sense that the words we use to describe the complexity of the modern world provide only a superficial understanding of the The Centre continues to broaden the scope of its activities over all underlying mechanisms of the processes upon which we depend. size scales enabling all areas of process systems to be addressed. In 1989, Professor Roger Sargent gathered together a group of This enables CPSE to be responsive to the evolving needs of industry engineers, mathematicians and molecular scientists and established and society. the Centre for Process Systems Engineering to define and quantify the components that make up complex industrial chemical Centre for Process Systems Engineering processes in order to optimize performance. Imperial College London Roderic Hill Building Since then our field of work has expanded to encompass many South Kensington Campus other critical industrial and biological systems and has led to the London, SW7 2AZ development of algorithms and computer simulations that describe Email: [email protected] individual processes, from the molecular to macroscopic scale, that http://www.imperial.ac.uk/process-systems-engineering/ combine to define, for example: a bacterial cell’s ability to produce a synthetic oil; the design of an optimized urban energy system and the economics of a commodity supply chain. Statistical routines have been developed to model the performance of complex systems even in the absence of full descriptions of all the contributory components.
CPSE History
International Research Leader in Process Systems Engineering
The Centre for Process Systems Engineering (CPSE) is a multi- institutional research centre. It was inaugurated in August 1989 by Professor Roger W.H. Sargent and involves Imperial College London and University College London.
A report by a panel of external, international experts to the EPSRC research council described CPSE as being “one of the major centres of excellence in its area of expertise in the world and is seen as the benchmark against which other world centres are judged”.
Innovative and dynamic in its approach to research and development, CPSE’s accomplishments include the Queens Prize for Higher Education, presented in 2003 for research excellence and technology transfer. 5
Highlights 2014–2015 CPSE Annual Report
Centre for Process Systems Engineering (CPSE) Research Excellence
The CPSE continues to deliver a unique multi-disciplinary approach to The CPSE’s acclaimed leadership in Process Systems Engineering is Process Systems Engineering. The number of academic staff has highlighted by the number of papers in prestigious publications. In the expanded to over 30 to meet the growing demand for research and last two years, there have been over 300 publications. Many papers education in this critically important subject. by CPSE researchers have been recognised for their originality, significance and influence. The group has an annual research income portfolio of £30M. Since it was founded in 1989, CPSE has used its expertise in Process and A paper co-authored by Professor George Jackson on the Statistical Product Design, Operations and Control and Modelling and Model Associating Fluid Theory (SAFT), was selected as one of the ‘All Time Solution tools to investigate a wide range of technically and Greats’ in the history of Industry & Engineering Chemistry Research commercially important issues. The scope of CPSE continues to evolve (I&ECR). The paper, ‘New Reference Equation of State for Associating and adjust to changes in technology and commercial needs with work Liquids’ by Walter G. Chapman, Keith E. Gubbins, George Jackson, and underway, for example, in new areas such as ‘Environmental Systems’ Maciej Radosz, I&ECR 29, 1709, (1990), describes an approach which and ‘Computational Optimisation and Machine Learning.’ permits scientists to make precise predictions about the behaviour of a broad range of liquids including solutions of polymers and surfactants.
New Academics A paper by the Molecular Systems Engineering Group was listed as “one of the most accessed in 2014” from The Journal of During 2014 and 2015, the number of academics grew following the Chemical Physics. The paper is entitled ‘Accurate statistical affiliation of eight new members from both Imperial College London and associating fluid theory for chain molecules formed from Mie University College London: Dr Marc Deisenroth, Lecturer in Statistical segments’, by Thomas Lafitte, Anastasia Apostolakou, Carlos Machine Learning, Department of Computing; Dr Adam Hawkes, Avendaño, Amparo Galindo, Claire S. Adjiman, Erich A. Müller and Senior Lecturer in Energy Systems; Dr Federico Galvanin, Lecturer, George Jackson, J. Chem. Phys. 139, 154504 (2013) Department of Chemical Engineering; Dr Gonzalo Guillén-Gosálbez, Reader in Process Systems Engineering, Dr Alexandros Kiparissides Another paper from the Molecular Systems Engineering Group was (former CPSE PhD student) Lecturer in the Department of Biochemical selected as “one of the 12 most notable papers”, out of 425 papers, Engineering; Dr Niall Mac Dowell (former CPSE PhD student) published in the proceedings of the 12th International Symposium on Lecturer in Energy and Environmental Technology and Policy; Dr Ruth Process Systems Engineering held in Copenhagen. The paper is entitled Misener, Royal Academy of Engineering Fellow, Lecturer, Department ‘Deterministic global optimization and transition states’, by Claire of Computing; Dr Wolfram Wiesemann (former CPSE PhD student) Adjiman and Dimitrios Nerantzis, Elsevier, Amsterdam, 851–856 (2015). Assistant Professor, Business School. Further endorsement was received for a book, ‘Distillation: 1. Fundamentals and Principles, 2. Operations and Applications, 3. Departing Academics Equipment and Processes’ which won the 2015 PROSE Chemistry & Physics Award. Professor Andrzej Górak, Editor of Chemical Former CPSE Director, Professor Stratos Pistikopoulos Engineering and Processing: Process Intensification and Professor Eva left Imperial College to join Texas A&M University. Professor Sørensen, Editor in Chief of Chemical Engineering Research and Design Pistikopoulos was a great supporter of CPSE, having led the Centre as well as their co-authors (Hartmut Schoenmakers and Zarko Olujic) for seven years (2002-2009). Professor Pistikopoulos will continue received the award at the Association of American Publishers’ (AAP) to be a member of CPSE as Visiting Professor. Professional and Scholarly Publishing (PSP) Annual Conference in Washington, DC. Awarded for the best in professional and scholarly publishing, the book addresses important current research on industrial distillation, process design, operation and control aspects, and conceptual design. 6
Highlights 2014–2015 CPSE Annual Report
Researcher Award. The award is given to an individual under the Academic Distinctions and Awards age of 40 for outstanding contributions to the chemical engineering computing and systems technology literature. Dr Chachuat is the The Centre’s reputation is further enhanced by the prestigious first to have won this award outside of the USA.Dr Ruth Misener national and international awards received by CPSE academics. won the David Smith, Jr. Graduation Publication Award. The CPSE academics are international leaders in their fields and have award is given to “an individual for outstanding published work in multi-disciplinary backgrounds, including: chemical engineering, chemical engineering computing and systems technology.” The mathematics, physics and chemistry. Their expertise has been publication consists of work done whilst pursuing graduate studies. recognised by numerous awards. Dr Misener received the award for her manuscript: R. Misener, C. A. Floudas, GloMIQO: Global Mixed-Integer Quadratic Optimizer, IChemE honoured CPSE’s founding father Professor Roger Journal of Global Optimization, 57, 3-30 (2013). Sargent, considered the “Pioneer of Process Systems Engineering.”, by creating a new medal in his name, called the Professor Geoffrey Maitland was inaugurated the 74th Sargent Medal for research in computer-aided product and President of IChemE. Immediately after becoming president, process engineering. The IChemE established the medal in Professor Maitland launched the ChemEng365 blog. The daily blog recognition of the work of members of the chemical engineering catalogues 365 chemical engineering successes and achievements. academic community who have contributed significantly to the advancement of the profession and society. Professor Costas Dr Wolfram Wiesemann become a Fellow of the new KPMG Pantelides was the recipient of the Sargent Medal for 2015. Centre for Advanced Data Analytics. The centre is funded by KPMG with £10m directly (£20m total). The Centre will focus on five Two CPSE academics were amongst the 2014 IChemE winners. core areas of research: Capital, Growth, People, Operations and Professor George Jackson won the Guggenheim Medal for Resilience. The focus will be on ground-breaking analytics research excellence in thermodynamics and/or complex fluids. techniques and algorithms that will put the UK at the forefront of Dr Niall Mac Dowell won the Nicklin Medal for exceptional data science. contribution to the process sciences by an author who has graduated within the last ten years. Professor Costas Pantelides was awarded the Imperial College President’s Medal for Excellence in Innovation and Professor Nilay Shah and Professor Claire Adjiman were Entrepreneurship. elected Fellows of the Royal Academy of Engineering. The Academy’s Fellowship represents “the nation’s best engineering researchers, innovators, entrepreneurs, business and industry leaders.” Election to the Academy is by invitation only.
Professor Eva Sørensen won the highly prestigious Inspiration Award for Women which supports Breakthrough Breast Cancer. Professor Sørensen featured on a list of luminaries which included J.K. Rowling and Maya Angelou. Professor Sørensen was nominated for the Inspirational Teacher Award but was instead awarded an Inspiration Award for her outstanding contributions to education at University College London and further afield.
Dr Benoît Chachuat and Dr Ruth Misener each won an AIChE Computing & Systems Technology Division (CAST) Award. Dr Benoît Chachuat received the CAST Outstanding Young 7
Tareq and Ibrahim were recognised as rising stars in the Gulf State of Qatar winning the award for their outstanding PhD research which could have a major impact on industry in Qatar.
Post Doctorate Distinctions and Awards
Yun-Bo Zhao (supervisor Dr J Krishnan) was selected in the 1000Plan programme for young talent. The initiative aims to recruit, and provide financial support for outstanding scientists and leading experts who will work in China and play a leading role in the development of high-tech industries or new fields of study in the nation’s major innovation projects, key programmes of study or laboratories, central enterprises or state-owned financial institutions, or high-tech development zones or industrial parks. Student Distinctions and Awards
Once again, all of our graduates who were applying for jobs were successful. Below are examples of some of the awards they have won. High Profile Events
President of the Republic of Singapore’s Visit Thapanar Suwanmajo (supervisor Dr J Krishnan) and Pongsathorn In October 2014, the President of the Republic of Singapore, Tony Dechatiwongse (supervisor Professor Geoffrey Maitland) won the Tan Keng Yam was hosted and given a tour of the Carbon Capture 2014 Anglo-Thai Education Awards in the Engineering/Technology Pilot Plant by Professor Nilay Shah (CPSE Director) and Professor category. The Award for Excellence is given to Thai postgraduate Alice Gast (Imperial President). students studying in the UK who have exceptional academic achievements. 17th British-French-German Conference A number of CPSE academics, students and researchers were part of Ioscani Jiménez Del Val (supervisor Dr Cleo Kontoravdi) won the the team that organised the 17th British-French-German Conference Dudley Newitt Prize for Computational/Theoretical Excellence. on Optimisation. The conference was 17th of the series of French- German meetings which started in Oberwolfach, Germany in 1980. Susie Sou (supervisor Dr Cleo Kontoravdi) won the best poster prize Since 1998, the conference has been organised under the participation at the UK Meeting of the European Society for Animal Cell Technology of a third European country. This time it was jointly organized with in Nottingham. Britain and took place at Imperial College London. The conference consisted of invited plenary talks, parallel invited and contributed María Fuentes Gari (supervisor Professor Sakis Mantalaris) won sessions. The conference was organised by Imperial College London, second prize at the 2nd Young Entrepreneur Award Competition the Department of Computing, the Centre for Process Systems (YEA). YEA is an international business plan competition organized by Engineering and the Imperial College Business School. the Fourth Valley Concierge Corporation and Asia Innovators’ Initiative. President, Nobuyuki Idei, Former CEO of Sony Corporation presented the award. Enhancing Education
Aiman Alam-Nazki (supervisor Dr J Krishnan) won an EPSRC Prize The CPSE continued to expand and develop education in Fellowship. The Prize Fellowship is a scheme intended to help Process Systems Engineering. universities attract and retain the very best newly qualified PhD graduates, who have been supported by the EPSRC. Aiman Alam-Nazki also won the Dudley-Newitt Prize for Theoretical/ Computational Excellence, an award given annually to the best thesis New Courses in the Chemical Engineering Department at Imperial in this category. Optimisation Courses The CPSE identified the need for technical training in optimisation CPSE students dominated the awards at the Qatar Energy R&D and to address this created two new courses. In April 2015, the first Award for two years running. 2014, Tareq Al-Ansari (co-supervisor course took place with participants from CPSE Industrial Company Professor Nilay Shah) and in 2015, Ibrahim Daher (co-supervised by Members and PhD students. Professor Geoff Maitland and Dr John Crawshaw) won the Qatar Energy R&D Award.
Images: (top left) Professor Nilay Shah (CPSE Director), Tony Tan Keng Yam (President of the Republic of Singapore) and Professor Alice Gast (Imperial College President) (left) Naveed Tariq and his Team win BBC’s Eggheads (above) Philanthropic Support from Alumni – Izzati Mohd Noor, the first to receive the Marit Mohn PhD Scholar 8
• The Introduction to Optimisation Course provides an Lectures and Seminars introduction to concepts in problem formulation and solution methods for linear, nonlinear and mixed-integer problems, Lectures focusing on local optimisation methods, with a brief introduction Annual Professor Roger W. H. Sargent Lecture to global optimisation. On the first Thursday in December, CPSE annually celebrates its • The Advanced Optimisation Course builds on the founding Academic Father Professor Roger Sargent through the introductory course and focuses on concepts in global Professor Roger W. H. Sargent Lecture. This tribute to Professor optimisation, bilevel optimisation, dynamic optimisation, Sargent celebrates his legacy in the field of Process Systems optimisation under uncertainty. Engineering. Recent eminent speakers who delivered the lectures are: Detailed information on the courses is available on the CPSE website. 2015 Professor Venkat Venkatasubramanian, Columbia University. “Process Systems Engineering at Crossroads: Part-time MSc in Process Automation Challenges and Opportunities in the Era of Watson.” The modular part-time MSc in Process Automation, Instrumentation and Control was launched in December 2014. The aim of the 2014 Professor Stratos Pistikopoulos FREng, CPSE, Imperial programme is to broaden and deepen the expertise and experience of College London. “Multi-Parametric Programming & Control 25 years personnel employed in process automation, either in the design and later: what is next?” development of control and related systems, in their application, or in their operation and management. A highlight of the year has been Seminars accreditation of the programme by IChemE, IET and the Institution of CPSE has been running a successful Seminar Series for many years Measurement and Control. and each year we invite distinguished national and international experts to the Centre. For over six years Dr J Krishnan has been organising the CPSE Seminar Series. From 2015, Dr Ruth Misener New Institutions and Dr Panos Parpas have taken on the tradition of hand picking speakers from around the world. CPSE Industrial Consortium CPSE has been instrumental in the creation of two new institutes. members are all welcome to attend these seminars.
Sustainable Gas Institute (SGI) 2014 CPSE Seminar Series Professor Nigel Brandon (Director) and Dr Adam Hawkes (Deputy Professor Arthur D. Lander, University of California, Irvine, CA Director) launched the Sustainable Gas Institute (SGI) in May 2014. The Professor Nick Sahinidis, Carnegie Mellon University Institute is a unique academic-industry partnership and a ground- Professor L. N. Trefethen, University of Oxford breaking collaboration between the United Kingdom and Brazil. Their role is to lead research and define innovative technologies that enable 2014 Special Seminars natural gas to play a key role in a low-carbon world. The institute is a Professor Julio Banga, CSIC, Spain multi-disciplinary organisation operating on a ‘hub and spoke’ model, Professor Ambros Gleixner, Zuse Institute Berlin with their international research hub at Imperial College London and Professor Ignacio E. Grossmann, Carnegie Mellon University spokes in development at leading research universities around the world Professor Jay H. Lee, Daejeon, Korea with a particular focus on Brazil. They manage, lead and deliver Mr Hernan Leovey, Humboldt University world-class research with global partners across the spectrum of Dr Mark Peters, UNISA science, engineering, economics and business. Professor B. Erik Ydstie, Carnegie Mellon University
Institute for Molecular Science and Engineering (IMSE) 2015 CPSE Seminar Series Professor Claire Adjiman (Co-Director) and Professor Nicholas Professor Ana Barbosa-Póvoa, Técnico Lisboa, Portugal Harrison (Co-Director) established the Institute for Molecular Science Professor Robert Bixby, Gurobi, USA and Engineering (IMSE) in August 2015. IMSE is one of Imperial Professor Leo Liberti, École Polytechnique ParisTech, France College London’s Global Institutes, drawing on the strength of it’s four Professor Alexander Mitsos, RWTH Aachen faculties to address some of the grand challenges facing the world Professor Kim Chuan Toh, National University of Singapore today. The Institute’s activities are focused on tackling problems Professor Philippe Toint, Université de Namur, Belgium where molecular innovation plays an important role. The Institute brings together researchers from a diverse range of specialisms to This is my last Annual Report publication as the Director of CPSE. network, communicate and collaborate. The institute also connects I will be stepping down and passing on the reins to Claire Adjiman these researchers with a wide spectrum of stakeholders including on 1st August 2016 and moving to the post of Head of Department industrialists, interested individuals, government representatives, and of Chemical Engineering at Imperial College London. It has been a researchers from other academic institutions, to enhance discovery great pleasure to see CPSE grow in size and breadth, while and innovation within the molecular field. continuing to excel in both fundamentals and applications. I leave it in the capable hands of Claire, however, I will remain part of CPSE. Professor Nilay Shah, CPSE Director. 9
CPSE Industrial Consortium Graham Elkes
“Members of the Industrial Consortium can scope out opportunities for optimising their interaction with CPSE through company-specific workshops and one-to- one interaction with leading academics across a broad range of disciplines.” 10
CPSE Industrial Consortium
The Centre started the Industrial Consortium when it was inaugurated in 1989 to address challenges facing industry
Companies have increasing pressures to stay ahead of their can be accessed through consortium membership. Members will be competitors. They need to be innovative, continuously launch new directed to key academics in both universities. products and improve existing products and processes. In today’s • Access to worldwide networking with major companies. The global market companies are faced with additional pressures to make consortium provides a neutral platform for intercompany networking their operations more energy efficient, safe and environmentally and benchmarking with some of the largest multinational companies. benign. Science and Engineering play a vital role in underpinning the • Staff training: the consortium provides an opportunity for company success of the majority of today’s commercial businesses. the CPSE employees to attend courses on optimisation. Industrial Consortium provides “a one-stop-shop” for companies • A member of academic staff (“friend”) as a liaison point for your seeking solutions to improve their products and operations. Member company companies are invited to become involved in the specification, development, validation and final commercial implementation of We offer: algorithms, software tools and methodologies derived from leading- • At least one active collaborative research project edge generic research performed in the Centre. Our members also • Interns for flexible internship projects have opportunities to guide our research and development resources • An annual, company-specific workshops to scope out through joint programmes and MSc projects. They are able to access opportunities and review technology in one or half-day workshops designed in • A warm welcome to company staff to secondments in CPSE conjunction with individual members, as well as, participating in • The CPSE Newsletter additional technology focus briefings for specific sectors. We also hold • A one-stop-shop for systems engineering technology and an annual meeting hosted by CPSE at Imperial College. This includes solutions to problems the annual Roger Sargent lecture, short lectures by research students, • Access to facilities and expert assistance for cutting edge guest lectures by consortium members, research updates by software evaluation academic staff and opportunities for informal social and technical • The provision of opportunities for inter-company networking and meetings. benchmarking • A credible, world-class partner for joint proposal development Our members join the CPSE Industrial Consortium to gain and joint projects • Privileged access to world-class academics from two top • Opportunities for member companies to interact with the Centre universities. CPSE academics between them have over 500 years of at a range of levels research experience. They come from many disciplinary areas • Access to an exclusive members-only website including: chemical engineering, mathematics, physics and chemistry and are leaders in their fields. • Access to well-trained PhD students and Post Doctoral researchers. Industrial Consortium Company Members The Consortium provides opportunities for members to interact with the Centre at many levels. Members are able to evaluate and recruit Company Academic Friend high calibre PhD students and Researchers from around the world. ABB Corporate Research Professor Nina Thornhill • The opportunity to exploit and develop research and resources. AkzoNobel Professor George Jackson Members have the opportunity to guide research development and BP Professor Nilay Shah resources towards their own business needs and have access to all ExxonMobil Dr Ruth Misener the non-confidential reports of work carried out by the Centre. Petrobras Professor David Bogle • Partnerships: Membership opens the opportunity for the creation of Praxair Dr Benoît Chachuat partnerships. Some consortium members have recognized the need PSE Professor Costas Pantelides to develop in-depth and long-term research relationships with CPSE Proctor and Gamble Professor Erich Müller and have opted to establish Partnerships. Shell Research & Technology Professor Geoffrey Maitland • Links to other Imperial College and UCL Departments. Imperial Syngenta Professor Claire Adjiman College and UCL have many other world-class departments which 11
CPSE Research Programme Professor Claire Adjiman
“Research carried out over the last few years has shown that the modelling techniques developed for the process industries by CPSE can deepen our understanding of a wide range of complex systems from the chemical processes within living cells to national energy supply chains.” 12
CPSE Research Programme
Application Domains Supply Systems Engineering Energy Systems Engineering Energy Biological Systems Engineering Molecular Systems Engineering Chemical Manufacturing Systems Environmental Systems Engineering Environmental
Competence Areas
Process and Product Design
Operations and Control
Modelling and Model Solution Tools
Computational Optimisation and Machine Learning
A new competence area has been created called Computational Optimisation and Machine Learning to focus on developing in a rapidly evolving area. 13
Competence Areas Dr Benoît Chachuat
“The CPSE offers a unique experience to graduates, including the opportunity to work with internationally renowned academics and some of the biggest industrial companies in the world.” 14
Competence Area Product Process and Design
CPSE research in Product and Process Design tackles the Traditionally, the water industry relied on civil engineering to solve its constraints and objectives imposed by today’s business challenges but the expertise in the chemical-engineering field is environment, in particular, in the field of sustainable development. being increasingly relied upon. Chemical engineers can play a vital role in reducing water losses by transferring knowledge from the We take into account the economic, environmental, safety and process industry to the provision and distribution of potable water. health aspects and use systematic model-based methodologies for The objective of the work in CPSE focuses on the development of the rational design of processes encompassing a growing range of predictive mathematical models based on first principles and the scales, such as: application of optimisation techniques to provide an optimal process • Nano-scale models for materials selection flowsheet. • Meso-scale models for design of specific processes • Overall process models for integrated plant design
There are several themes within Product and Process Design, however, the areas that we are concerned with are: Materials design for process synthesis such as development of methodologies property prediction techniques; the design problems with a large number of degrees of freedom (molecular structure, microstructure, formulation variables etc.) Another theme is the design of novel Figure 2: Creating a model representation of water treatment manufacturing processes. Here we are interested in the processes and their interactions to mitigate risk development of models and techniques for design of state-of-the- art processes, with a particular emphasis on fine chemicals and Currently, work within the clean-water industry relies heavily on pharmaceuticals. We also look at the integrated process synthesis empirical/hydraulic models. This is due to the clean-water industry and the development of tools for the analysis of interactions being quite traditional in the way it approaches its problems. between design and operability. Technology transfer is also an However, it is slowly realising the importance of maintaining a interesting theme which still requires more study. In particular, the competitive edge. Our research looks at deriving individual unit facilitation of more mature technologies to industrial partners still models and validating and combining units and considering remains a challenge. plant-wide operation. By incorporating the use of mathematical models that can describe the processes, we believe industry can develop its understanding of a unit and be able to find more cost-effective solutions.
To create a model representation of water treatment processes and their interactions to mitigate risk
• Each unit is derived and validated separately and then uses a Figure 1: Drinking water is a limited resource plug flow reactor (PFR) model to represent the distance the water has to travel between various process units • The process flowsheet is used to reflect the units operated, Water Treatment – Predictive modelling of chemical additive processes and the physical processes that conventional clean water treatment can be modelled using first principles to deepen the Eva Sørensen understanding of how each unit operation works. A major challenge currently facing a sustainable future is the ever increasing demand for clean water of adequate quality and quantity. 15
modelling, optimisation and chemical engineering insights to Figure 3: Optimisation of WTW based on superstructures formulate the general mixture problem. Within this approach, the optimal number of components in a mixture, their identities and The advantage of having a dynamic model of a clean water compositions are determined simultaneously. A logic-based treatment process is invaluable. To demonstrate the applicability of methodology, Generalised Disjunctive Programming, is used to the overall plant model, a sensitivity analysis can be performed by express the general mixture problem within a mathematical considering the impact of a disturbance propagating through the framework and formulate the discrete choices inherent in the process for an illustrative case study, where the concentration for problem. source of raw water inlet changes. The case study is implemented in gPROMS. The results produced are reflective of how a system The novel framework proposed has been applied successfully to the would react to a change like this. design of solvent mixtures for separation processes, including crystallisation and liquid-liquid extraction. Significant benefits can There are various different processing units available for each accrue by employing this approach in product design, especially as specific process type. For example, coagulation and flocculation the number of desirable mixture components increases: the explicit can occur in a CSTR or the chemical coagulant can be injected at evaluation of every choice of the number of components is avoided, one point and allowed to flow through different chambers creating a making it possible to consider larger design spaces. turbulent flow. There can be multiple units of the same process in parallel as well as for different water sources; some unit configurations work better.
Rational mixture design: optimisation-based approaches Claire S Adjiman and Suela Jonuzaj
The formulation of mixtures offers a potential route to enhanced performance across a wide range of chemical engineering applications, from separation processes to product design. However, mixture design can be very challenging because it requires The work has been published in Jonuzaj et al. (2016) and Jonuzaj and Adjiman (2016), finding the optimal number, identities and compositions of mixture and will be presented as a keynote at the 26th European Symposium on Computer components and using nonlinear property models, which results in Aided Process Engineering (http://escape26.um.si/). complex nonlinear problems with a large combinatorial space. Thus, a restricted version of the problem is usually posed, where the Jonuzaj S., Akula P. T., Kleniati P. M., Adjiman C. S., 2016. The formulation of optimal number of mixture ingredients is fixed in advance, before other mixtures with Generalized Disjunctive Programming: A solvent design case study. AIChE design decisions are made. This restricts our ability to identify the Journal. DOI: 10.1002/aic.15122. optimal mixture.
Jonuzaj S., Adjiman C. S., 2016. A Convex Hull formulation for the design of optimal In view of these challenges, our work focuses on developing a mixtures. In: 26th European Symposium on Computer Aided Process Engineering. comprehensive and systematic methodology within the Computer- Available online: http://escape26.conforganizer.net/upload/escape26/abstracts/ Aided Mixture/blend Design framework by combining mathematical files/26-efe3-Jonuzaj-and-Adjiman_Escape26.pdf. 16
Competence Area Operations and Control
Process Operations uses mathematical models that capture the This project is concerned with a methodology for combining underlying science of a process and adopts an optimization multi-parametric programming and NCO tracking into a unified approach to give improved operation in terms of product quality, framework for model predictive control, for which we coined the energy usage, environmental impact and sustainability. The research name “multi-parametric NCO-tracking control”. Such a combination within the Centre covers optimization of the operations of existing is especially promising in that using feedback laws tracking the plants, optimal designs for new plants that take account of dynamic optimality conditions inside a multi-parametric controller has the operation at the design stage, management of supply chains and of potential to dramatically reduce the number of critical regions batch processing. compared with classical mp-MPC controllers based on time discretization. Moreover, multi-parametric programming provides a Process control covers the theory and practice of advanced means for relaxing the fixed switching structure assumption in automation and control applied to a wide variety of processes NCO-tracking, thereby paving the way towards a theoretical including reaction, adsorption, granulation and polymerization justification for NCO-tracking too. Our initial focus has been on carried out within a spectrum of manufacturing industries including constrained linear dynamic systems, and extensions to the general oil & gas. Competencies feeding into applications include: integration nonlinear case are now being investigated. of design; operation and decision making; multi-scale modelling; integrated monitoring of processes; electrical and mechanical equipment; and theoretical advances in robust parametric control. A special feature of the programme is the ability to move new theory rapidly towards practical realisation and thus to help the process control sector take early advantage of new developments.
A selection from the activities in the past year includes:
Multi-parametric NCO-tracking controllers for linear dynamic systems Driven by the need to improve performance and reduce economic costs in industrial processes, on-line optimization and real-time control have been receiving a lot of attention. The strategy employed in classical model predictive control (MPC) is to solve the optimization problem in a receding horizon manner. This is often a rather computationally demanding task that may cause serious delays especially for systems with fast dynamics, leading to suboptimal performance or even infeasibility. In the multi-parametric programming paradigm, the optimization is performed off-line, resulting in a priori explicit mapping of the solutions, effectively control strategies as a function of measurable quantities. Likewise, NCO tracking is a measurement-based optimization approach to enforcing optimality in the presence of uncertainty, via tracking of the necessary conditions for optimality (NCO). Figure 1: Comparison between the critical regions in a mp-NCO- tracking controller (top plot; 11 regions) and a mp-MPC controller over 50 stages (bottom plot; 1687 regions) for a constrained FCC unit operated in partial combustion mode. 17
Robust MPC using set-based methods Process Automation Research Programme Classical MPC control is based on a certainty-equivalence principle, whereby the future of the system is optimized as if neither external Worldwide, there is a huge inventory of currently installed process disturbances nor model mismatch were present. Although these plants and our research finds ways of helping these to run efficiently uncertainties are the main reason why feedback is needed in the and smoothly. This is achieved by optimizing the operation of the first place, the main advantage of certainty-equivalence in MPC is process and equipment by detection and diagnosis of the root that the resulting optimization problems can often be solved causes of process inefficiencies. The methods make use of all efficiently, in real time. Moreover, this approach works well in many available information, not only measurements from operating practical applications, and it often exhibits a certain robustness due processes but also qualitative and connectivity information from its inherent ability to reject disturbances. However, the constraints process schematics and drawings, plus reasoning from scientific may become violated when large disturbances occur, since first principles. uncertainty is not taken into account in optimizing the predicted state trajectories. In such cases, robust MPC schemes may be used Process plants depend upon mechanical and electrical equipment. to mitigate these optimistic predictions. We are looking at measurements from the mechanical and electrical sub-systems to understand the whole picture and are also exploring Our focus in this project is on robust MPC schemes using set- the interactions between a.c. transmission grids and process plants based methods, known collectively under the name tube-based which are large electrical consumers. The work is being undertaken MPC. The predicted trajectory is replaced by a robust forward by Imperial researchers, industrial research engineers on invariant tube (RFIT) in the state-space, namely a tube that encloses secondment and PhD students sharing their time between Imperial all possible state trajectories under a given feedback control law, and industrial placements with collaborating companies. More which is independent of the uncertainty realization. In contrast to information on Process Automation is available at: existing methods which parameterize the control law, our approach http://www3.imperial.ac.uk/processautomation introduces a min-max differential inequality exploiting the properties on the boundary of RFITs. These min-max differential inequalities Detection of Disturbances provide sufficient conditions for a time-varying convex-set-valued The process automation group develops methods for detection and function to be an RFIT, for an inclusive class of input-affine nonlinear diagnosis of process disturbances. Recently, the work has examined control systems. We also derive practical implementations of transient disturbances in multi-rate systems. The motivation for these tube-based MPC based on ellipsoidal calculus, which (i) scale developments is that there is an increasing industrial requirement for linearly with the length of the prediction horizon, and (ii) do not rely the analysis of data sets comprising measurements from industrial on a particular parameterization of the control law. In principle, this processes together with their associated electrical and mechanical approach can achieve arbitrary precision insofar as the tubes are equipment. These systems are increasingly affected by transient represented with sufficient accuracy. The construction of robust disturbances, and their measurements are commonly sampled at MPC controllers with such properties is unprecedented for nonlinear different rates. Progress with these objectives is illustrated in Figure 3. input-affine systems. The methods are based on nearest-neighbours techniques, meaning This work is a collaboration with ShanghaiTech (Dr. Houska) and the that they identify occurrences of similar patterns in the time trends. University of Freiburg (Prof. Diehl). They build a vector of anomaly indices which are high for the period with the transient disturbance. The general applicability of the above methods is well illustrated by case studies from oil and gas plants and from an experimental compressor rig where process measurements are treated together with electrical measurements from the variable speed drive.
Recently the same methods have been used for automated detection of transient events in an electrical transmission grid as measured by instruments called Phasor Measurement Units. Power system disturbances generally result from the penetration of heavy or light loads, sudden changes in the operation conditions, and faults.
The timescale is much faster than that of events in a process system. Detection of power-system disturbances is a difficult task because of system complexity, diversity of operating conditions and interference from noise. It places high demands on reliable, sensitive and real-time implementation. The successful results show that Figure 2: Ellipsoidal RFIT for robust MPC control of a constrained methods can be adapted across time scales. spring-mass-damper system, along with three uncertainty realizations (dashed blue lines). 18
References Cai, L., Pal, B.C. and Thornhill, N.F., 2016, Multivariate detection of power system disturbances based on fourth order moment and singular value decomposition, submitted to IEEE Transactions on Power Systems.
Cecilio, I., Ottewill, J.R., Fretheim, H., and Thornhill, N.F., 2015, Multivariate detection of transient disturbances for uniand multi-rate system IEEE Transactions on Control Systems Technology s, 23, 1477-1493,
Cecilio, I., Ottewill, J.R., Pretlove, J., and Thornhill, N.F., 2014, Figure 3: Disturbance detection methods for transient and Nearest neighbors method for detecting transient disturbances multirate systems. in process and electromechanical systems, Journal of Process Control, 24, 1382-1393. The work has received financial support from the Portuguese Foundation for Science and Technology (FCT) under Fellowship SFRH/BD/61384/2009, from the Marie Curie FP7-IAPP project “Using real-time measurements for monitoring and management of Operations and Control – Highlighted project power transmission dynamics for the Smart Grid – REALSMART”, Supercritical gas recycle for surge control of CO2 centrifugal Contract No: PIAP-GA-2009-251304, and from EPSRC compressors EP/L014343/1 “Stability and Control of Power Networks with The highlighted project concerns computer-based design and Energy Storage (STABLE-NET)”. analysis of control systems for centrifugal compressors when the
operating fluid is supercritical CO2. The work has implemented a Multi-criterion manufacturability indices for ranking high- non-linear dynamic model including a main forward compression concentration monoclonal antibody formulations line together with hot and cold recycles. The work is based on a The need for high-concentration formulations for subcutaneous validated model of a CO2 compressor station in collaboration with delivery of therapeutic monoclonal antibodies (mAbs) can present the industrial partner. manufacturability challenges for the final ultrafiltration/diafiltration (UF/DF) step. Viscosity levels and the propensity to aggregate are Industrial compressor trains typically use both hot and cold gas key considerations for high-concentration formulations. recycle for the purposes of surge avoidance. The idea is that the operating fluid is recycled back to the compressor inlet if the flow This project created a novel framework for deriving a set of rate reduces such that the operating point of the compressor manufacturability indices related to viscosity and thermostability to approaches the surge line. Hot recycling feeds fluid back to the rank high-concentration mAb formulation conditions in terms of their compressor inlet directly through the recycle valve, while cold ease of manufacture. This is illustrated by analysing published recycling also cools the fluid. Ideally recycling would be avoided high-throughput biophysical screening data that explores the since recycling of already-compressed fluid represents a waste of influence of different formulation conditions (pH, ions and excipients) energy. On the other hand, the compressor must be protected from on the solution viscosity and product thermostability. surge, and at the same time must fulfil delivery of the operating fluid to the downstream processes or pipeline in the right thermodynamic The project used a decision-tree classification method, CART state. The analysis in this project has provided some insights into (Classification and Regression Tree) to identify the critical formulation the dynamics and control of the two configurations. conditions that influence the viscosity and thermostability. The ultimate industrial deliverable from the work was a set of stress The work demonstrated that compared to the hot recycle, the maps which show viscosity and thermostability as functions of the process configuration including a cold gas recycle has better overall formulation conditions and time profiles during UF/DF. stability, but higher power consumption and lower values for the control performance indicators. Moreover it compares subcritical The framework helped to identify the optimal formulation conditions and supercritical compression during surge prevention and that minimize the potential for both viscosity and highlights the importance of the selection of the gas recycle aggregation issues during UF/DF. configuration when full recycle is needed. The key findings are outlined in the table on the right. The work is a sub-project of the EPSRC Centre for Innovative Manufacturing in Emergent Macromolecular Therapies led with UCL. It is sponsored by EPSRC and pharmaceutical companies including GE Healthcare, GlaxoSmithKline, Pfizer and MedImmune. 19
Cold recycle
Advantages: No issues of overheating since the recycled gas is Disadvantages: Repeated opening and closing of the recycle valve cooled. No loss of machine integrity if the machine runs occurs because the inlet pressure increases when recycled fluid is continuously in recycle mode. fed back. This causes interaction between the surge control system and the pressure control system. Higher overall power consumption and lower pressure control performance
Hot recycle
Advantages: Simple layout and rapid response due to short pipe Disadvantages: Repeated opening and closing of the recycle valve runs. Less gas is recycled than with cold recycle system. can occur because recycle of hot gas increases the inlet Better pressure control performance. temperature, which has an impact on the location of the surge region. The machine can overheat due to the high temperature of the recycled gas. Therefore the duration of operation with hot recycle is limited.
Recycle of subcritical CO2 Recycle of supercritical CO2
Cold recycle circulates 23% more gas than hot recycle and hence Cold recycle circulates 82% more gas than hot recycle due to the equipment sizing will be similar. Designs may be based on change of state from supercritical to subcritical. Therefore cold considerations outlined above in this table. recycle may be more effective for supercritical CO2 surge protection.
The work was funded by the Marie Curie Marie Curie FP7-ITN project “Energy savings from smart operation of electrical, process and mechanical equipment – ENERGY SMARTOPS”, PITN-GA- 2010-264940,and by EPSRC EP/J020788/1 Gas-FACTS: Gas – Future Advanced Capture. Thank you also to ESD Simulation Training for their encouragement, advice and technical support for the project
References Budinis, S., and Thornhill, N.F., 2015, Supercritical gas recycle analysis for surge control of centrifugal compressors, Computer Aided Chemical Engineering (Proceedings of ESCAPE 25), 37, 1583-1588, 2015.
Budinis, S., and Thornhill N.F., 2016, Supercritical gas recycle for surge control of CO2 centrifugal compressors, submitted to Computers & Chemical Engineering (invited paper). 20
Competence Area Modelling and Model Solution Tools
The development of new and improved Modelling and Model Global Sensitivity Analysis (GSA) Solution tools is a key factor in maintaining the excellence of CPSE’s GSA is used to identify key parameters whose uncertainty most academic research and has led to many of the software packages affects the output. This information can then be used to rank in this area that are now the accepted standards in industry. variables, fix unessential variables and decrease problem dimensionality1, 2. Over the last decade GSA has gained acceptance The models and solution tools in use and under development in among practitioners in the process of model development, CPSE focus on different spatial and temporal scales across a wide calibration and validation, analysis of problem structure, reliability range of process systems engineering problems. Four recent and robustness analysis, decision-making under uncertainty, examples are described below: quality-assurance, and complexity reduction3. The variance-based method of global sensitivity indices (SI) developed by Sobol’ has Zacros become the method of choice among practitioners due to its Zacros is a Kinetic Monte Carlo software package written in Fortran efficiency and ease of interpretation. However, there is an important and developed at UCL for simulating molecular phenomena on class of practical design problems involving inequality constraints catalytic surfaces. The tool enables researchers in the areas of imposing structural dependences between model variables in Computational Catalysis and Surface Science to perform dynamic addition to potential correlations between them. modelling of adsorption, desorption, surface diffusion, and reaction processes on heterogeneous catalysts. The rates of these The development of efficient computational approaches for elementary processes are typically computed from ab initio constrained GSA (cGSA) is challenging because the feasible domain simulations, thereby enabling the prediction of catalytic performance of the model variables’ variation may have an arbitrary shape metrics (such as activity and selectivity) from first principles, and the including non-convex or disconnected (as opposed to detailed validation of hypothesised kinetic mechanisms against hyperrectangular spaces considered within conventional GSA). experimental data. We have proposed a novel concept of constrained Global Sensitivity The package employs the Graph-Theoretical KMC methodology Analysis which adds the ability to analyse model output variance in coupled with cluster expansion Hamiltonians and Brønsted-Evans- such domains. The advantage of the presented formulations is that Polanyi relations, which can naturally capture: steric exclusion no prior knowledge of conditional or marginal distributions is effects for species that bind in more than one catalytic site; complex assumed. All the required dependences are derived from the joint reaction patterns involving adsorbates in specific binding p.d.f. and, furthermore, in the presence of constraints it is sufficient configurations and neighbouring patterns; spatial correlations and to know the joint p.d.f. corresponding to the unconstrained ordering arising from adsorbate lateral interactions that involve formulation. many-body contributions; changes in the activation energies of elementary events, influenced by the energetic interactions of Grid cubature and Monte Carlo estimates have been proposed for reactants with neighbouring spectator species. the evaluation of main and total effect indices. The new approach amounts to greatly expanding the scope of GSA to a wide range of The software was commercialised by UCL Business in Nov-2013, situations of practical importance involving inequality constraints. and has a dedicated website (http://zacros.org) with documentation, tutorials, list of publications and links to e-Lucid, the For more information about GSA please contact S. Kucherenko and UCL online licensing portal from where users can obtain Zacros O.V. Klymenko. from. The code can be obtained free of charge by academics, and since inception it has been distributed more than 70 users in 25 countries worldwide. For more information about Zarcos please contact Michail Stamatakis ([email protected]). 21
Figure 2: bounds on the reachable set (shaded area) of a two-step anaerobic digestion model with uncertain initial conditions. The coloured lines correspond to different set-parameterizations and expansion orders.
Figure 1
Set-Valued Integration of Uncertain Dynamic Systems Many engineering design and control problems can be formulated, analyzed and solved in a set-based framework. When it comes to designing a control system for instance, the constraints, uncertainties and design specifications are described naturally in terms of sets. In measuring the effect of a disturbance on a system’s response or in bounding the error of an estimation algorithm likewise, sets play a central role. A number of key set-theoretic concepts were proposed in the early 1970s, but their systematic application was not possible until enough computational capability became widely available. Today, many such methods and tools are available for the estimation and control of linear systems, but it is less so for nonlinear systems.
The development of set-valued integration algorithms for uncertain dynamic systems has been an on-going research area in Dr Chachuat’s group for over 10 years. Central to these approaches is the ability to Figure 3: Basic schematic of the MUSE (modular energy system compute tight enclosures of the range of multivariate systems, simulation environment). The market clearing algorithm iterates e.g.,using ellipsoidal calculus or higher-order inclusion techniques amongst all sectors until they agree on price and quantity for each based on multivariate polynomials. In recent years, we have developed energy commodity. efficient methods, both continuous-time and discretized approaches, capable of propagating generic set-parameterizations in order to yield The Sustainable Gas Institute is developing a new energy systems tight enclosures on the reachable set of an uncertain ODE or DAE simulation environment. Instead of using intertemporal optimisation system. Moreover, sufficient conditions that guarantee stability of the like many other models, it strives to simulate investment and activity bounding system have been identified for the first time. in each sector of the global economy (split into roughly 30 regions) in a way that is appropriate for each sector. The model is bottom- For more information on set-valued integration please contact up, including engineering detail and basic economic characteristics Benoît Chachuat. for thousands of technologies. It is built on the principles of simplicity and transparency, and the modelling framework will Simulation of long-term global energy transitions ultimately be made open source. For further information about The 5th Assessment Report of Working Group 3 of the global energy systems modelling please contact Adam Hawkes. Intergovernmental Panel on Climate Change was released at the end of 2014, setting out approaches to climate-change mitigation. 1 Saltelli A. Tarantolla S., Campolongo F., Ratto M. (2004). Sensitivity analysis in A number of models were used to support this study, each being practice, Wiley, New York. global in scope, with long time horizons to capture the dynamics of 2 Saltelli A., Annoni P., Azzini I., Campolongo F., Ratto M., Tarantola S. (2010) climate change, and particularly to explore approaches to limiting Comput. Phys. Comm. 181 (2): 259–270. average surface temperature rise to less than 2ºC.The importance 3 Kucherenko S., Feil B., Shah N., Mauntz W. (2011) Reliability Engineering and of these models has increased as a result of the Paris Agreement, System Safety, 96:440–449. further pushing the ambition to limit temperature rise to 1.5ºC. 22
Competence Area Computational Optimisation and Machine Learning
The Computational Optimisation Group has a 30-year track record financial engineering and risk management. The Statistical Machine of research in decision-making under uncertainty, stochastic and Learning Group focuses on Bayesian methods. Application areas robust optimisation. Current interests of the group include include autonomous systems, robotics, time series analysis, representing uncertainty in optimisation models, designing numerical reinforcement learning, and brain-machine interfaces. Several other optimisation algorithms and computational software frameworks, groups within CPSE also have strands of research in computational and applying these algorithms to energy production, capacity optimisation. planning, manufacturing and distribution models under uncertainty,
Area Academic Expertise
Bayesian Optimisation Deisenroth, Misener Algorithm design, Optimisation for machine learning, Parameterestimation
Optimisation-based Control Bogle, Chachuat, Deisenroth, Dynamic optimisation, Multiparametric programming, Optimal Dua Control
Implementations & Software Adjiman, Chachuat, Fraga, Deterministic global optimisation, Global sensitivity analysis, Kucherenko, Misener Set-membership estimation, Mixed-integer nonlinear optimisation, Multi-objective optimisation
Large-Scale Convex Parpas Multiscale optimisation Optimisation Machine Learning Deisenroth Gaussian processes, Reinforcement learning, Bayesian inference, Graphical models, Active learning/optimal design
Mixed-Integer Nonlinear Adjiman, Chachuat, Misener alphaBB, Algorithm design, Cutting planes, Deterministic global Optimisation optimisation, Implementations & software, Multivariable relaxations
Multilevel Optimisation Adjiman, Rustem, Wiesemann Bilevel optimisation, Minimax, Semi-infinite optimisation
Optimisation under Rustem, Wiesemann, Fraga Chance-constrained systems, Risk management, Robust uncertainty optimisation, Stochastic optimisation
Signal Processing Deisenroth Bayesian state estimation, System identification, Inference and learning in nonlinear dynamical systems 23
Highlighted Project Highlighted Project References: Bayesian Optimisation with Dimension Scheduling: • C. Baroukh, R. Munoz-Tamayo, J.-P. Steyer, O. Bernard, 2014. Application to Biological Systems DRUM: A new framework for metabolic modeling under non- balanced growth. application to the carbon metabolism of Highlighted Project Authors: Doniyor Ulmasov, Caroline Baroukh unicellular microalgae. PLoS ONE 9 (8), e104499. (INRA, France), Benoît Chachuat, Marc Peter Deisenroth, • D. Ulmasov, C. Baroukh, B. Chachuat, M.P. Deisenroth, R. Ruth Misener. Misener, 2015. Bayesian Optimization with Dimension Bayesian Optimisation (BO) is a data-efficient, global black-box Scheduling: Application to Biological Systems. arXiv preprint optimisation method optimising an expensive-to-evaluate fitness arXiv:1511.05385. function; BO uses Gaussian Processes (GPs) to describe a posterior • Misener R., Floudas C.A. ANTIGONE: Algorithms for coNTinuous distribution over fitness functions from available experiments. Similar / Integer Global Optimization of Nonlinear Equations, Journal of to experimental design, an acquisition function is applied to the GP Global Optimization; 59: 503 – 526, 2014. posterior distribution over fitness functions to suggest the next (optimal) experiment. Deterministic Global Optimization in Nonlinear Dynamic models of biological processes allow us to test biological Optimal Control hypotheses while running fewer costly, real-world experiments. We Benoît Chachuat, Boris Houska, Nikola Perić. consider estimating biological parameters (e.g., reaction rate The problem addressed in this project is in the broad field of global kinetics) by minimising the squared error between model and optimization of dynamic systems. In a society where experimental data points. Specifically, we propose BO for efficient competitiveness and sustainability are two major drivers, this parameter estimation of a dynamic microalgae metabolism model problem has attracted a lot of attention by the PSE community over (Baroukh etal., 2014). The forcing function is based on light the last two decades. Nevertheless, existing methods fail to provide exposure and nitrate input; experimental data have been collected a certificate of global optimality for systems having more than a for measurable outputs including lipids, carbohydrates, carbon handful of time-invariant inputs (controls), let alone systems with organic biomass, nitrogen organic biomass and chlorophyll. Our time-varying inputs. method is general and may be applied to any process model.
Dr Chachuat’s group has contributed a new algorithmic framework, There are several timescales for collecting microalgae metabolism data: called branch-and-lift, that enables guaranteed global optimization an experiment may take 10 days while each model simulation of of optimal control problems, without the need for a priori Baroukh et al. (2014) runs in a fraction of a second. BO is traditionally parameterization of the time-varying inputs. Branch-and-lift applied to functions with expensive evaluation costs, e.g., running a 10 essentially yields an extension of the branch-and-bound concept to day experiment, but the objective of this paper is testing biological infinite-dimensional Hilbert space. It could be established that the hypotheses; we are specifically interested in running the simulation branch-and-lift algorithm terminates finitely for inequality- model many times for parameter estimation. constrained, input-affine dynamic systems under mild conditions. Preliminary results with case studies indicate that branch-and-lift In biological parameter estimation, BO is challenging because the greatly mitigates the curse of dimensionality and cuts the parameters interact nonlinearly and the broad parameter bounds result computational time by several orders of magnitude. These results in a huge search space. Due to the high problem dimensionality (in this are particularly significant in that they open, for the first time, the context, 10 parameters), balancing exploration versus exploitation prospect of applying global and robust dynamic optimization becomes more intricate and traditional Bayesian methods do not scale technology to industrially relevant problems. On-going work involves well. Therefore, we introduce a new Dimension Scheduling Algorithm developing an efficient implementation of the branch-and-lift (DSA) to deal with high dimensional models. The DSA optimises the algorithm, by building upon the advanced bounding techniques for fitness function only along a limited set of dimensions at each iteration. dynamic systems. In each iteration, a random set of dimensions is selected to be optimised. This reduces the necessary computation time, and allows the dimension scheduling method to find good solutions faster than the This project is an on-going collaboration with Professor Houska traditional method. The increased computational speed stems from the (ShanghaiTech University, China). reduced number of data points per GP and the reduced input dimensions in the GP; GPs scale linearly in the number of dimensions but cubically in the number data points. Additionally, considering a limited number of dimensions at each node allows us to easily parallelise the algorithm.
Compared to commercial parameter estimation for biological models and a traditional Bayesian Optimisation algorithm, our approach achieves strong performance in significantly fewer experiments and a reduced computation time. We also design and provide a graphical user interface (GUI), which allows untrained users to optimise any model that can be invoked through a command line. The framework removes the barrier of Figure 1: Convergence of branch-and-lift for a bioreactor control programming language by providing the user with a straight forward user problem (right plot), and illustration of limited clustering occuring interface to set BO parameters, observe the optimisation as the code when lifting the search space dimension M (left plot) runs, and examine the GP after the experiment has been completed. 24
Dynamic optimisation of dynamic systems in this project consists of two stages. The first stage is the validation subject to uncertainty (Carlos Perez-Galvan, of existence and uniqueness of a solution in which also a suitable David Bogle – CONACyT) a priori enclosure and a time step are obtained. The second stage involves the computation of a tighter enclosure in which a high order Many process engineering problems have critical bounds (quality, Taylor series is used to refine the solution obtained in the first stage. safety or environmental) that must be satisfied at all times. These methods are desirable in applications such as guaranteed
Figure 1. Dynamic optimisation of dynamic system using a sequential approach parameter estimation, optimal control, and safe critical applications Reduction of the overestimation where critical variables such as safety or environmental performance The major challenge in these methods is the reduction of the are an issue. In a dynamic optimisation algorithm guaranteed overestimation generated in the integration process which is mainly bounds on the dynamic variables of the models that describe caused by the dependency and wrapping effect problems. This processes are needed in order to solve the problem to global project addresses the reduction of the overestimation and the novel optimality in a rigorous way. Hence, verified bounds are a key step part of the method is the implementation of non-linear interval in the optimisation algorithm (Focus on first box of Figure 1). contractors such as Krawczyk, Newton/ Gauss-Seidel and Forward- However, the construction of tight bounds is still an issue for Backward. practical applications. This project focuses on obtaining bounds that tightly enclose the representation of the reachable set. Figure 1 represents the construction of bounds for an exothermic batch reactor using the interval Taylor series method with different Dynamic simulation interval contractor implementations, namely, no contractor (NC), Verified methods of initial value problems (IVP) for ordinary Newton and Krawczyk (K) contractors. The grey lines represent the differential equations (ODE) provide enclosures which are reachable set; they have been constructed using Monte Carlo guaranteed to contain all the possible solutions of a problem simulations (2000 samples). (possibly subject to an uncertain value). The bounding method used
Figure 2. Bounds constructed by interval Taylor series method without contractors (NC) and with Newton (N) and Krawczyk (K) contractors. 25
Global optimisation The algorithms with the Newton and Krawczyk contractors have been implemented in a global optimisation algorithm. The algorithm consists of a branch-and-bound tree, the node on which to branch was the one with the least lower bound. At each node, the variable with the greatest diameter (distance between its upper and lower bound) was selected for branching. The first order sensitivity calculations were included in order to discard regions not containing zero in its gradient.
Figure 3. Global optimisation subject to uncertainty of the oil shale pyrolysis process
Figure 3 shows a graph of an oil shale pyrolysis example in which the black line represents the optimal profile and the rest of the lines represent suboptimal trajectories. The algorithm which makes use of the interval Taylor series with contractors is able to obtain upper and lower bounds on the global optimum of this problem. 26
Application Domains Professor David Bogle, CPSE Deputy Director
“CPSE researchers are taking Process Systems Engineering research into new domains such as nanotechnology, healthcare and sustainability. This is leading to powerful new methods applicable for solving an even wider range of challenges facing chemical engineers in industry.” 27
Application Domain Chemical Manufacturing Systems
Many of the fundamental tools deveveloped in the four competence has been established that rigorous, risk-averse solutions can be areas of Product & Process design, Operations & Control, Modeling computed in reasonable time too, which could make them the and Model Solution Tools, and Optimization & Machine Learning are solution of choice in planning and decision making. motivated by the challenges arising from chemical manufacturing systems. This application domain explores the need for new technologies, more effective use of new tools of analysis, and improved integration of all elements of manufacturing operations, including machines, information and humans. Through this domain, CPSE serves several process industries such as bulk chemicals (including petrochemical and oil & gas), pharmaceuticals & agrochemicals, specialty chemicals, and biofuels.
Integrated Water Networks for Freshwater Minimization Cheng Seong Khor, Benoît Chachuat, Nilay Shah Due to the high demand for freshwater by the process industries, together with the drive for achieving sustainable development, water network synthesis problems have received increasing attention in the Figure 1: Principle of two-stage stochastic methodology for water PSE community. For the objective of minimizing freshwater use and network synthesis under uncertainty. wastewater generation, water can be reused by channeling the effluent from a water-using operation to other operations, and possibly recycled to the operations where it was generated. In further reducing freshwater and wastewater flowrates after exhausting recovery opportunities via direct reuse/recycle, water regeneration can be considered, which involves performing partial treatment on the effluent by using water treatment and purification units such as membranes and steam stripping prior to reuse/recycle.
CPSE is investigating the synthesis of optimal water networks in the `environomic’ sense – that is, maximizing economic profit and meeting certain environmental sustainability criteria at the same time – while complying with constraints on the water users and/or final discharge limits to the environment. Our focus has been on using superstructure optimization together with realistic regenerator models, which leads to challenging, nonconvex MINLP models. Industrial case studies of water networks in petroleum refineries with a large number of wastewater sources and sinks as well as multiple Figure 2: Histograms comparing the projected total annual cost regenerators have revealed that state-of-the-art global optimization distributions of risk neutral and risk-averse solutions for a water technology can be applied to tackle these problems rigorously, network consisting of 7 water-using operations, 3 sources and 3 leading in certain cases to more than 50% annual savings in sinks; the regeneration technologies considered for abatement of oil & freshwater use. Our recent work has investigated the problem of grease and suspended solids are carbon filter and reverse osmosis. integrated water network synthesis under uncertainty, with risk management using the Conditional Value-at-Risk (CVaR) metric. It 28
Towards Membrane Cascades for Isothermal Refining effective area of 14 cm2 Vincentius Surya Kurnia Adi, Marcus Cook, Ludmila Peeva, Andrew Economically Optimal Integrated Process Livingston, Benoît Chachuat and MPC Control Design Crude oil refining is the second most energy-intensive industry after Flávio Strutzel; David Bogle, CAPES the chemical industry in advanced economies. Current refinery technology is based on distillation, which typically accounts for over half of the total energy consumption due to vaporization (phase change) and the need for reflux. Membrane technology offers a promising alternative for separating mixtures without the need to employ energy intensive operations based on phase change. In particular, organic solvent nanofiltration (OSN) provides a means for separating organic-organic mixtures such as crude oil. In many cases, a mixture separation may not be achieved through a single membrane pass because OSN membranes are not selective enough between the different constituents. Instead, the mixture can be processed through multiple membranes and/or using multiple passes, namely a membrane cascade arrangement.
Given the recent advances in the development of membranes for organic mixtures and their applications in membrane cascades, this project is concerned with the possible use of membranes for hydrocarbon mixtures. We are developing a superstructure Figure 4: Benefits of MPC optimization approach based on mixed-integer nonlinear programming (MINLP) to determine the most promising cascade The use of MPC (Model Predictive Control) is nowadays ubiquitous configurations. The aim of the optimization is to determine the in the chemical industry and offers great advantages. The zone cascade design and operating conditions maximizing product purity, constrained MPC with economic optimization capabilities is today’s for a given composition of the inlet stream. Our initial focus is on a standard in the chemical industry. MPC reduces process variability binary system of heptane and hexadecane to mimic the light-key and and enables operation with lower quality giveaway, increasing heavy-key in the multicomponent environment of a representative output of high value added products and decreasing by-product petrochemical/hydrocarbon feed stream while simplifying the output. However, new chemical processes are being projected analysis. without taking into account how design choices affect the MPC’s ability to deliver better control and optimization. Therefore, a methodology to determine if a certain design option favours or hinders MPC performance is desirable.
This project develops the “economic MPC optimization index”, whose intended use is to provide a procedure to compare different designs for a given process, assessing how well a given flowsheet interacts with a generic MPC package. This index is impacted by process controllability, control resilience, control requirements and restrictions of a given plant. It quantifies the economic optimization benefits available and how well the plant performs under MPC control, thereby providing a monetization measure of expected control performance.
This approach assumes the availability of a linear state-space model valid within the control zone defined by the upper and lower bounds of each controlled and manipulated variable. Process economics provides the basis for the analysis as the index needs to be minimised in order to find the most profitable steady state within the zone constraints towards which the MPC is expected to direct the process. Special attention is paid to the effect of model uncertainty and/or disturbances on the index, which may reduce profitability by restricting the ability of a MPC to reach dynamic equilibrium near process restrictions, thus increasing product quality giveaway and Figure 3: Optimized lab-scale membrane cascade for purification of costs in turn. This approach has been demonstrated the case study heptane from a 50-50 wt% mixture of heptane and hexadecane, of a realistically sized crude oil atmospheric distillation plant using a maximum of 10 identical membrane units, each with an consisting of four alternative designs. 29
Sample Workflow – Oil Distillation Case Study
Figure 5: Illustration of the ‘economic MPC optimization index’ methodology for comparison of alternative process designs. 30
Application Domain Molecular Systems Engineering
The Molecular Systems Engineering (MSE) group has over 30 staff and Two recent papers highlight advances in developing intermolecular students and, since its inception, has published close to 200 papers potential models for use with the SAFT-VR Mie equation of state and many of which have received large numbers of citations in the academic development of force-field parameters from the SAFT-γ Equation of press. The team has expertise in both molecular modelling and State for use in course-grained molecular simulations. thermodynamics and process systems engineering. Their modelling work covers all scales from sub-atomic (quantum) to macroscopic. The Developing intermolecular-potential models for use with the group has a website (http://molecularsystemsengineering.com) SAFT-VR Mie equation of state where it is possible to access recent papers and results. A major advance in the statistical associating fluid theory for potentials of variable range (SAFT-VR) has recently been made with the MSE research is underpinned by a £1.8M Platform Grant (EPSRC) incorporation of the Mie (generalized Lennard–Jones [LJ]) interaction which supports the next generation of post-doctoral researchers between the segments comprising the molecules in the fluid (Lafitte et and has the support of BMS, Chemistry Innovation, GSK, P and G al. J. Chem. Phys. 2013;139:154504). The Mie potential offers and Syngenta. The programme is entitled ‘Molecular systems greater versatility in allowing one to describe the softness/hardness of Engineering of High-Value Structured and Formulated products’. the repulsive interactions and the range of the attractions, which The aim is to advance the tools of molecular systems engineering to govern fine details of the fluid-phase equilibria and thermodynamic tackle some of the key molecular challenges to improving the derivative properties of the system. In our current work, the SAFT-VR productivity of drug discovery and processing by improving our Mie equation of state is employed to develop models for a number of predictive capability of the relevant physical properties. prototypical fluids, including some of direct relevance to the oil and gas industry: methane, carbon dioxide and other light gases, alkanes, MSE collaborates with industry across a broad range of sectors alkyl benzenes, and perfluorinated compounds. A complication with from pharmaceuticals to oil and gas. The following highlights some the use of more-generic force fields such as the Mie potential is the of our recent publications and progress. additional number of parameters that have to be considered to specify the interactions between the model molecules, leading to a SAFT developments degree of degeneracy in the parameter space. A formal methodology to isolate intermolecular-potential models and assess the adequacy of the description of the thermodynamic properties in terms of the complex parameter space is developed. Fluid-phase equilibrium properties (vapour pressure and saturated-liquid density) are chosen as the target properties in the refinement of the force fields; the predictive capability for other properties such as the enthalpy of vaporization, single-phase density, speed of sound, isobaric heat capacity, and Joule–Thomson coefficient, is appraised. It is found that an overall improvement of the representations of the thermophysical properties of the fluids is obtained using the more-generic Mie form of interaction; in all but the simplest of fluids, one finds that the LJ interaction is not the most appropriate. An update of our work in this area is found in Dufal et al. AIChE J 61 2891 (2015) and Sadeqzadeh et al., Fluid Phase Equilib. 407, 39 (2016).
Figure 1: Statistical associated fluid theory (SAFT) is fundamental to the group’s work. 31
Force-Field Parameters from the SAFT-Equation of State for The separation of carbon dioxide from gas streams is of significant Use in Coarse-Grained Molecular Simulations importance in many energy development schemes. Further information A description of fluid systems with molecular-based algebraic is included in the Energy Systems Engineering section of this report. equations of state (EoSs) and by direct molecular simulation is common practice in chemical engineering and the physical – Pharma – partitioning of APIs between solvents sciences, but the two approaches are rarely closely coupled. The Many APIs have low solubility in both water and other solvents and key for an integrated representation is through a well-defined force it is also difficult to predict partitioning between two solvents. field and Hamiltonian at the molecular level. In developing coarse- grained intermolecular potential functions for the fluid state, one Good progress has been made at modelling some of these typically starts with a detailed, bottom-up quantum-mechanical or systems. The figure shows the actual and the calculated solubility of atomic-level description and then integrates out the unwanted ibuprofen and ketoprofen in water and acetone and shows that the degrees of freedom using a variety of techniques; an iterative models can achieve good agreement with measured values. heuristic simulation procedure is then used to refine the parameters of the model. By contrast, with a top-down technique, one can use an accurate EoS to link the macroscopic properties of the fluid and the force-field parameters. We discuss the latest developments in a top-down representation of fluids, with a particular focus on a group-contribution formulation of the statistical associating fluid theory (SAFT-γ). The accurate SAFT-γ EoS is used to estimate the parameters of the Mie force field, which can then be used with confidence in direct molecular simulations to obtain thermodynamic, structural, interfacial, and dynamical properties that are otherwise inaccessible from the EoS. This year we have advanced in this area, presenting coarse grained (CG) for water (Lobanova et al., Molecular Physics 113, 1228 (2015)); natural gases and condensates Herdes et al., Fluid Phase Equilibria 406, 91 (2015); suprespreading surfactants (Theodorakis et al., Soft Matter 11, 9254 (2015).
Figure 2: Solvent design for seperations and reactions Applications – Solvent design for separation When looking at systems where there are large numbers of potential The group has carried out a series of studies on, in particular, the solvents and extremely large numbers of potential solvent mixtures, separation of carbon dioxide from methane. computing time becomes a key factor for modelling. This can be managed by developing generic mathematical formulations of the A Hierarchical Method to Integrated Solvent and Process mixture design challenge and then investigating the most effective Design of Physical CO2 Absorption Using the SAFT-γ solution strategies. Systems that have been studied include Mie Approach mixtures of solvents to maximise ibuprofen solubility and mixtures of Molecular-level decisions are increasingly recognized as an integral solvents that give best performance for the extraction of acetic acid part of process design. Finding the optimal process performance from water. requires the integrated optimization of process and solvent chemical structure, leading to a challenging mixed-integer nonlinear Similar issues occur when looking at how solvent selection can be programming (MINLP) problem. The formulation of such problems used to maximise the reaction rate constant. To optimise it is when using a group-contribution version of the statistical essential to be able to consider a wide range of solvents (through associating fluid theory, SAFT-γ Mie, to predict the physical Computer Aided design techniques), be able to make reliable properties of the relevant mixtures reliably over process conditions is predictions of kinetics using Quantum mechanics and, finally, challenging. To solve the challenging MINLP, a novel hierarchical integrate within process design by use of Mixed Integer Nonlinear methodology for integrated process and solvent design (hierarchical Programming. optimization) is presented. Reduced models of the process units are developed and used to generate a set of initial guesses for the In an example case it was possible to increase the rate constant by MINLP solution. The methodology is applied to the design of a 126% for the Menshutkin reaction of phenacyl bromide and pyridine physical absorption process to separate carbon dioxide from and to verify this result experimentally. methane, using a broad selection of ethers as the molecular design space. The solvents with best process performance are found to be poly(oxymethylene)dimethylethers. A review of the results is presented in J. Bruger et al. AIChE J6,1 3249 (2015). 32
Application Domain Biological Systems Engineering
Biological Systems Engineering at CPSE is concerned with the host cell contaminants is a poorly understood process that largely elucidation and control of biological systems at multiple scales depends on process conditions and cell health. The group is ranging from the molecular to the cellular to the tissue to the organ currently focused on developing a mechanistic understanding of the level and beyond. A range of approaches is developed and contaminants content with respect to process conditions and linking deployed for this purpose including different kinds of mathematical this knowledge to the efficiency of the primary purification step, modelling, analysis, design, optimization and control, and affinity chromatography. Overall this work involves mechanistic experiments and their integration. The applications of this work span mathematical modelling of the relevant cellular biochemical steps biomedical engineering, biotechnology and systems and synthetic and their effect at the process level, with associated tools of analysis biology. Snapshots of the work in biological systems engineering are and design. presented below, revealing multiple facets of the work in this area. Professor Bogle along with colleagues at the UCL Institute for Liver Dr Misener, Professor Mantalaris, Professor Pistikopoulos and and Digestive Health have used process systems engineering collaborators have developed a novel 3-D biomimetic bioreactor for approaches and tools to tackle medical problems which involve growing red blood cells ex vivo. The bioreactor recapitulates complex chemical transformations and spatial phenomena looking in architectural and functional properties of erythrocyte formation, particular at the liver system, the body’s chemical factory. This reducing the need for expensive growth factors by an order of involves modelling distributed behaviour necessary to predict the magnitude. Building on this, ongoing work involves developing a behaviour of drugs for treating liver disease. The model developed global superstructure optimization for improved bioreactor design. has been used to predict the effects of suppression of de novo Another project is motivated by the treatment protocols in Acute lipogenesis, stimulation b-oxidation and a combination of the two. Myeloid Leukaemia, which relies on cell cycle phase-specific chemotherepeutic drugs. A platform is developed combining In non-alcoholic fatty liver disease (NAFLD), lipid build-up and the experiments, modelling of the cell cycle, and modelling of cell resulting damage is known to occur more severely in perivenous populations using population balance models. This platform can be cells. Due to the complexity of studying individual regions of the the basis of improving chemotherapy planning through such cell sinusoid, the causes of this zone specificity and its implications on cycle phase-specific drugs, leading to optimizing drug dosages and treatment are largely ignored. A computational model of liver glucose timings in a systematic manner. Overall, these projects involve a and lipid metabolisms has been developed which treats the sinusoid combination of mechanistic mathematical modelling, in some cases as the repeating unit of the liver rather than the single hepatocyte. By at multiple levels, design and optimization. simulating insulin resistance (IR) and high intake diets leading to the development of steatosis in the model, the work identifies key Dr. Kontoravdi and co-workers are developing process models to differences between periportal and perivenous cells accounting for enable the implementation of Quality by Design in bioprocessing. higher susceptibility to perivenous steatosis. Secondly, variation Model development centres around two main themes: the between individuals is seen in both susceptibility to steatosis and in mechanisms involved in protein glycosylation and the release of host its development across the sinusoid. Sensitivity analysis was used to cell contaminants. Protein glycosylation is a type of non-template identify the processes which have the largest effect on both total modification that affects the efficacy, stability and immunogenicity of hepatic triglyceride levels and on the sinusoidal location of steatosis. therapeutic proteins. It is, in turn, affected by process conditions, cell Results confirm phenomena seen in vivo. Overall, this work involves metabolism and intracellular regulation events. The group is working multiscale and multilevel modelling, and systems engineering tools towards understanding these interactions and eventually providing a for their analysis. platform for glycosylation optimisation and control with a view to producing a narrow and targeted set of structures. In parallel, Dr. Work in Dr Krishnan’s group focuses on information processing in Kontoravdi is collaborating with Prof. Shah and colleagues in cells and tissues using a combination of mathematical modelling Chemistry and Life Sciences on the design and fabrication of a across a range of scales and levels, theoretical and systems analysis, synthetic enzymatic reactor that will perform protein glycosylation ex and collaboration with experimentalists. Recent work has focused on vivo in a fully controlled manner. In the second theme, the release of information processing in multisite phosphorylation, connecting the 33
enzymatic mechanism to the molecular information processing levels simultaneously, in a systematic manner in this context. Overall, behaviour. This in turn plays an important role in signalling networks, the projects described above involve a combination of mathematical where such enzymatic mechanisms are implicated. Another project models (temporal, spatial, stochastic) and tools from nonlinear in the area of mRNA translation combines experiments (in the group dynamical systems analysis, systems and control engineering and of Ian Stansfield) and modelling to develop a systems analysis for networks for analysis. connecting ribosomal recycle, feedback, nonsense mediated decay and mRNA stability. A complementary approach in this area has Taken together, the above research snapshots clearly demonstrate a been to develop new Probabilistic Boolean Network tools to facilitate number of features. Firstly, biological systems are complex in many analysis of these stochastic transport models. At the network level, ways and present a range of challenges at different scales. Secondly, recent work has focused on the effects of spatial regulation and systems engineering approaches are essential to tackle these compartmentalization in biochemical networks, an aspect of challenges, and further different kinds of systems engineering tools increasing importance in both systems and synthetic biology. are needed in different contexts. Thirdly, a combination of modelling, Another project examines the effect of dynamic environments on the experiments and the deployment of appropriate systems engineering progression of the cell cycle in budding yeast. Using a multiplicity of tools can prove to be very effective. Fourthly, new systems models, as well as different experimental data, a number of engineering approaches need to be developed in certain cases. underlying features of cell cycle progression in dynamically varying Finally, systems engineering provides vital input in the life sciences in environments has been demonstrated. A platform for connecting the areas ranging from basic biology, biomedical engineering, effects of the environment, the cell cycle and growth has also been biotechnology and synthetic biology. All these areas in turn provide created. Finally, at the cell and tissue levels the effects of different new impetus for systems engineering itself. modes of intrinsic and induced drug resistance mechanisms in tumours at the cellular and tissue levels has been studied. This work clearly demonstrates the need to account for both cellular and tissue 34
Application Domain Energy Systems Engineering
The importance of Energy Systems Engineering as an application optimisation of the process. Similar approaches are being applied to domain within CPSE has increased over the last few years. high-pressure amine solvent design for separation with membrane Concerns over the cost and integrity of supply, coupled with the contactors. The other main line of work involves addressing apparent inability to control greenhouse-gas emissions resulting climate-change mitigation issues: integrated solvent and process from the increased use of fossil fuels, has amplified the need to design of carbon dioxide capture from power station flue gas at low focus not only on a less carbon-intense supply but the efficiency of pressures. With a detailed SAFT description of the thermodynamics energy generation and use together with strategies for carbon of the reactive dissolution equilibria we can successfully model the mitigation. process by focusing on the mass transport with just a single transferable modulation of the diffusivity of carbon dioxide in the CPSE is engaged in a number of these areas of research including solvent. (Jackson, Adjiman, Galindo, Pantelides) Urban Energy Systems, Bioenergy Systems, Hydrogen Networks and Polygeneration, Energy Storage, Carbon Capture and Storage, Energy Storage and Network Systems. We are modelling integrated energy systems for off-grid mining operations to identify the trade-offs between reliability of energy Urban Energy Systems provision, due to the use of variable renewable energy generation Cities use up approximately three-quarters of the world’ s energy such as solar and wind, with the cost of large scale energy storage. and play a major role in issues such as economic security and The system model includes the variable and stochastic behaviour of climate change. Work continues in the area of Urban Energy renewable energy. Storage technologies include compressed air, Systems, building on the £4 million, 5-year collaborative project with molten salts and pump-hydraulic systems with energy efficiency and BP that investigated the technologies and systems used in cities to losses. The approach includes the use of case studies of large scale distribute and consume energy. Understanding these systems in mining operations with both heat and power demands in Chile and more detail can provide valuable insights into how to make the Canada. (Fraga) distribution and consumption of energy more cost effective and sustainable in cities in the future. State of the art Urban Energy Local Energy Systems Systems Model (URBEN) is a comprehensive optimisation tool that This area involves the design of neighbourhood-level energy enables urban planners, property developers and equipment systems, incorporating local distribution and sharing of both heat manufacturers to determine the optimum mix of technologies in and power amongst dwellings. Local energy generation includes order to meet policy goals and cost constraints for both retrofit and combined heat and power units, such as fuel cells using grid new urban build projects.Research continues on new approaches to supplied gas, solar thermal, solar photo-voltaic and wind turbines. designing our urban energy infrastructure so that it is more efficient Energy storage in the form of hot water tanks is included. A key and has less impact on the environment. (Shah, Kierstead) consideration is the regulatory framework to support energy integrated at this neighbourhood scale and the impact of such Molecular Energy Systems regulations on the systems design. (Fraga) Energy is a key area in which Molecular Systems Engineering approaches have been developed and applied to key problems. The Nuclear Reprocessing general approach is to develop molecular equations of state for Recently research has started on looking at the design of nuclear phase behaviour and thermodynamic properties and integrate these reprocessing using intensified operations. Traditional technologies into process system design and optimisation approaches, using for for separation are mixer-settlers; we are looking at micro-channels instance gPROMS, for combined fluids/materials and process for intensified operations to reduce the volume of solvents required design. A good recent example of this involves an integrated and improve the separation performance. (Fraga) molecular and process design of separation of carbon dioxide from natural gas (methane) for well-head applications.Here we have used our group contribution SAFT-γ Mie approach to design new solvents for CO2/methane separation using a unified process/solvent 35
Multiscale Modelling of Integrated Energy Systems The activity is a close collaboration between the Departments of There is a strong CPSE engagement (Mac Dowell, Shah, Maitland) Chemical Engineering and Earth Science and Engineering and within the CleanFAB (Clean Fossil and Bioenergy) Group, an involves the close interplay of experimental and theoretical/ interdisciplinary team of researchers studying how fossil fuels and numerical modelling research. Molecular Systems Engineering and bioenergy, in conjunction with CCS, will be key to enabling our Multiscale Modelling within CPSE are a key part of this activity and stable, cost-effective transition to a low-carbon energy system. the programme has enabled a unique partnership of modelling and From engineering to economics, we are determined to make this experimental work, the one driving the other in terms of new insights adaptation as successful as possible. The work focuses on the and improved predictive capability. multi-scale modelling of clean fossil and bioenergy as part of the diverse energy system of the 21st century. An example of the work The experimental work involves characterisation of the rocks, the we are carrying out in this space is the MESMERISE-CCS project properties of reservoir fluids mixed with supercritical CO2 and the wherein we are integrating energy system, electricity market, multiphase flow of such fluids in the porous and fractured carbonate
CCS-power plant, CO2 transport and CO2 storage models. This rocks. Imaging using X-ray micro-tomography and modified work is driven by the view that the role that thermal power plants will body-scanners plays a major role in this. The modelling work play in the energy system going forward will be distinct to that which comprises prediction of the thermophysical properties (phase they played historically. In particular, the concept of baseload or behaviour, interfacial properties, transport properties) of the fluids indeed mid-merit power plants will be a thing of the past– in order involved under high temperature-pressure reservoir conditions. to be successful, thermal power plants will need to operate in a Molecular Systems Engineering plays a major role here, and new much more flexible fashion than in the 20th century. The objective of developments of the SAFT approaches, are transforming our ability this work is therefore to understand how flexible the CCS chain to predict accurately the way complex fluid mixtures behave under needs to be, to identify the flexibility-limiting links in the CCS chain such extreme conditions. These models feed into simulations of and to gain insight into the value of re-engineering these systems to multiphase fluid flow in the storage rocks on a wide range of provide enhanced flexibility to the energy system, thus enabling the length-scales, from the pore scale (pore network models and Lattice integration of increased quantities of renewable power, hastening Boltzmann) through core and metre block scales up to the kilometre our transition to a low-carbon energy system. (Mac Dowell) distances of CO2 plume development at the reservoir scale. Once robust reservoir models are developed, the challenge will be to use Carbon Storage systems engineering approaches to aid in the design, optimisation, The Qatar Carbonates and Carbon Storage Research Centre monitoring and control of these complex operations. (Maitland, (QCCSRC) is a 10 year, $70m research programme funded by Qatar Jackson, Galindo) Petroleum, Shell and Qatar Science and Technology Park. It is the largest industry-funded research programme at Imperial and aims to provide the underpinning science and engineering to enable the optimised design and operation of large-scale carbon dioxide storage operations in carbonate reservoirs typically found in Qatar and other parts of the Middle East. 36
Application Domain Environmental Systems Engineering
The application of system engineering techniques to environmental sludge treatment), owned and operated by Sydney Water (Australia), problems is relatively nascent within CPSE, but is a rapidly emerging were investigated. Plant-wide dynamic models were assembled and area. The dynamics of the interactions, in both length- and time- calibrated using historical data for both plants, paying special attention scales, between human-natural systems are complex and nuanced, to closing the solids balances in the main treatment/separation units. often involving multiple stakeholder groups. Thus the tools and A scenario-based optimization approach was used in an objective to techniques developed within CPSE are ideally poised to make a determine the best possible performance with respect to a variety of sizable contribution to this emerging area, in the context of process economic and environment sustainability metrics. In turn, these results and systems optimisation and also in the provision of decision could feed into decisions revolving around treatment-plant operation support tools to the industrial and policy-making communities. and asset management as well as inform the next major plant license review. An inherent advantage of this methodology is that it can be Plant-wide Optimization of Full-Scale Wastewater used for analysing other ‘what-if’ scenarios or for assessing the Treatment Plants performance of other WWTPs. Improving operational and process control strategies has become key for the sewage industry to reduce their energy consumption without compromising effluent quality. These strategies may be particularly useful for energy-intensive processes such as activated sludge aeration, which can account for 45-75% of a plant’s energy expenditure. Overall, it is estimated that energy consumption of most wastewater treatment plants (WWTPs) may be reduced by 10-40% this way. Nevertheless, WWTPs are comprised of a large number of treatment and separation units, which involve a great variety of processes acting on different time scales and interacting with each other via recycling loops. Failure to account for these interactions, e.g., by optimizing in a unit-wise manner, may not lead to the largest possible improvements and could even be detrimental from a plant-wide standpoint.
The group of Dr Chachuat is working on the development and application of a model-based methodology in order to provide a better understanding of the impacts of changing effluent quality targets on Figure 1: Comparison of various strategies for an optimal interplay plant-wide energy use and fugitive emissions. Two industrial case between plantwide power consumption and NO3 emissions in the studies corresponding to existing activated sludge plants (including treated effluent
Figure 2 37
Figure 3 (right and left plots): Velocity field in raceway pond (left plot) and simulated microalgae production over several weeks (right plot)
Multi-Scale Modeling of Microalgae Culture for Optimization Water and Energy Systems in Sustainable City Development and Control – Resilience.IO platform Andreas Nikolaou, Benoît Chachuat The grand challenges facing human societies are closely Microalgae have long been identified as a promising candidate for interconnected with the sustainable provisioning of energy, water biofuel production. These microorganisms have fast growth rates and and material resources, for growing and developing populations, a rich protein content, in addition to being able to produce and and the subsequent processing and management of waste and accumulate lipids under certain stress conditions. They are pollution. Current urban water and energy systems are expanding considered by many to be a viable alternative to conventional oil increasing attention paid to their economic and environmental crops due to a higher biomass productivity and independence impacts. However, there is a lack of a sufficiently systematic towards arable land and fresh water. Moreover, the downstream approach to address these impacts and evaluate optimal strategies, processing of microalgae in biorefineries opens the perspective for either in the context of research or real-world decision making. producing a wide spectrum of valuable products in addition to biofuel, including cosmetics, pharmaceuticals and nutraceuticals, while The group of Professor Nilay Shah took advantage of their strength treating nutrient-rich effluents from wastewater treatment works or in urban energy and transportation systems to expand the study to
CO2 from power-plant flue gas, all in the same process. Despite these water, sanitation, and hygiene sector (WASH). The current regional promises, mass production of microalgae for large-scale biofuel demographics, land-use, infrastructure and economic information is production is yet to be demonstrated, especially in regards of their used as input for the initial state of the focused urban system high nutrient requirements, the trade-off between biomass growth incorporating energy, water and other related resources. and lipid productivity, and the lipid extraction challenges. Detailed spatio-temporal demand data, obtained by simulating a The group of Dr Chachuat is working on the development of synthetic population using agent-based models, is further used to mathematical models capable of capturing the processes governing plan capacity utilization and expansion by supply-side matching on light-limited growth in microalgae. Particularly important in outdoor a cost optimal basis, eventually aiming to explore the optimal design culture systems, where the light irradiance vary greatly, are the and operational strategies for residential, commercial, industrial, and mechanisms of photoinhibition and photoacclimation, which act on other sectors. Moreover, long-term socio-economic scenarios are a wide range of time-scales (from seconds to days). addressed in the urban system development through a real-time Our recent focus is on integrating microalgae growth models at the feedback loop. cell level with CFD and light attenuation models describing the mixing conditions and the vertical light distribution in raceway ponds The team developed a prototype based on the Greater Accra and other cultivation systems. These models provide a way of Metropolitan Area (GAMA) city-region in Ghana, as part of the assessing various scale-up effects and how certain key parameters Department for International Development (DfID) funded Future may affect microalgae productivity. The ultimate goal is to provide Cities Africa (FCA) project. The outputs depict an overall resource reliable predictions in large-scale production systems, as a means landscape of the studied urban area, but also provide the material for optimizing their design and operation. This work is a and energy balance of supply and demand from both macro and collaboration with the University of Padova (Prof. Bezzo, Prof. micro perspectives, which is used to propose environmentally Morosinotto) and BIOCORE-INRIA (Dr. Bernard). friendly and cost effective sustainable city-development strategies. This work is to become a core component of the Resilience.io platform as an open-source, data-driven, integrated systematic tool gathering social, environmental and economic data to inform urban planning, investment and policy-making for city-regions globally. 38
changes in the load [2]. In order to implement the MPC control strategy, the detail dynamic model of the capture unit was approximated by a state-space model of five inputs and five outputs. A key advantage of the MPC control scheme is that it uses an optimisation framework which makes use of explicit process models to predict the future behaviour of the plant. The results demonstrated that the MPC control strategy can compensate for disturbances. Moreover, the work also studied flexibility scenarios involving changes to the set point for the carbon capture rate thus allowing an economic trade-off between use of steam (and the consequent increase in use of natural gas) versus decreased
capture rate which could incur penalties for CO2 emissions. The work was funded by EPSRC through grant EP/J020788/1 Gas- FACTS: Gas – Future Advanced Capture Technology Options.
Understanding Methane and Carbon Dioxide Emissions from the Natural Gas Supply Chain When you compare natural gas to other fossil fuels such as coal, its combustion generates approximately half as much carbon
dioxide (CO2) emissions. However, natural gas is also mainly composed of methane, which is itself a strong greenhouse gas, and is emitted at different stages along the natural-gas supply chain. While methane dissipates from the atmosphere more quickly than
CO2, it is considered to have a higher global warming potential and therefore a more potent short-term effect on climate change than carbon dioxide.
The big question is: do these methane emissions along the supply chain undermine natural gas’s lower carbon credentials? Over the last five years, a large number of studies have estimated how much methane is emitted through the whole natural-gas supply chain from exploring, extracting, producing, processing and transporting natural gas. These studies have used a variety of Figure 4: Example of simulated wastewater flow in GAMA (top plot) methods to understand the issue, but so far have differed and optimized investment strategies for water and wastewater significantly in their findings. technologies (bottom plot)
Professor Nigel Brandon and Dr Adam Hawkes and colleagues at Model Predictive Control of Post-Combustion CO2 Capture the Sustainable Gas Institute (SGI) have undertaken a Process integrated with a power plant comprehensive review of all the available global data on both CO2 The process of CO2 capture and storage is a potential way to and methane emissions from the natural-gas supply chain to fully control the emissions of CO2 from large-scale power plants. A understand the scale of the issue. This briefing note summarises the favoured CCS (Carbon Capture and Storage) strategy is the main findings and recommendations of the Institute’ s first White post-combustion CO2 capture process using MEA. However, in a Paper. By systematically assessing the literature in terms of gas-fired power station, the power plant has to respond to transparency, relevance and accuracy, the paper assembles and dispatching signals from the transmission operator in order to analyses the current state of our knowledge on emissions globally. provide load balancing. Frequent changes in operating point create significant disturbances to the CO2 capture plant. Therefore, the Key Questions integration of the CO2 capture process and gas-fired power plants • How much methane and CO2 is emitted from the natural will increase the need to design advanced model-based control gas supply chain? systems to overcome the process interactions and maintain • What methods are being used to estimate these emissions? dynamic operability of power plant and CCS unit. The dynamic • What factors affect emission ranges? behaviour of the capture plant was implemented in gCCS [1], a tool • Why do we see such a big range? developed within gPROMS for the modelling of the capture plant units. In order to show how the proposed control scheme responds to a real operation during a day, fluctuation of the flue gas flowrate was implemented in the model. A Model Predictive Control (MPC) strategy was implemented in Matlab in order to maintain the dynamic operability of the CO2 capture plant in the presence of 39
This review analysed over 250 studies and reports. These studies 4. Some of the emissions estimates are considerable, but covered natural gas from both conventional wells and there is potential to reduce these emissions. unconventional wells at every stage in the supply chain, as well as • If modern equipment with appropriate operation and examining the liquefied natural gas (LNG) process. maintenance regimes were to be used, the total supply chain
emissions should lie within the range of 19–212 gCO2 eq/kWh
with a central estimate of 92 gCO2 eq/kWh. If the natural gas was used in a power plant, these supply chain emissions would contribute between 4%–35% of the total greenhouse gas emissions per kWh of electricity generation. • Methane emissions are expected to be 0.3%–2.4% of total produced methane, with a central estimate of 1.4%. • Further reductions could be made, particularly for emissions from transport, storage and distribution, and also at the point when gas is extracted.
5. A wide variety of techniques are used to monitor emissions which means supply chain emissions estimates vary greatly in the literature. • Many studies apply a top-down approach to measuring methane emissions which involves measuring or inferring the concentration of methane in the atmosphere within a region, and then attributing emissions to specific sources within that KEY FINDINGS: region. A more thorough approach would involve a bottom-up 1. The range of estimated emissions across the supply chain point measurement at specific places on the ground in is vast. combination with local leak detection.
• Combined methane and CO2 emissions from the supply chain • Methodological assumptions vary significantly across the
are between 14 and 302 gCO2eq/kWh literature and have a major effect on the estimated emissions • A small number of studies estimate exceptionally high emissions (e.g., total production volume of a well and the assumed from specific supply chain stages or facilities. However, the methane content of the extracted natural gas). average estimates lie towards the lower end (see Figure 5). • Methane emissions are estimated to be between 0.2% and 6. There is a significant lack of data, particularly for regions 10% of total produced methane. other than the US. • More data are required globally for offshore extraction, coal-bed 2. Key emissions sources are during well completions, liquids methane extraction, liquids unloading, well completions with unloading, and the use of pneumatic devices and RECs, transmission and distribution pipelines, and methane compressors. emission measurement from all LNG stages. • Studies show that the use of Reduced Emission Completions (RECs) equipment can significantly reduce methane emissions 7. Further research is needed to determine the potential role by over 75%. This technique is now compulsory in the United of natural gas in a low-carbon energy mix. States. • Research exploring the technological, operational or regulatory • Emissions from both unconventional and conventional wells are mechanisms is required to achieve emission reductions. comparable as long as methane is captured rather than flared • Further studies are also necessary to quantify the potential during well completion. reduction in supply-chain emissions and to examine factors • Gas venting and leakage from compressors and pneumatic affecting different supply-chain emissions in order to understand devices across the supply chain contribute significantly to the mitigation potential at each stage and also to look at the emissions. impact of regional regulation (e.g., regulation for continuous • More research is needed to quantify the factors affecting the monitoring of ‘super-emitting’ facilities). emissions from the liquids unloading process. References 3. There is evidence of ‘super emitter’ facilities all along the [1] Process Systems Enterprise, 2015, gCCS – supply chain. overview: whole chain CCS systems modelling, on-line February • A small number of high-emitting facilities strongly impact the 2016, http://www.psenterprise.com/power/ccs/gccs.html emissions profile at every stage in the production process. [2] Mehleri ED, Mac Dowell N, Thornhill NF, 2015, Model predictive
• These may be a result of the use of ineffective process control of post-combustion CO2 capture process integrated with a equipment and poor operational and maintenance strategies, power plant, 12th International Symposium on Process and could be eliminated and reduced if the best available Systems Engineering (PSE) / 25th European Symposium on techniques were applied. Computer Aided Process Engineering (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: 161-166 40
Application Domain Supply Chains of the Future
Supply chains of the future will have to deal with a host of Case study and results new challenges facing us in the 21st century, including: A case study explored the allocation of production of multiple • Exploiting new energy and material sources products to seven plants around the world, and their subsequent • Cleaner exploitation of existing sources distribution to markets, using the supply chain structure as below: (e.g. high-carbon fossil fuels) • Resource efficiency to deal with increasing scarcity of non-fuel Raw material Production Customer resources (e.g. water and minerals) suppliers plants locations • Decarbonised supply chains • Customisation of products and services (e.g. healthcare) closer to the point of use.
A key feature of supply-chain optimisation is the need to include multiple objective functions when considering the design or operation of a supply chain. These may reflect for example economics, sustainability and responsiveness metrics. An example of an industrial case study which employs multi-objective optimisation is discussed below.
Incorporating sustainability measures in supply chains A trade-off curve between the three objectives was developed by Sustainability plays a key role in the management of a successful the use of classical multi-objective optimisation procedures. The and responsible business. When trying to improve the sustainability overall trade-offs between the objectives can be seen below: performance of a business, there are three major challenges that 78 Tota l Lead Time need to be addressed. First, assessment of sustainability requires TLT ≤ 1098 76 consideration of not just economic, but also environmental and TLT ≤ 1106 social impacts. Second, we need to find appropriate sustainability TLT ≤ 1113
on 74 TLT ≤ 1120 indicators and gather the necessary data in order to quantify si is TLT ≤ 1128 72 sustainability performance. Finally, sustainability has to be seen in Em TLT ≤ 1165 the context of the whole system, i.e., it has to include all activities 70 TLT ≤ 1202 GHG along the supply chain. In this work, we consider all three aspects l TLT ≤ 1239 ta 68 TLT ≤ 1276 and propose a multi-objective optimisation framework for the To TLT ≤ 1312 optimisation of a sustainable supply chain. 66 TLT ≤ 1349 TLT ≤ 1386 64 TLT ≤ 1421 Three sustainability indicators have been considered, namely the 66 68 70 72 74 76 total cost (reflecting economics), GHG emissions (reflecting Total Cost sustainability) and lead time (reflecting responsiveness). We apply this framework to an industrial test case using real-world data It can be seen that GHG emissions can be reduced considerably drawn from an industrial collaborator. The results show clear without a significant cost increase initially, but then they are very trade-offs between the three different objectives. However, we can hard to reduce. Shorter lead times can only be achieved by also observe that typically a considerable decrease in GHG compromising both emissions and cost. emissions or lead time can already be achieved with only a relatively small increase in cost. The proposed framework enables us to determine such trade-off relations and consequently make decisions that improve the sustainability performance of the supply chain. 41
Academic Profiles Professor Berc Rustem
“CPSE academics are expected to span several disciplines including systems modelling, optimisation and control and computing.” 42
Academic Profiles
Process synthesis and development for fine chemicals, pharmaceutical and biochemical processes: • Combination of chemistry with modelling and engineering to improve process designs and to speed up process development. • Performing rapid economic assessments for different manufacturing routes. • Developing long-term capacity and investment plans.
Safety in design and operation, especially the application of formal mathematical techniques to assess and improve process safety
Other Activities Co-founder of Process Systems Enterprise Ltd Nilay Shah FREng EPSRC college member EPSRC Manufacturing Strategy Advisory Team Professor of Process Systems Engineering, BBSRC Industrial Biotechnology and Bioenergy Strategic Advisory Director CPSE, Department of Chemical Engineering, Team Imperial College London IChemE Transactions editorial board member Director, Imperial College Manufacturing Futures Lab Qualifications MEng in Chemical Engineering (Imperial College London) Reviewer for PhD in Chemical Engineering (Imperial College London) AIChE Journal Chemical Engineering Research and Design Awards and Distinctions Computers and Chemical Engineering Fellow of the Royal Academy of Engineering Chemical Engineering Science Fellow of the IChemE A-Star Research Council (Singapore) RAEng MacRobert Award and Prize (2007) Science Foundation Ireland RSC/SCI/IOM Beilby Medal (2005) ICI/RAEng Fellowship (1997-2002) Academic Collaborations Imperial College Faculty of Engineering Teaching Award (2009) University College London, Department of Chemical Engineering IChemE Hutchison Medal (2012) Newcastle and Strathclyde Universities, CPACT National University of Singapore Research Interests Delft University of Technology Design and analysis of energy and process systems: Rothamsted Research • Bioenergy/Biorenewable systems and technologies. IBERS – University of Aberystwyth • Urban Energy Systems. University of York • Modelling and optimisation of low-carbon technologies and Aston University systems (e.g., CCS, hydrogen infrastructure etc). Newcastle University Cardiff University Supply-chain design and optimisation: • Development of new algorithms for large-scale supply-chain models. • Application to sector-specific processes (e.g., pharmaceuticals, oil and gas, consumer goods) 43
Industrial Collaborations 10. Sharifzadeh M, Wang L, Shah N, 2015, Integrated
Shell (Energy Efficient Refining) biorefineries: CO2 utilization for maximum biomass conversion, Syngenta (Supply Chain Optimisation) RENEWABLE & SUSTAINABLE ENERGY REVIEWS, Vol: 47, Sainsbury’s (Store of the Future) Pages: 151-161, ISSN: 1364-0321 Unilever (Sustainable Supply Chains Design) 11. Sharifzadeh M, Wang L, Shah N, 2015, Decarbonisation of Energy Technologies Institute (Bioenergy Value Chains) olefin processes using biomass pyrolysis oil, APPLIED Biosep (Biomass Fractionation) ENERGY, Vol: 149, Pages: 404-414, ISSN: 0306-2619 Petronas (Novel Gas Separation Technologies) 12. Akgul O, Mac Dowell N, Papageorgiou LG, Shah N, 2014, A mixed integer nonlinear programming (MINLP) supply chain Publications optimisation framework for carbon negative electricity Journal Articles (A * indicates open-access publication) generation using biomass to energy with CCS (BECCS) in the 1. Voll P, Jennings M, Hennen M, Shah N, Bardow A, 2014, The UK, INTERNATIONAL JOURNAL OF GREENHOUSE GAS Good, the Bad, and Your Real Choices – Decision Support for CONTROL, Vol: 28, Pages: 189-202, ISSN: 1750-5836 Energy Systems Synthesis through Near-Optimal Solutions 13. Boot-Handford ME, Abanades JC, Anthony EJ, Blunt MJ, Analysis, Computer Aided Chemical Engineering, Vol: 33, Brandani S, Mac Dowell N,Fernandez JR, Ferrari M-C, Gross Pages: 25-30, ISSN: 1570-7946 R, Hallett JP, Haszeldine RS, Heptonstall P, Lyngfelt A, 2. Guo M, Richter GM, Holland RA, Eigenbrod F, Taylor G, Shah Makuch Z, Mangano E, Porter RTJ, Pourkashanian M, N, Implementing Land-use and Ecosystem Service Effects into Rochelle GT, Shah N, Yao JG, Fennell PS, 2014, Carbon An Integrated Bioenergy Value Chain Optimisation Framework, capture and storage update, ENERGY & ENVIRONMENTAL Computers and Chemical Engineering, ISSN: 1873-4375 SCIENCE, Vol: 7, Pages: 130-189, ISSN: 1754-5692 3. Al-Ansari T, Korre A, Nie Z, Shah N, 2015, Development of a 14. Jennings M, Fisk D, Shah N, 2014, Modelling and optimization life cycle assessment tool for the assessment of food of retrofitting residential energy systems at the urban scale, production systems within the energy, water and food nexus, ENERGY, Vol: 64, Pages: 220-233, ISSN: 0360-5442 Sustainable Production and Consumption, Vol: 2, Pages: 15. Jennings MG, Shah N, 2014, Workforce planning and 52-66 technology installation optimisation for utilities, COMPUTERS 4. Stockford C, Brandon N, Irvine J, Mays T, Metcalfe I, Book D, & INDUSTRIAL ENGINEERING, Vol: 67, Pages: 72-81, ISSN: Ekins P, Kucernak A, Molkov V, Steinberger-Wilckens R, Shah 0360-8352 N, Dodds P, Dueso C, Samsatli S, Thompson C, 2015, H2FC 16. Khor CS, Chachuat B, Shah N, 2014, Fixed-flowrate total SUPERGEN: An overview of the Hydrogen and Fuel Cell water network synthesis under uncertainty with risk research across the UK, International Journal of Hydrogen management, JOURNAL OF CLEANER PRODUCTION, Vol: Energy, Vol: 40, Pages: 5534-5543, ISSN: 0360-3199 77, Pages: 79-93, ISSN: 0959-6526 5. Niu H, Leak D, Shah N, Kontoravdi C, 2015, Metabolic 17. Khor CS, Chachuat B, Shah N, 2014, Optimization of Water characterization and modeling offermentation process ofan Network Synthesis for Single-Site and Continuous Processes: engineered Geobacillus thermoglucosidasius strain for Milestones, Challenges, and Future Directions, INDUSTRIAL & bioethanol production with gas stripping, CHEMICAL ENGINEERING CHEMISTRY RESEARCH, Vol: 53, Pages: ENGINEERING SCIENCE, Vol: 122, Pages: 138-149, ISSN: 10257-10275, ISSN: 0888-5885 0009-2509 18. Mac Dowell N, Shah N, 2014, Dynamic modelling and analysis 6. Ortiz-Gutierrez RA, Giarola S, Shah N, Bezzo F, 2015, An of a coal-fired power plant integrated with a novel split-flow
approach to optimize multi-enterprise biofuel supply chains configuration post-combustion CO2 capture process, including Nash equilibrium models, 12TH INTERNATIONAL INTERNATIONAL JOURNAL OF GREENHOUSE GAS SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING AND CONTROL, Vol: 27, Pages: 103-119, ISSN: 1750-5836 25th EUROPEAN SYMPOSIUM ON COMPUTER AIDED Pantaleo A, Candelise C, Bauen A, Shah N, 2014, ESCO PROCESS ENGINEERING, PT C, Vol: 37, Pages: 2255-2260, business models for biomass heating and CHP: Profitability of ISSN: 1570-7946 ESCO operations in Italy and key factors assessment, 7. Samsatli S, Samsatli NIJ, Shah N, 2015, BVCM: A RENEWABLE & SUSTAINABLE ENERGY REVIEWS, Vol: 30, comprehensive and flexible toolkit for whole system biomass Pages: 237-253, ISSN: 1364-0321 value chain analysis and optimisation – Mathematical 19. Pantaleo AM, Camporeale S, Shah N, 2014, Natural gas- formulation, APPLIED ENERGY, Vol: 147, Pages: 131-160, biomass dual fuelled microturbines: Comparison of operating ISSN: 0306-2619 strategies in the Italian residential sector, APPLIED THERMAL 8. Sharifzadeh M, Richard CJ, Liu K, Hellgardt K, Chadwick D, ENGINEERING, Vol: 71, Pages: 686-696, ISSN: 1359-4311 Shah N, 2015, An integrated process for biomass pyrolysis oil 20. Pantaleo AM, Giarola S, Bauen A, Shah N, 2014, Integration upgrading: A synergistic approach, BIOMASS & BIOENERGY, of biomass into urban energy systems for heat and power. Vol: 76, Pages: 108-117, ISSN: 0961-9534 Part I:An MILP based spatial optimization methodology,
9. Sharifzadeh M, Shah N, 2015, Comparative studies of CO2 ENERGY CONVERSION AND MANAGEMENT, Vol: 83, Pages: capture solvents for gas-fired power plants: Integrated 347-361, ISSN: 0196-8904 modelling and pilot plant assessments, INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL, Vol: 43, Pages: 124-132, ISSN: 1750-5836 44
21. Pantaleo AM, Giarola S, Bauen A, Shah N, 2014, Integration of biomass into urban energy systems for heat and power. Part II: Sensitivity assessment of main techno-economic factors, ENERGY CONVERSION AND MANAGEMENT, Vol: 83, Pages: 362-376, ISSN: 0196-8904 22. Todri E, Amenaghawon AN, del Val IJ, Leak DJ, Kontoravdi C, Kucherenko S, Shah N, 2014, Global sensitivity analysis and meta-modeling of an ethanol production process, CHEMICAL ENGINEERING SCIENCE, Vol: 114, Pages: 114-127, ISSN: 0009-2509 23. Zhang Q, Shah N, Wassick J, Helling R, van Egerschot P, 2014, Sustainable supply chain optimisation: An industrial case study, COMPUTERS & INDUSTRIAL ENGINEERING, Vol: 74, Pages: 68-83, ISSN: 0360-8352 Claire S. Adjiman FREng
Conference Papers Professor of Chemical Engineering, Department of Chemical 1. Bustos-Turu G, Van Dam KH, Acha S, Shah N 2015, Engineering, Imperial College London Estimating plug-in electric vehicle demand flexibility through an agent-based simulation mode Qualifications 2. lSamsatli S, Samsatli NJ, Shah N, Optimal design of a future MEng in Chemical Engineering, Imperial College London hydrogen supply chain using a multi-timescale and spatially- PhD in Chemical Engineering, Princeton University distributed model, Hydrogen & Fuel Cell SUPERGEN Researcher Conference 2014 Awards and Distinctions 3. Pantaleo AM, Ciliberti P, Camporeale S, Shah N, 2015, Fellow of the Royal Academy of Engineering Thermo-economic assessment of small scale biomass CHP: Fellow of the Institution of Chemical Engineers steam turbines vs ORC in different energy demand segments, Chartered Engineer 7th International Conference on Applied Energy (ICAE), EPSRC Leadership Fellowship, 2012-2017 Publisher: ELSEVIER SCIENCE BV, Pages: 1609-1617, ISSN: Henry E. Armstrong Memorial Lecture of the Society of Chemical 1876-6102 Industry, 2011 4. Brown S, Martynov S, Mahgerefteh H, Fairweather M, Woolley Philip Leverhulme Trust Prize for Engineering, 2009 RM, Wareing CJ, Falle SAEG, Rutters H,Niemi A, Zhang YC, Research Excellence Award for Molecular Systems Engineering Chen S, Besnebat J, Shah N, Mac Dowell N, Proust C, Farret team, Imperial College, 2009 R, Economou IG, Tsangaris DM, Boulougouris GC, Van Rector’s Excellence Award, Imperial College, 2007 Wittenberghe J, 2014, CO(2)QUEST: Techno-economic Royal Academy of Engineering ICI Fellowship, 1998-2003 assessment of CO2 quality effect on its storage and transport, Porter Ogden Jacobus Honorific Fellowship, Princeton University, 12th International Conference on Greenhouse Gas Control 1997 Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 2622-2629, ISSN: 1876-6102 Secondments 5. Elahi N, Shah N, Korre A, Durucan S., 2014, Multi-period least Process Systems Enterprise Ltd, September 2006-August 2007 cost optimisation model ofanintegrated carbon dioxide capture transportation and storage infrastructure in the UK, Research Interests 12th International Conference on Greenhouse Gas Control Systematic methodologies for integrated molecular and process Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, design for reactive processes: development of modelling and Pages: 2655-2662, ISSN: 1876-6102 optimisation tools and applications (e.g., solvent design for reactions 6. Korre A, Nie Z, Durucan S, Elahi N, Shah N, Ahmad S, or CO2 capture, risk management). Model-based assessment of Goldthorpe W, 2014, The effect of market and leasing design of energy-conversion systems including solid-oxide fuel cells. conditions on the techno-economic performance of complex th Development of property-prediction techniques integrating different CO2 transport and storage value chains, 12 International scales of modelling (from quantum mechanics to advanced Conference on Greenhouse Gas Control Technologies equations of state). Global analysis techniques, such as global (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: 7225- optimisation and safety analysis 7233, ISSN: 1876-6102 7. Mac Dowell N, Shah N, 2014, Optimisation of post- th Other Activities combustion CO2 capture for flexible operation, 12 Associate Editor, Chemical Engineering Science International Conference on Greenhouse Gas Control Associate Editor, Journal of Global Optimization Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Editorial Board, Fluid Phase Equilibria Pages: 1525-1535, ISSN: 1876-6102 AIChE: Technical area co-chair/chair for CAST10a, 2006-2008 IChemE: Committee Member, Computer-Aided 45
Process Engineering Group relevance to the oil and gas industry, Fluid Phase Equilibria, EPSRC: Member of Peer Review College ISSN: 0378-3812 Co-chair, Foundations of Molecular Modeling and Simulations 2015 7. Rhazaoui K, Cai Q, Kishimoto M, Tariq F, Somalu MR, Adjiman (FOMMS 2015), Oregon CS, Brandon NP, 2015, Towards the 3D Modelling of the Effective Conductivity of Solid Oxide Fuel Cell Electrodes – Reviewer for Validation against experimental measurements and prediction AIChE Journal, Chemical Engineering Research and Design, of electrochemical performance, ELECTROCHIMICA ACTA, Computers and Chemical Engineering, Molecular Physics, Journal Vol: 168, Pages: 139-147, ISSN: 0013-4686 of Power Sources, Energy & Fuels, Journal of Global Optimization, 8. Adjiman CS, Galindo A, Jackson G, 2014, Molecules Matter: Industrial and Engineering Chemistry Research, Fluid Phase The Expanding Envelope of Process Design, PROCEEDINGS Equilibria, Chemical Engineering Science, Computers and Chemical OF THE 8th INTERNATIONAL CONFERENCE ON Engineering, Imperial College Press, Mathematical Programming, FOUNDATIONS OF COMPUTER-AIDED PROCESS DESIGN, Optimization and Engineering. Vol: 34, Pages: 55-64, ISSN: 1570-7946 9. Cai Q, Adjiman CS, Brandon NP, 2014, Optimal control Academic Collaborations strategies for hydrogen production when coupling solid oxide Argonne National Laboratory, UCL, University of Manchester, electrolysers with intermittent renewable energies, JOURNAL University of Edinburgh, University of Cardiff, University of OF POWER SOURCES, Vol: 268, Pages: 212-224, ISSN: Paderborn, University of Pannonia, ETH Zürich, National Technical 0378-7753 University of Athens, Centre for Research and Technology-Hellas, 10. Dufal S, Papaioannou V, Sadeqzadeh M, Pogiatzis T, Chremos University of Notre-Dame. A, Adjiman CS, Jackson G, Galindo A, 2014, Prediction of Thermodynamic Properties and Phase Behavior of Fluids and Industrial Collaborations Mixtures with the SAFT-gamma Mie Group-Contribution BP, CaO Hellas, Dynamic Extraction, Julius Montz, Novartis, Pfizer, Equation of State, JOURNAL OF CHEMICAL AND Process Design Center, Procter & Gamble, Process Systems ENGINEERING DATA, Vol: 59, Pages: 3272-3288, ISSN: Enterprise, Public Power Corporation, Scottish Power, Syngenta 0021-9568 11. Jackson G, Galindo A, Adjiman CS, Müller EA, 2014, Employing Publications a SAFT equation of state to obtain force fields for use in Journal Articles coarse-grained molecular simulations, Pages: 1231-1232 1. Burger J, Papaioannou V, Gopinath S, Jackson G, Galindo A, 12. Kleniati P-M, Adjiman CS, 2014, Branch-and-Sandwich: a Adjiman CS, 2015, A hierarchical method to integrated solvent deterministic global optimization algorithm for optimistic bilevel
and process design of physical CO2 absorption using the programming problems. Part I: Theoretical development, SAFT- Mie approach, AICHE JOURNAL, Vol: 61, Pages: JOURNAL OF GLOBAL OPTIMIZATION, Vol: 60, Pages: 3249-3269, ISSN: 0001-1541 425-458, ISSN: 0925-5001 2. Habgood M, Sugden IJ, Kazantsev AV, Adjiman CS, 13. Kleniati P-M, Adjiman CS, 2014, Branch-and-Sandwich: a Pantelides CC, 2015, Efficient Handling of Molecular Flexibility deterministic global optimization algorithm for optimistic bilevel in Ab Initio Generation of Crystal Structures, JOURNAL OF programming problems. Part II: Convergence analysis and CHEMICAL THEORY AND COMPUTATION, Vol: 11, Pages: numerical results, JOURNAL OF GLOBAL OPTIMIZATION, 1957-1969, ISSN: 1549-9618 Vol: 60, Pages: 459-481, ISSN: 0925-5001 3. Kleniati P-M, Adjiman CS, 2015, A generalization of the 14. Pantelides CC, Adjiman CS, Kazantsev AV, 2014, General Branch-and-Sandwich algorithm: From continuous to Computational Algorithms for Ab Initio Crystal Structure mixed-integer nonlinear bilevel problems, COMPUTERS & Prediction for Organic Molecules, PREDICTION AND CHEMICAL ENGINEERING, Vol: 72, Pages: 373-386, ISSN: CALCULATION OF CRYSTAL STRUCTURES: METHODS AND 0098-1354 APPLICATIONS, Vol: 345, Pages: 25-58, ISSN: 0340-1022 4. Nerantzis D, Adjiman CS, 2015, Deterministic Global 15. Papadopoulos AI, Badr S, Chremos A, Forte E, Zarogiannis T, Optimization and Transition States, 12TH INTERNATIONAL Seferlis P, Papadokonstantakis S, Adjiman CS, Galindo A, SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING (PSE) Jackson G, 2014, Efficient screening and selection of th AND 25 EUROPEAN SYMPOSIUM ON COMPUTER AIDED post-combustion CO2 capture solvents, Chemical Engineering PROCESS ENGINEERING (ESCAPE), PT A, Vol: 37, Pages: Transactions, Vol: 39, Pages: 211-216, ISSN: 2283-9216 851-856, ISSN: 1570-7946 16. Papadopoulos AI, Badr S, Chremos A, Forte E, Zarogiannis T, 5. Papadokonstantakis S, Badr S, Hungerbühler K, Seferlis P, Papadokonstantakis S, Adjiman CS, Galindo A,
Papadopoulos AI, Damartzis T, Seferlis P, Forte E, Chremos A, Jackson G, 2014, Molecular design of optimum CO2 capture Galindo A, Jackson G, Adjiman C, 2015, Toward Sustainable solvents: From conceptual screening to SAFT-based
Solvent-Based Postcombustion CO2 Capture: From Molecules validation, Pages: 382-383 to Conceptual Flowsheet Design, Computer Aided Chemical 17. Pereira FE, Galindo A, Jackson G, Adjiman C, 2014, On the Engineering, Vol: 36, Pages: 279-310, ISSN: 1570-7946 impact of using volume as an independent variable for the 6. Papaioannou V, Calado F, Lafitte T, Dufal S, Sadeqzadeh M, solution of P-T fluid-phase equilibrium with equations of state, Jackson G, Adjiman CS, Galindo A, 2015, Application of the COMPUTERS & CHEMICAL ENGINEERING, Vol: 71, Pages: SAFT-γ Mie group contribution equation of state to fluids of 67-76, ISSN: 0098-1354 46
18. Rhazaoui K, Cai Q, Adjiman CS, Brandon NP, 2014, Towards Awards and Distinctions the 3D modeling of the effective conductivity of solid oxide fuel Fellow of the Royal Academy of Engineering (2005) cell electrodes – II. Computational parameters, CHEMICAL Fellow of Institution of Chemical Engineers (1997) ENGINEERING SCIENCE, Vol: 116, Pages: 781-792, ISSN: IChemE Council Medal (2005) 0009-2509 19. Schreckenberg JMA, Dufal S, Haslam AJ, Adjiman CS, Research Interests Jackson G, Galindo A, 2014, Modelling of the thermodynamic Numerical global optimisation techniques for process design. and solvation properties of electrolyte solutions with the Controllability analysis of nonlinear systems. Process modelling of statistical associating fluid theory for potentials of variable pressure swing adsorption and desalination units. Systems Biology range, MOLECULAR PHYSICS, Vol: 112, Pages: 2339-2364, and Systems Medicine with particular focus on liver physiology and ISSN: 0026-8976 protein networks in cancer. 20. Siougkrou E, Galindo A, Adjiman CS, 2014, On the optimal design of gas-expanded liquids based on process Other Activities performance, CHEMICAL ENGINEERING SCIENCE, Vol: 115, Pro-Vice-Provost, Head of the UCL Doctoral School Pages: 19-30, ISSN: 0009-2509 Member of College of Engineering for the Engineering & Physical 21. Vasileiadis M, Pantelides CC, Adjiman CS, 2014, Prediction of Sciences Research Council (EPSRC) the crystal structures of axitinib, a polymorphic pharmaceutical Vice Chair of BBSRC Multidisciplinary Synthetic Biology Research molecule, Chemical Engineering Science, Vol: 121, Pages: Centres panel (2014) 60-76, ISSN: 0009-2509 Vice Chair of EPSRC Engineering Fellowships for Growth – Synthetic Biology panel (2014) Selected Refereed Conference Publications Committee member of Computer Aided Process Engineering 1. Kazazakis N, Adjiman CS, 2014, GLOBIE: An algorithm for the Subject Group of Institution of Chemical Engineers deterministic global optimization of box-constrained NLPs, Member of European Federation of Chemical Engineers Working PROCEEDINGS OF THE 8th INTERNATIONAL CONFERENCE Party on Computer Aided Process Engineering (UK representative) ON FOUNDATIONS OF COMPUTER-AIDED PROCESS Member of International Federation of Automatic Control (IFAC) DESIGN, Vol: 34, Pages: 669-674, ISSN: 1570-7946 Technical Committee on Control of Environmental Systems 2. Papaioannou V, Lafitte T, Avendano C, Adjiman CS, Jackson Member of Royal Academy International Committee G, Müller EA, Galindo A, 2014, Group contribution Chair Royal Academy of Engineering Distinguished Visiting methodology based on the statistical associating fluid theory Fellowship Scheme for heteronuclear molecules formed from Mie segments, Chair Royal Academy of Engineering Industry Academic JOURNAL OF CHEMICAL PHYSICS, Vol: 140, ISSN: Partnerships Programme Steering Group (from 2016) 0021-9606 Chair League of European Research Universities Doctoral Studies Community UK representative on European Research Area Steering Group on Human Resources and Mobility Working Group on Doctoral Education Advisory Board of University of Zurich Graduate Campus Advisory Board AICES (Aachen Institute for Computational Engineering Science) RWTH Aachen
Reviewer for EPSRC, BBSRC, Royal Academy of Engineering, Royal Society, Industrial and Engineering Chemistry Research, Computers and Chemical Engineering, AIChEJournal, Engineering in the Life Sciences, Hepatology, Fonds National de la Recherche Luxembourg, Polish Research Council. I David L. Bogle CEng FREng FIChemE Academic Collaborations Professor of Chemical Engineering, Department of Chemical UCL Chemical Engineering, Centre for Mathematics and Physics in Engineering, University College London the Life Sciences and Experimental Biology (UCL), UCL Hepatology, UCL Cancer Institute, University of Palermo. Qualifications PhD in Chemical Engineering (Imperial College London) Industrial Collaborations MSc in Chemical Engineering (Imperial College London) PricewaterhouseCoopers DIC in Engineering (Imperial College London) BEng with honours in Chemical Engineering (Imperial College London) 47
Publications Awards and Distinctions Journal Articles 2014 Francis Bacon Medal, American Society of Mechanical 1. Perez-Galvan, C., & Bogle, I. D. L. (2014). Comparison Engineers between Interval Methods to Solve Initial Value Problems in 2014 RISE (Recognising Inspirational Scientists and Engineers) Chemical Process Design. 24th EUROPEAN SYMPOSIUM ON Fellow COMPUTER AIDED PROCESS ENGINEERING, PTS A AND 2014 Co-Director, Energy SuperStore B, 33, 1405-1410. 2014 Director Sustainable Gas Institute 2. Al-Fulaij, H., Cipollina, A., Micale, G., Ettouney, H., & Bogle, D. 2013 Member of Council, Royal Academy of Engineering (2014). Eulerian-Eulerian modelling and computational fluid 2012 Director Hydrogen and Fuel Cells Supergen Hub dynamics simulation of wire mesh demisters in MSF plants. 2012 Director Energy Storage Research Network ENGINEERING COMPUTATIONS, 31 (7), 1242-1260. 2012 BRE Fellow doi:10.1108/EC-03-2012-0063 2012 Visiting Professor, Energy Research Institute, NTU Singapore 3. Alsoudani, T. M., & Bogle, I. D. L. (2014). From discretization 2011 Baker Medal, Institute of Civil Engineering to regularization of composite discontinuous functions. 2011 OBE for services to UK-China science Computers & Chemical Engineering, 62, 139-160. 2008 Fellow of the Royal Academy of Engineering doi:10.1016/j.compchemeng.2013.11.019 2008 Fellow of the City and Guilds of London Institute 4. Tedesco M., Mazzola P., Micale G., Bogle I.D.L., Papapetrou, 2007 Royal Academy of Engineering Silver Medal Tamburini A., Cipollina A. (2014) Reverse Electrodialysis 2006 Chartered Engineer Process: Analysis of Optimal Conditions for Process Scale-up. 2006 Fellow of the Institute of Materials, Minerals and Mining In Proc EDS Conference on “Desalination for the Environment, 2006 Fellow of the Energy Institute Clean Water and Energy”, Cyprus, May 2014. 2006 Inaugural Energy Senior Research Fellow to the Research 5. Perez-Galvan, C. and Bogle, I. D. L. Deterministic Global Councils Energy programme Dynamic Optimisation using Interval Analysis (2014) in Proc 12th International Conference on Process Systems Research Interests Engineering, Copenhagen, 791-796 Professor Brandon’s research is focused on electrochemical power 6. Tedesco M., Cipollina A., Tamburini A., Bogle I.D.L., and sources for fuel cell and energy storage applications. He collaborates MICALE G. (2015) Reverse electrodialysis process with extensively with industry in this field, as well with other research seawater and concentrated brines: a comprehensive model centres and universities around the world, and he is Director of the for equipment design. Chemical Engineering Research and RC Energy programme funded Hydrogen and Fuel Cells SUPERGEN Design 93 441-456 Hub (www.h2fcsupergen.com). He was the founding Director of the 7. Mendes M.F. and Bogle I.D.L. (2015) Evaluation of the effects Energy Futures Lab at Imperial College (www.imperial.ac.uk/ and mechanisms of bioactive components present in energyfutureslab), and a founder of Ceres Power (www.cerespower. hypoglycemic plants. Int.J. Chem. & Biomolec. Sci. 1/3 com), an AIM listed fuel cell company spun out from Imperial College. 167-178 In 2014 he was appointed to the BG Chair in Sustainable Gas and as Director of the Sustainable Gas Institute at Imperial College.
Publications Journal Articles 1. Bahadori L, Chakrabarti MH, Hashim MA, Manan NSA, Mjalli FS, AlNashef IM, Brandon NP, 2015, Temperature Effects on the Kinetics of Ferrocene and Cobaltocenium in Methyltriphenylphosphonium Bromide Based Deep Eutectic Solvents, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 162, Pages: H617-H624, ISSN: 0013-4651 2. Bahadori L, Chakrabarti MH, Manan NSA, Hashim MA, Mjalli FS, AlNashef IM, Brandon N, 2015, The Effect of Temperature on Kinetics and Diffusion Coefficients of Metallocene Derivatives in Polyol-Based Deep Eutectic Solvents, PLOS ONE, Vol: 10, ISSN: 1932-6203 Nigel Brandon OBE FREng 3. Boldrin P, Millan-Agorio M, Brandon NP, 2015, Effect of Sulfur- and Tar-Contaminated Syngas on Solid Oxide Fuel Cell Director of the Sustainable Gas Institute (SGI), Department of Anode Materials, ENERGY & FUELS, Vol: 29, Pages: 442-446, Earth Science & Engineering, Imperial College London ISSN: 0887-0624 Boldrin P, Ruiz-Trejo E, Yu J, Gruar RI, Tighe CJ, Chang K-C, Ilavsky J, Darr JA, Brandon N, 2015, Qualifications Nanoparticle scaffolds for syngas-fed solid oxide fuel cells, PhD in Electrochemical Engineering (Imperial College London) JOURNAL OF MATERIALS CHEMISTRY A, Vol: 3, Pages: BSc (Eng) in Minerals Technology (Imperial College London) 3011-3018, ISSN: 2050-7488 48
4. Chakrabarti MH, Manan NSA, Brandon NP, Maher RC, Mjalli 15. Wu B, Yufit V, Merla Y, Martinez-Botas RF, Brandon NP, Offer FS, AlNashef IM, Hajimolana SA, Hashim MA, Hussain MA, Nir GJ, 2015, Differential thermal voltammetry for tracking of D, 2015, One-pot electrochemical gram-scale synthesis of degradation in lithium-ion batteries, JOURNAL OF POWER graphene using deep eutectic solvents and acetonitrile, SOURCES, Vol: 273, Pages: 495-501, ISSN: 0378-7753 CHEMICAL ENGINEERING JOURNAL, Vol: 274, Pages: 16. Cai Q, Adjiman CS, Brandon NP, 2014, Optimal control 213-223, ISSN: 1385-8947 strategies for hydrogen production when coupling solid oxide 5. Dewage HH, Wu B, Tsoi A, Yufit V, Offer G, Brandon N, 2015, electrolysers with intermittent renewable energies, JOURNAL A novel regenerative hydrogen cerium fuel cell for energy OF POWER SOURCES, Vol: 268, Pages: 212-224, ISSN: storage applications, JOURNAL OF MATERIALS CHEMISTRY 0378-7753 A, Vol: 3, Pages: 9446-9450, ISSN: 2050-7488 17. Chakrabarti MH, Brandon NP, Hajimolana SA, Tariq E, Yufit V, 6. Duboviks V, Lomberg M, Maher RC, Cohen LF, Brandon NP, Hashim MA, Hussain MA, Low CTJ, Aravind PV, 2014, Offer GJ, 2015, Carbon deposition behaviour in metal- Application of carbon materials in redox flow batteries, infiltrated gadolinia doped ceria electrodes for simulated JOURNAL OF POWER SOURCES, Vol: 253, Pages: 150-166, biogas upgrading in solid oxide electrolysis cells, JOURNAL ISSN: 0378-7753 OF POWER SOURCES, Vol: 293, Pages: 912-921, ISSN: 18. Chung D-W, Shearing PR, Brandon NP, Harris SJ, Garcia RE, 0378-7753 2014, Particle Size Polydispersity in Li-Ion Batteries, 7. Mazur C, Contestabile M, Offer GJ, Brandon NP, 2015, JOURNAL OF THE ELECTROCHEMICAL SOCIETY, Vol: 161, Understanding the drivers of fleet emission reduction activities Pages: A422-A430, ISSN: 0013-4651 of the German car manufacturers, Environmental Innovation 19. Cooper SJ, Eastwood DS, Gelb J, Damblanc G, Brett DJL, and Societal Transitions, Vol: 16, Pages: 3-21 Bradley RS, Withers PJ, Lee PD, Marquis AJ, Brandon NP, 8. Parkes MA, Refson K, d’Ayezac M, Offer GJ, Brandon NP, Shearing PR, 2014, Image based modelling of microstructural Harrison NM, 2015, Chemical Descriptors of Yttria-Stabilized heterogeneity in LiFePO4 electrodes for Li-ion batteries, Zirconia at Low Defect Concentration: An ab Initio Study, JOURNAL OF POWER SOURCES, Vol: 247, Pages: 1033- JOURNAL OF PHYSICAL CHEMISTRY A, Vol: 119, Pages: 1039, ISSN: 0378-7753 6412-6420, ISSN: 1089-5639 20. Duboviks V, Maher RC, Kishimoto M, Cohen LF, Brandon NP, 9. Rhazaoui K, Cai Q, Kishimoto M, Tariq F, Somalu MR, Adjiman Offer GJ, 2014, A Raman spectroscopic study of the carbon
CS, Brandon NP, 2015, Towards the 3D Modelling of the deposition mechanism on Ni/CGO electrodes during CO/CO2 Effective Conductivity of Solid Oxide Fuel Cell Electrodes – electrolysis, PHYSICAL CHEMISTRY CHEMICAL PHYSICS, Validation against experimental measurements and prediction Vol: 16, Pages: 13063-13068, ISSN: 1463-9076 of electrochemical performance, ELECTROCHIMICA ACTA, 21. Eastwood DS, Bradley RS, Tariq F, Cooper SJ, Taiwo OO, Vol: 168, Pages: 139-147, ISSN: 0013-4686 Gelb J, Merkle A, Brett DJL, Brandon NP, Withers PJ, Lee PD, 10. Ruiz-Trejo E, Atkinson A, Brandon NP, 2015, Metallizing Shearing PR, 2014, The application of phase contrast X-ray porous scaffolds as an alternative fabrication method for solid techniques for imaging Li-ion battery electrodes, NUCLEAR oxide fuel cell anodes, JOURNAL OF POWER SOURCES, Vol: INSTRUMENTS & METHODS IN PHYSICS RESEARCH 280, Pages: 81-89, ISSN: 0378-7753 SECTION B-BEAM INTERACTIONS WITH MATERIALS AND 11. Ruiz-Trejo E, Zhou Y, Brandon NP, 2015, On the manufacture ATOMS, Vol: 324, Pages: 118-123, ISSN: 0168-583X of silver-BaCe0.5Zr0.3Y0.16Zn0.04O3-delta composites for 22. Eastwood DS, Yufit V, Gelb J, Gu A, Bradley RS, Harris SJ, hydrogen separation membranes, INTERNATIONAL Brett DJL, Brandon NP, Lee PD, Withers PJ, Shearing PR, JOURNAL OF HYDROGEN ENERGY, Vol: 40, Pages: 2014, Lithiation- Induced Dilation Mapping in a Lithium- Ion 4146-4153, ISSN: 0360-3199 Battery Electrode by 3D X- Ray Microscopy and Digital 12. Stockford C, Brandon N, Irvine J, Mays T, Metcalfe I, Book D, Volume Correlation, ADVANCED ENERGY MATERIALS, Vol: 4, Ekins P, Kucernak A, Molkou V, Steinberger-Wilckens R, Shah ISSN: 1614-6832 N, Dodds P, Dueso C, Samsatli S, Thompson C, 2015, H2FC 23. Guerra C, Lanzini A, Leone P, Santarelli M, Brandon NP, 2014, SUPERGEN: An overview of the Hydrogen and Fuel Cell Optimization of dry reforming of methane over Ni/YSZ anodes research across the UK, INTERNATIONAL JOURNAL OF for solid oxide fuel cells, JOURNAL OF POWER SOURCES, HYDROGEN ENERGY, Vol: 40, Pages: 5534-5543, ISSN: Vol: 245, Pages: 154-163, ISSN: 0378-7753 0360-3199 24. Howey DA, Mitcheson PD, Yufit V, Offer GJ, Brandon NP, 13. Teng F, Pudjianto D, Strbac G, Brandon N, Thomson A, Miles 2014, Online Measurement of Battery Impedance Using Motor J, 2015, Potential value of energy storage in the UK electricity Controller Excitation, IEEE TRANSACTIONS ON VEHICULAR system, PROCEEDINGS OF THE INSTITUTION OF CIVIL TECHNOLOGY, Vol: 63, Pages: 2557-2566, ISSN: 0018-9545 ENGINEERS-ENERGY, Vol: 168, Pages: 107-117, ISSN: 25. Kalyvas C, Kucernak A, Brett D, Hinds G, Atkins S, Brandon 1751-4223 N, 2014, Spatially resolved diagnostic methods for polymer 14. Tonekabonimoghadam S, Akikur RK, Hussain MA, Hajimolana electrolyte fuel cells: a review, WILEY INTERDISCIPLINARY S, Saidur R, Ping HW, Chakrabarti MH, Brandon NP, Aravind REVIEWS-ENERGY AND ENVIRONMENT, Vol: 3, Pages: PV, Nayagar JNS, Hashim MA, 2015, Mathematical modelling 254-275, ISSN: 2041-8396 and experimental validation of an anode-supported tubular 26. Kishimoto M, Lomberg M, Ruiz-Trejo E, Brandon NP, 2014, solid oxide fuel cell for heat and power generation, ENERGY, Enhanced triple-phase boundary density in infiltrated Vol: 90, Pages: 1759-1768, ISSN: 0360-5442 electrodes for solid oxide fuel cells demonstrated by high- 49
resolution tomography, JOURNAL OF POWER SOURCES, 3. Tariq F, Yufit V, Kishimoto M, Cui G, Somalu M, Brandon N, Vol: 266, Pages: 291-295, ISSN: 0378-7753 2014, Advanced 3D Imaging and Analysis of SOFC 27. Lomberg M, Ruiz-Trejo E, Offer G, Brandon NP, 2014, Electrodes, Symposium on Solid State Ionic Devices 10 held Characterization of Ni-Infiltrated GDC Electrodes for Solid during the 226th Meeting of the Electrochemical-Society, Oxide Cell Applications, JOURNAL OF THE Publisher: ELECTROCHEMICAL SOC INC, Pages: 81-86, ELECTROCHEMICAL SOCIETY, Vol: 161, Pages: F899-F905, ISSN: 1938-5862 ISSN: 0013-4651 4. Kishimoto M, Lomberg M, Ruiz-Trejo E, Brandon NP, 2014, 28. Rhazaoui K, Cai Q, Adjiman CS, Brandon NP, 2014, Towards Towards the Microstructural Optimization of SOFC Electrodes the 3D modeling of the effective conductivity of solid oxide fuel Using Nano Particle Infiltration, Symposium on Solid State cell electrodes – II. Computational parameters, CHEMICAL Ionic Devices 10 held during the 226th Meeting of the ENGINEERING SCIENCE, Vol: 116, Pages: 781-792, ISSN: Electrochemical-Society, Publisher: ELECTROCHEMICAL 0009-2509 SOC INC, Pages: 93-102, ISSN: 1938-5862 29. Ruiz-Trejo E, Boldrin P, Lubin A, Tariq F, Fearn S, Chater R, 5. Maskell WC, Brett DJL, Brandon NP, 2014, Thick-film Cook SN, Atkinson A, Gruar RI, Tighe CJ, Darr J, Brandon NP, amperometric zirconia oxygen sensors: influence of cobalt 2014, Novel Composite Cermet for Low-Metal-Content oxide as a sintering aid, Publisher: IOP PUBLISHING LTD, Oxygen Separation Membranes, CHEMISTRY OF ISSN: 0957-0233 MATERIALS, Vol: 26, Pages: 3887-3895, ISSN: 0897-4756 6. Philbin SP, Jones D, Brandon NP, Hawkes AD, 2014, 30. Tariq F, Kishimoto M, Yufit V, Cui G, Somalu M, Brandon NP, Exploring Research Institutes: Structures, Functioning and 2014, 3D imaging and quantification of interfaces in SOFC Typology, Portland International Conference on Management anodes, JOURNAL OF THE EUROPEAN CERAMIC SOCIETY, of Engineering & Technology (PICMET), Publisher: IEEE, Vol: 34, Pages: 3755-3761, ISSN: 0955-2219 Pages: 2569-2582, ISSN: 2159-5100 31. Tariq F, Yufit V, Eastwood DS, Merla Y, Biton M, Wu B, Chen Z, Freedman K, Offer G, Peled E, Lee PD, Golodnitsky D, Invited Lectures Brandon N, 2014, In-Operando X-ray Tomography Study of 1. The Role of Shale Gas in UK Energy Security, Invited lecture, Lithiation Induced Delamination of Si Based Anodes for Shale Gas Environmental Summit, London, Oct 26-27th, 2015. Lithium-Ion Batteries, ECS ELECTROCHEMISTRY LETTERS, 2. Natural Gas in the UK – a stepping stone or an end point? Vol: 3, Pages: A76-A78, ISSN: 2162-8726 Invited lecture, BIEE Gas Seminar, London, 15th October 2015. 32. Tariq F, Yufit V, Kishimoto M, Shearing PR, Menkin S, 3. Electrochemistry in energy applications: policy drivers, Golodnitsky D, Gelb J, Peled E, Brandon NP, 2014, Three- commercial opportunities and research challenges, Conference dimensional high resolution X-ray imaging and quantification of plenary lecture, ECS conference on electrochemical energy lithium ion battery mesocarbon microbead anodes, JOURNAL conversion and storage, Glasgow, 26th to 31st July 2015. OF POWER SOURCES, Vol: 248, Pages: 1014-1020, ISSN: 4. Visualisation and quantification of microstructural change in 0378-7753 battery electrodes, Invited lecture, ECS conference on 33. Troxler Y, Wu B, Marinescu M, Yufit V, Patel Y, Marquis AJ, electrochemical energy conversion and storage, Glasgow, 26th Brandon NP, Offer GJ, 2014, The effect of thermal gradients to 31st July 2015. on the performance of lithium-ion batteries, JOURNAL OF 5. Application of 3D imaging to design better electrodes for fuel POWER SOURCES, Vol: 247, Pages: 1018-1025, ISSN: cells and flow cells, Invited lecture, Annual meeting of the 0378-7753 STFC Global chellenge network in batteries and 34. Wu B, Parkes MA, Yufit V, De Benedetti L, Veismann S, electrochemical devices, Oxford, 30th June to 1st July 2015. Wirsching C, Vesper F, Martinez-Botas RF, Marquis AJ, Offer 6. An overview of the UK Energy Storage Research Network and GJ, Brandon NP, 2014, Design and testing of a 9.5 kWe the Supergen Energy Storage Hub, Invited lecture, 2nd proton exchange membrane fuel cell-supercapacitor passive symposium on Heat and Electricity Storage, PSI, Villigen, hybrid system, INTERNATIONAL JOURNAL OF HYDROGEN Switzerland, 5th May 2015. ENERGY, Vol: 39, Pages: 7885-7896, ISSN: 0360-3199 7. Correlating Solid Oxide Cell Microstructure and Performance, 35. Yang W, Zhao Y, Liso V, Brandon N, 2014, Optimal design and Invited lecture, Manufacturing Green Fuels from Renewable operation of a syngas-fuelled SOFC micro-CHP system for Energy, DTU Riso, Denmark, 15th April 2015. residential applications in different climate zones in China, 8. Making Gas Greener, Invited lecture, Flame, Amsterdam, 14th ENERGY AND BUILDINGS, Vol: 80, Pages: 613-622, ISSN: April 2015. 0378-7788 9. Overview of energy storage technologies and options, Invited lecture, UK energy storage: The Opportunities, Renewable Conference Papers Energy Association, London, 12th March 2015. 1. Boldrin P, Ruiz-Trejo E, Tighe C, Chang KC, Darr J, Brandon 10. The role of fuel cells and energy storage in low carbon energy NP, 2015, Impregnation of nanoparticle scaffolds for syngas- systems, Invited lecture, Midlands Energy Consortium, fed solid oxide fuel cell anodes, Pages: 1219-1227, ISSN: Nottingham, 11th March 2015. 1938-5862 11. Materials Engineering for Solid Oxide Fuel Cells and 2. Lomberg M, Boldrin P, Tariq F, Offer G, Wu B, Brandon NP, Electrolysers, Invited lecture, 9th International Symposium on 2015, Additive manufacturing for solid oxide cell electrode Hydrogen and Energy, Emmetten, Switzerland, 25-30th fabrication, Pages: 2119-2127, ISSN: 1938-5862 January 2015. 50
12. Understanding electrodes in fuel cells and batteries, Invited lecture, University of Calgary, Canada, 20th November 2014. 13. The role and value of fuel cells and energy storage in low carbon energy systems, Zandmer Distinguished lecture, University of Calgary, Canada, 19th November 2014. 14. Solid Oxide Fuel Cell Electrodes – a design led approach, Invited lecture, Workshop on industrial and academic advances in Solid Oxide Fuel Cells, Imperial College, London, October 30th 2014. 15. UK Hydrogen and Fuel Cell Research – an overview, Plenary lecture, 14th International Symposium on Metal-Hydrogen Systems, Salford, Manchester, 20-25th July 2014. 16. An overview of UK Fuel Cell Research, UK-Korea workshop on fuel cells, Seoul, South Korea, 17-18th July 2014. 17. Solid Oxide Fuel Cells – from concept to commercialisation, Benoît Chachuat Francis Bacon Medal award lecture, 12th ASME Fuel Cell Science, Engineering and Technology Conference, Boston, Reader in Process Systems Engineering, Department of USA, June 30th to July 2nd 2014. Chemical Engineering, Imperial College London 18. Grid scale energy storage – a transformation, Invited lecture, 3rd annual Oxford Energy Conference, Oxford, June 17th 2014. Qualifications 19. Developments in Solid Oxide Fuel Cells, Invited lecture, 3rd MEng in Environmental Engineering (1998, with Distinction – International symposium on solid oxide fuel cells for next ENGEES, Strasbourg, France) generation power plants: gasifier-SOFC systems, Warsaw, MSc in Engineering Science (1998, with Distinction – Universite Poland, June 2nd 2014. Louis Pasteur, Strasbourg, France) 20. 3D Imaging and Analysis of SOFC Electrodes, Grove Fuel Cell PhD in Chemical Engineering (2001, with Distinction – INPL, Nancy, Symposium, Amsterdam, 3-4th April, 2014. France) 21. Fuel cells for Power and Heat, Invited lecture, Innovation in Energy, Royal academy of Engineering, London, 31st March, Awards and Distinctions (Selection) 2014. Certificate of Excellence in Reviewing, Computers & Chemical 22. Understanding SOFC Electrodes: characterisation, design and Engineering, 2013 fabrication, 10th Int Hydrogen and Fuel Cell Conference, Top-5 papers published in Journal of Global Optimization in 2013, Birmingham, 26-27 March, 2014. “Convergence analysis of Taylor models and McCormick Taylor 23. Advances in Electrodes for Solid Oxide Fuel Cells and models” Electrolysers, Plenary lecture, International Conference on CAST Outstanding Young Researcher Award, AIChE, 2014 Nanotechnology, nanomaterials and thin films for energy CAST Directors Award, AIChE, 2015 applications, London, 19-21 February, 2014. 24. The Role of Renewable Energy, Invited speaker, Oxford Research Interests Climate Forum,, Oxford, Feb 7-8th 2014. 1. Environmental systems engineering: design and operation of 25. Hydrogen – a key enabler for low carbon energy systems? wastewater treatment and recovery plants; multiscale Plenary lecture, Hydrogen: A vital element for our sustainable modeling, design and operation of miroalgae culture systems. future, Bath University, Jan 30th 2014. 2. Integrated membrane processes: OSN membrane cascades for separation of organic mixtures; modeling and optimization of membrane contactors; water network synthesis with membrane regenerators. 3. Analysis of uncertainty propagation in dynamic systems optimization-based control and real-time optimization of dynamic systems. 4. Complete search methods and tools for global optimization and constraint satisfaction.
Other Activities (Selection) Program Coordinator (Elect.), Area 10D (Applied Mathematics and Numerical Analysis), AIChE Computing & Systems Technology (CAST) division, 2015-2016 Member of International Programming Committee, 9th IFAC Symposium on Advanced Control of Chemical Processes (ADCHEM), June 2015 UK Representative of IFAC Technical Committee on Chemical 51
Process Control, since March 2015 5. C. Puchongkawarin, C. Gomez-Mont, D.C. Stuckey, B. Visiting Scientist, Department of Industrial Engineering, University of Chachuat, Optimization-based Methodology for the Synthesis Padova, Italy (June 2014) of Wastewater Facilities for Energy and Nutrient Recovery, Invited Professor, Automatic Control Laboratory, EPFL (August- Chemosphere, 140:150-158, 2015. September 2015) 6. M.E. Villanueva, B. Houska, B. Chachuat, Unified Framework for the Propagation of Continuous-Time Enclosures for Plenary and Keynote Lectures Parametric Nonlinear ODEs, Journal of Global Optimization, 9th IFAC Internation Symposium on Advanced Control of Chemical 62(3):575-613, 2015. Processes (ADCHEM), Plenary address, June 2015 7. C.S. Khor, B. Chachuat, N. Shah, Optimization of Water AIChE Annual Meeting, CAST Division Plenary, November 2014 Network Synthesis: Milestones, Challenges, and Future Directions, Industrial & Engineering Chemistry Research, Editorial and Peer-Review Activities 53(25):10257-10275, 2014. Associate Editor, Journal of Process Control (Elsevier) 8. C.S. Khor, B. Chachuat, N. Shah, Fixed-Flowrate Total Water Associate Editor, Journal of Optimization Theory & Applications Network Synthesis under Uncertainty with Risk Management, (Springer) Journal of Cleaner Production, 77:79-93, 2014. Guest Editor, Optimal Control Applications & Methods (Wiley), special 9. B. Houska, B. Chachuat, Branch-and-Lift Algorithm for issue on Global and Robust Optimization of Dynamic systems Deterministic Global Optimization in Nonlinear Optimal Control, Reviewer for: AIChE Journal; Annual Reviews in Control; Applied Journal of Optimization Theory & Applications, 162(1):208- Energy; Applied Mathematics & Computations; Applied Numerical 248, 2014. Mathematics; Automatica; Computers & Chemical Engineering; IEEE Control Systems Magazine; IEEE Transactions on Automatic Peer Reviewed International Conference Papers Control; Industrial & Engineering Chemistry Research; Journal of 1. B. Chachuat, B. Houska, R. Paulen, N. Peric, J. Rajyaguru, Global Optimization; Journal of Optimization Theory & Applications; M.E. Villanueva, Set-Theoretic Approaches in Analysis, Journal of Process Control; Mathematical Programming; Estimation and Control of Nonlinear Systems (Plenary Optimization & Engineering; Optimization Letters; Optimization Address), International Symposium on Advanced Control of Methods & Software Chemical Processes (ADCHEM), 7-10 June 2015, Whistler, British Columbia, Canada. Academic Collaborations 2. J. Rajyaguru, M.E. Villanueva, B. Houska, B. Chachuat, EPFL, Switzerland, Automatic Control Lab (Prof. Bonvin) Continuous-Time Enclosures for Uncertain Implicit Differential INRIA Sophia Antipolis, France, BIOCORE Group (Dr. Bernard) Equations, International Symposium on Advanced Control of INRA, France, LBE Narbonne (Dr. Steyer) Chemical Processes (ADCHEM’2015), 7-10 June 2015, MIT, Dpt Chemical Engineering (Prof. Barton) Whistler, British Columbia, Canada. RWTH Aachen, Dpt Mechanical Engineering (Prof. Mitsos) 3. C. Puchongkawarin, S. Fitzgerald, B. Chachuat, Plantwide STU Bratislava, Slovakia, Dpt Chemical Engineering (Prof. Fikar) Optimization of Activated Sludge Plants with Anaerobic University of Padova, Dpt Industrial Engineering (Prof. Bezzo), Dpt Sludge Treatment, International Symposium on Advanced Biology (Prof. Morosinotto) Control of Chemical Processes (ADCHEM’2015), 7-10 June 2015, Whistler, British Columbia, Canada. Industrial Collaborations 4. M. Sun, B. Chachuat, E.N. Pistikopoulos, Design of Petronas, Praxair, Sydney Water, Syngenta Multiparametric NCO-tracking Controllers for Linear Dynamic Systems, 12th PSE and 25th ESCAPE Symposium, 31 May-4 Publications June 2015, Copenhagen, Denmark. Journal Articles 5. M.E. Villanueva, J. Rajyaguru, B. Houska, B. Chachuat, 1. J. Fu, J.M. Faust, B. Chachuat, A. Mitsos, Local Optimization Ellipsoidal Arithmetic for Nonlinear Vector-Valued Functions12th of Dynamic Programs with Guaranteed Satisfaction of Path PSE and 25th ESCAPE Symposium, 31 May-4 June 2015, Constraints, Automatica, 62:184-192, 2015. Copenhagen, Denmark. 2. B. Houska, M.E. Villanueva, B. Chachuat, Stable Set-Valued 6. A. Bernardi, A. Nikolaou, A. Meneghesso, B. Chachuat, T. Integration of Nonlinear Dynamic Systems using Affine Set Morosinotto, F. Bezzo, Dynamic Modelling of PI Curves in Parameterizations, SIAM Journal on Numerical Analysis, 53(5), Microalgae, 12th PSE and 25th ESCAPE Symposium, 31 May-4 2307-2328, 2015. June 2015, Copenhagen, Denmark. 3. C. Puchongkawarin, C. Menichini, C. Laso-Rubido, S.K. 7. A. Bernardi, A. Nikolaou, A. Meneghesso, T. Morosinoto, B. Fitzgerald, B. Chachuat, Model-Based Methodology for Chachuat, F. Bezzo, Using Fluorescence Measurements to Model Plantwide Analysis of Wastewater Treatment Plants: Industrial Key Phenomena in Microalgae Photosynthetic Mechanisms, Case Study, Water Practice & Technology, 10(3), 517-526, 2015. 12th International Conference on Chemical and Process 4. A. Nikolaou, A. Bernardi, A. Meneghesso, F. Bezzo, T. Engineering (ICheaP-12), 19-22 May 2015, Milano, Italy. Morosinotto, B. Chachuat, A Model of Chlorophyll Fluorescence in Microalgae Integrating Photoproduction, Photoinhibition and Photoregulation, Journal of Biotechnology, 194:91-99, 2015. 52
8. A. Nikolaou, A. Bernardi, F. Bezzo, T. Morosinoto, B. 2. Andras Kupcsik, Marc P. Deisenroth, Jan Peters, Loh Ai Poha, Chachuat, A Dynamic Model of Photoproduction, Prahlad Vadakkepata, Gerhard Neumann, Model-based Photoregulation and Photoinhibition in Microalgae using Contextual Policy Search for Data-Efficient Generalization of Chlorophyll Fluorescence, 19th World Congress of the Robot Skills, Artificial Intelligence, 2015 International Federation of Automatic Control (IFAC’14), 24-29 3. Roberto Calandra, Andre Seyfarth, Jan Peters, Marc P. Aug 2014, Cape Town, South Africa. Deisenroth, Bayesian Optimization for Learning Gaits under 9. M.E. Villanueva, B. Houska, B. Chachuat, On the Stability of Uncertainty, Annals of Mathematics and Artificial Intelligence, Set-Valued Integration for Nonlinear Parametric ODEs 24th 2015 European Symposium on Computer Aided Process Engineering (ESCAPE24),15-18 June 2014, Budapest, Hungary. Conference Contributions 1. Niklas Wahlström, Thomas B. Schön, Marc P. Deisenroth, Learning Deep Dynamical Models From Image Pixels, IFAC Symposium on System Identification, 2015 2. Roberto Calandra, Serena Ivaldi, Marc P. Deisenroth, Jan Peters, Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin, Proceedings of the IEEE- RAS International Conference on Humanoid Robots, 2015 3. Marc P. Deisenroth, Jun W. Ng, Distributed Gaussian Processes, Proceedings of the International Conference on Machine Learning, 2015 4. Roberto Calandra, Serena Ivaldi, Marc P. Deisenroth, Elmar Rueckert, Jan Peters, Learning Inverse Dynamics Models with Contacts, Proceedings of the IEEE International Conference on Robotics and Automation, 2015 Marc Deisenroth 5. Sanket Kamthe, Jan Peters, Marc P. Deisenroth, Multi-Modal Filtering for Non-linear Estimation, International Conference on Lecturer in Statistical Machine Learning, Department of Acoustics, Speech, and Signal Processing (ICASSP), 2014 Computing, Imperial College London 6. Nooshin Haji Ghassemi, Marc P. Deisenroth, Analytic Long- Term Forecasting with Periodic Gaussian Processes, Qualifications Proceedings of the International Conference on Artificial PhD in Computer Science (Karlsruhe Institute of Technology) Intelligence and Statistics (AISTATS), 2014 7. Roberto Calandra, Jan Peters, Andre Seyfarth, Marc P. Awards and Distinctions Deisenroth, An Experimental Evaluation of Bayesian Best Cognitive Robotics Paper Award at ICRA 2014 Optimization on Bipedal Locomotion, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Research Interests 2014 Machine Learning, Robotics, Optimization 8. Marc P. Deisenroth, Peter Englert, Jan Peters, Dieter Fox, Multi-Task Policy Search for Robotics, Proceedings of the Other Activities IEEE International Conference on Robotics and Automation Area Chair at NIPS 2015 (ICRA), 2014 9. Bastian Bischoff, Duy Nguyen-Tuong, Herke van Hoof, Andrew Reviewer for McHutchon, Carl E. Rasmussen, Alois Knoll, Jan Peters, Marc P. JMLR, NIPS, ICRA, RLDM, Cambridge University Press, AISTATS Deisenroth, Policy Search For Learning Robot Control Using Sparse Data, Proceedings of the IEEE International Conference Academic Collaborations on Robotics and Automation (ICRA), 2014 MIT, TU Darmstadt, AIMS Senegal, Uppsala University Invited Lectures and Seminars 2015 (Talks/Seminars) Book Chapters University of Edinburgh Roberto Calandra, Nakul Gopalan, Andre Seyfarth, Jan Peters, ETH Zurich Marc P. Deisenroth, Bayesian Gait Optimization for Bipedal University of Washington Locomotion, volume 8426 (Lecture Notes in Computer Science), Sloan pp.274–290, 2014 Summit at London Business School (Keynote) International Conference on Machine Learning (Contributed Talk) Publications Workshop on Autonomous Citizens (Keynote) Journal Articles AI Society, Queen Mary University London 1. Marc P. Deisenroth, Dieter Fox, Carl E. Rasmussen, Gaussian Robotics Society, Imperial College London Processes for Data-Efficient Learning in Robotics and Control, NIPS Workshop on Bayesian Optimization (Contributed Talk) IEEE Transactions on Pattern Analysis and Machine Intelligence, Tesco volume 37, pp.408–423, 2015 53
2015 (Tutorials) Reviewer for Machine Learning Summer School (Chalmers University) Analytical Chemistry, Journal of Proteome Research, Computers & Gaussian Process Winter School (University of Sheffield) Chemical Engineering, Journal of Global Optimisation, Chemical Engineering Research and Design. 2014 (Talks/Seminars) Microsoft Research Academic Collaborations University of Sheffield MRC Clinical Sciences Centre (London), Hammersmith Hospital TU Darmstadt (London), Institut Pasteur, The Francis Crick Institute, The University University of Hertfordshire of Edinburgh, Howard Hughes Medical Institute, University of Rhode University College London Island. Georgia Institute of Technology International Conference on Artificial Industrial Collaborations Intelligence and Statistics (Contributed Talk) GSK International Conference on Robotics and Automation AstraZeneca (Contributed Talk) Chalmers University Publications University of Oxford Journal Articles British Petroleum 1 Horejs, C.M., Serio A., Purvis A., Gormley A.J., Bertazzo S., Workshop on Policy Learning at International Conference on Poliniewicz A., Wang A., DiMaggio P.A., Hohenester E., Humanoid Robotics (Invited Talk) Stevens M.M., “A biologically active laminin-111 fragment that modulates the epithelial-to-mesenchymal transition in embryonic stem cells”, PNAS, 111(16), 5908-5913 (2014). 2. DiMaggio P.A., O’Connor C., Shenk T., and B.A. Garcia, “Quantitative proteomic discovery of dynamic epigenome changes that control human cytomegalovirus infection”, Mol. Cell. Proteom., 13(9), 2399-410 (2014). 3. Dattani R., Gibson K., Few S., Borg A., DiMaggio P.A., Nelson J., Kazarian S., Cabral J., “Fullerene Oxidation and Clustering in Solution Induced by Light”, J Colloid Interface Sci., 446, 24-30 (2015). 4. Brownstein N.C., Guan X.,Yuan Mao Y., Zhang Q. DiMaggio P.A., Xia Q., Marshall A.G., and N.L. Young, “Paired Single Residue-Transposed Lys-N and Lys-C Digestions for Label- Free Identification of N-Terminal and C-Terminal MS/MS Peptide Product Ions: Ultrahigh Resolution FT-ICR MS and Peter DiMaggio MS/MS for Peptide De Novo Sequencing”, Rapid Commun. Mass Spectrometry, 29(7), 659-66 (2015). Senior Lecturer, Department of Chemical Engineering, Imperial College London Invited Lectures and Seminars 1. ELRIG Drug Discovery Meeting, September 2015, Telford UK. Qualifications 2. Wellcome Trust Epigenomics of Common Diseases, BSc in Chemical Engineering November 2015, Wellcome Trust Genome Campus, PhD in Chemical Engineering Cambridge, UK.
Awards and Distinctions Ruth L. Kirschstein National Research Service Award: NIH Postdoctoral Research Fellowship, Princeton U., 2010-2012 Porter Ogden Jacobus Honorific Fellowship, Princeton U., 2008-09 Kristine M. Layn Award for Outstanding Achievement in Research, Princeton U., 2007
Research Interests Holistic integration of proteomics and genomics data to understand the epigenetic basis of disease regulation Combinatorial optimisation and multivariate statistical tools for the interpretation and integration of large-scale omics datasets. 54
63576-1.50051-0 3. Galvanin, A., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. (2015). A model-based experimental design study for the development of kinetic models of methanol oxidation on silver catalyst. Proceedings of CAPE Forum 2015, 87-93. 4. Charitopoulos, V., & Dua, V. (2015). A Unified Framework for Model-Based Multi-objective Process and Energy Optimisation under Uncertainty. Proceedings of SusTEM conference 2015 5. Bhatti, A. H., Thomas, G., & Dua, V. (2015). Model based design of a gene metabolic system using model predictive control. ChemEngDayUK 2015, Sheffield Charitopoulos, V., & Dua, V. (2015). Explicit Model Predictive Control of Hybrid Systems using Multi-parametric Mixed Integer Polynomial Programming. 17th British-French-German Conference on Vivek Dua Optimization 2015, London 6. Mid, E. C., & Dua, V. (2015). Model predictive fault-tolerant Senior Lecturer and Departmental Tutor, Department of control of process systems. ChemEngDayUK 2015, Sheffield Chemical Engineering, UCL 7. Jamili, E., & Dua, V. (2015). Modelling and Optimal Control of Non-Viral siRNA Delivery. AIChE Annual Meeting 2015, Salt Qualifications Lake City PhD in Chemical Engineering, Imperial College London 8. Dua, V., & Jamili, E. (2015). Modelling and optimal control of MTech in Chemical Engineering, Indian Institute of Technology, Kanpur non-viral siRNA delivery. ChemEngDayUK 2015, Sheffield BE (Honours) in Chemical Engineering, Panjab University, Chandigarh 9. Dua, V., & Owolaja, A. (2015). Parameter Estimation and Nonlinear Model Predictive Control Using Meshless Modelling Research Interests Framework. AIChE Annual Meeting 2015, Salt Lake City Model Reduction, Parameter Estimation, Mixed-Integer 10. Vyas, J., & Dua, V. (2015). Process Synthesis and Design Optimisation, Refinery-wide optimization, Solvent Extraction based under Uncertainty: A Specific Class of MINLP Problems. 17th Water Desalination, Synthetic Biology, Cystic Fibrosis British-French-German Conference on Optimization 2015, London Other Activities Member Synthetic Biology Network Co-editor of Process Systems Engineering book series
Reviewer for AIChE Journal, Industrial and Engineering Chemistry Research, Computers and Chemical Engineering, Journal of Global Optimization, Automatica, IEEE Transactions Neural Networks, IFAC Conferences
Publications Journal Articles 1. Dua, V. (2015). Mixed integer polynomial programming. Computers & Chemical Engineering, 72, 387-394. doi:10.1016/j.compchemeng.2014.07.020 2. Galvanin, F., Cao, E., Al-Rifai, N., Dua, V., & Gavriilidis, A. Eric S Fraga (2015). Optimal design of experiments for the identification of Professor of Process Systems Engineering, Department kinetic models of methanol oxidation over silver catalyst. of Chemical Engineering, University College London Chimica Oggi/Chemistry Today, 33 (3), 51-56.
Qualifications Conference Contributions BSc in Applied Mathematics (University of Alberta) 1. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. MSc in Computer Science (University of Alberta) (2015). Model-based design of experiments for the PhD in Computer Science (University of Waterloo) identification of kinetic models in microreactor platforms. Computer Aided Chemical Engineering, 37, 323-328. Research Interests doi:10.1016/B978-0-444-63578-5.50049-9 Professor Fraga’s interests lie at the interfaces between engineering, 2. Bhatti, A. H., Thomas, G., & Dua, V. (2015). Design of a Gene mathematics and computer science. He is specifically interested in Metabolator under Uncertainty. Computer Aided Chemical the design of novel computer algorithms and mathematical Engineering, 37, 2141-2146. doi:10.1016/B978-0-444- 55
techniques and their application to problems in process engineering. Conference Contributions In the past, his research has concentrated on the development of 1. C Jones, K Armstrong & E Fraga (2015), Wider Impacts: methods for automated process design, or process synthesis, with general discussion, Faraday Discussions, 10.1039/ the development of tools for the design of profitable, safe, C5FD90081F. environmentally benign chemical plants. These tools, including most 2. M North, P Abrantes, E S Fraga et al. (2015), CO2 reduction prominently the Jacaranda system, use a variety of optimization reactions: general discussion, Faraday Discussions, 10.1039/ methods and specially targeted visualization and interaction procedures C5FD00038 to provide a system which is both powerful and easy to use. 3. F. K Ronaszegi, D J L Brett & E S Fraga (2015), System modelling for hybrid solar hydrogen generation and solar Other activities heating configurations for domestic applications, in Sayigh, A. EPSRC: Member of Peer Review College (Editor), Renewable Energy in the Service of Mankind Vol I, Member of the International Editorial Board for the Journal of Springer, ISBN 978-3-319-17777-9, pages 123-131. Industrial Biotechnology and Biorefineries 4. O Amusat, P Shearing & E S Fraga (2015), Optimal integrated The Information Technology and Control journal energy systems design incorporating variable renewable The Journal of Optimization energy sources, Proceedings of Sustainable Thermal Energy Revista Scientia Alimentaria Management (SusTEM) 2015, 245–253. Member of Programme Committee for META’2016 5. E S Fraga & M Ng (2015), A framework for the analysis of the security of supply of utilising Carbon Dioxide as a chemical Reviewer for feedstock, Faraday Discussions 183:309-326, 10.1039/ A number of journals and funding agencies, covering the interfaces c5fd00038f. (Link) between computer science, mathematics and engineering. 6. C F Triana, E S Fraga & E Sorensen (2015), Energy assessment of different process configurations for the Academic Collaborations production of ethanol from lignocellulosic biomass, Universitat d’Alacant, Spain; University of Edinburgh, UK; University Proceedings of the 12th International Symposium on Process of Essex, UK; University of Leeds, UK. Systems Engineering and 25th European Symposium on Computer Aided Process Engineering, Krist V Gernaey, Jakob Publications K Huusom and Rafiqul Gani (Editors), 2285-2290, ISBN: Journal Articles 978-0-444-63429-0. 1 J Beck, D Friedrich, S Brandani & E S Fraga (2015), Multi- 7. C Wouters, E S Fraga & A James (2015), Techno-economic Objective Optimisation using Surrogate Models for the Design optimisation based approach for design and operation of a of VPSA Systems, Computers & Chemical Engineering residential microgrid with energy export restrictions, 82:318-329, 10.1016/j.compchemeng.2015.07.009. Proceedings of the 12th International Symposium on Process 2. S Brown, E S Fraga, H Mahgerefteh & S Martynov (2015), A Systems Engineering and 25th European Symposium on geometrically based grid refinement technique for multiphase Computer Aided Process Engineering, Krist V Gernaey, Jakob flows, Computers & Chemical Engineering, 10.1016/j. K Huusom and Rafiqul Gani (Editors), 2357-2362, ISBN: compchemeng.2015.05.031. 978-0-444-63429-0. 3. C Wouters, E S Fraga & A James (2015), An energy integrated 8. O Amusat, P Shearing & E S Fraga (2015), System design of multi-microgrid, MILP approach for residential distributed renewable energy generation and storage alternatives for large energy system planning – A South Australian case-study, scale continuous processes, Proceedings of the 12th Energy 85:30-44, 10.1016/j.energy.2015.03.051. International Symposium on 4. A Zilinskas, E S Fraga, J Beck & A Varoneckas (2015), 9. Process Systems Engineering and 25th European Symposium Visualisation of multi-objective decisions for the optimal design on Computer Aided Process Engineering, Krist V Gernaey, of a pressure swing adsorption system, Chemometrics and Jakob K Huusom and Rafiqul Gani (Editors), 2279-2284, Intelligent Laboratory Systems 142:151-158, 10.1016/j. ISBN: 978-0-444-63429-0 chemolab.2015.01.002. 5. E S Fraga, A Salhi, D Zhang & L G Papageorgiou (2015), Optimisation as a tool for gaining insight: An application to the built environment, Journal of Algorithms and Computational Technology 9:13-26. 10.1260/1748-3018.9.1.13 6. A Adam, E S Fraga & D J L Brett (2015), Options for residential building services design using fuel cell based micro-CHP and the potential for heat integration, Applied Energy 138:685-694, 10.1016/j.apenergy.2014.11.005. 56
Other activities Member of the Royal Society of Chemistry (RSC) Member of the peer review college of the Engineering and Physical Sciences Research Council (EPSRC) Member of the International Scientific Advisory Committee of the European Symposium on Applied Thermodynamics (ESAT)
Editorial Activity Journal of Chemical Engineering Data Editorial Advisory Board Molecular Physics Editorial Advisory Board
Industrial Collaborations P&G, Petronas, Pfizer, PSE Ltd., Qatar Petroleum, Shell, Syngenta.
Publications Amparo Galindo Journal Articles 1. Al Ghafri SZS, Forte E, Galindo A, Maitland GC, Trusler JPM, Professor of Physical Chemistry, Department of Chemical 2015, Experimental and Modeling Study of the Phase Engineering, Imperial College London Behavior of (Heptane plus Carbon Dioxide plus Water) Mixtures, JOURNAL OF CHEMICAL AND ENGINEERING Qualifications DATA, Vol: 60, Pages: 3670-3681, ISSN: 0021-9568 PhD in Physical Chemistry, University of Sheffield 2. Burger J, Papaioannou V, Gopinath S, Jackson G, Galindo A, BSc Chemistry, Universidad Complutense de Madrid (Spain) Adjiman C, 2015, A hierarchical method to integrated solvent
and process design of physical CO2 absorption using the Awards and Distinctions SAFT- Mie approach, AICHE JOURNAL, Vol: 61, Pages: Imperial College Research Excellence Award as part of the 3249-3269, ISSN: 0001-1541 Molecular Systems Engineering Team for high academic 3. Cristino AF, Morgado P, Galindo A, Filipe EJM, Palavra AMF, achievement and significant future potential (2009) Nieto de Castro CA, 2015, High-temperature vapour-liquid Imperial College Award for Excellence in Research Supervision for an equilibrium for ethanol-1-propanol mixtures and modeling with exemplary activity in inspiring and supporting research students (2007) SAFT-VR, FLUID PHASE EQUILIBRIA, Vol: 398, Pages: 5-9, Imperial College Award for Excellence in Teaching for outstanding ISSN: 0378-3812 contribution to undergraduate teaching (2007) 4. Dufal S, Lafitte T, Galindo A, Jackson G, Haslam AJ, 2015, ExxonMobil Teaching Fellow (2005-2009), ExxonMobil – Royal Developing intermolecular-potential models for use with the Academy of Engineering, 2005 SAFT-VR Mie equation of state, AICHE JOURNAL, Vol: 61, Pages: 2891-2912, ISSN: 0001-1541 Research Interests 5. Dufal S, Lafitte T, Haslam AJ, Galindo A, Clark GNI, Vega C, My research interests are two-fold: the development of statistical Jackson G, 2015, The A in SAFT: developing the contribution mechanical approaches for complex systems, and their application to of association to the Helmholtz free energy within a Wertheim processes relevant to industry. The tools of statistical mechanics and TPT1 treatment of generic Mie fluids, MOLECULAR PHYSICS, computer simulations offer a privileged molecular perspective of Vol: 113, Pages: 948-984, ISSN: 0026-8976 increasingly complex systems. My interest in this field is to develop 6. Jover J, Galindo A, Jackson G, Müller EA, Haslam AJ, 2015, fundamental approaches to contribute to the understanding of Fluid-fluid coexistence in an athermal colloid-polymer mixture: experimental systems, with a special focus on chemical processes. thermodynamic perturbation theory and continuum molecular- The goal is to be able to predict bulk properties of complex systems. dynamics simulation, MOLECULAR PHYSICS, Vol: 113, We are currently concentrating on the advancement of group Pages: 2608-2628, ISSN: 0026-8976 contribution methodologies targeting specifically solubility prediction 7. Jover JF, Müller EA, Haslam AJ, Galindo A, Jackson G, of organic molecules (usually active pharmaceutical ingredients) and Toulhoat H, Nieto-Draghi C, 2015, Aspects of Asphaltene their use for the development of coarse grained force fields for use in Aggregation Obtained from Coarse-Grained Molecular molecular dynamics simulations. Increasingly the use of quantum Modeling, ENERGY & FUELS, Vol: 29, Pages: 556-566, ISSN: mechanics and statistical mechanics to predict reaction rate 0887-0624 constants and guide solvent design is a major interest. The impact 8. Papadokonstantakis S, Badr S, Hungerbühler K, Papadopoulos and exposure of this work is maximised through collaborative efforts AI, Damartzis T, Seferlis P, Forte E, Chremos A, Galindo A, in which the aim is to promote the transfer of the theoretical Jackson G, Adjiman C, 2015, Toward Sustainable Solvent-Based developments into tools for the design and synthesis of chemical Postcombustion CO2 Capture: From Molecules to Conceptual processes and products. Flowsheet Design, Computer Aided Chemical Engineering, Vol: 36, Pages: 279-310, ISSN: 1570-7946 57
9. Ramrattan NS, Avendano C, Müller EA, Galindo A, 2015, A 20. Siougkrou E, Galindo A, Adjiman CS, 2014, On the optimal corresponding-states framework for the description of the Mie design of gas-expanded liquids based on process family of intermolecular potentials, MOLECULAR PHYSICS, performance, CHEMICAL ENGINEERING SCIENCE, Vol: 115, Vol: 113, Pages: 932-947, ISSN: 0026-8976 Pages: 19-30, ISSN: 0009-2509 10. Adjiman CS, Galindo A, Jackson G, 2014, Molecules Matter: The Expanding Envelope of Process Design, PROCEEDINGS Conference contributions OF THE 8th INTERNATIONAL CONFERENCE ON 1. Diamanti A, Adjiman C, Galindo A, 2014, Systematic study FOUNDATIONS OF COMPUTER-AIDED PROCESS DESIGN, of the accuracy of Conventional Transition State Theory in the Vol: 34, Pages: 55-64, ISSN: 1570-7946 calculations of the kinetics of a gas-phase reaction, 248th 11. Al Ghafri SZS, Forte E, Maitland GC, Rodriguez-Henriquez JJ, National Meeting of the American-Chemical-Society (ACS), Trusler JPM, 2014, Experimental and Modeling Study of the Publisher: AMER CHEMICAL SOC, ISSN: 0065-7727
Phase Behavior of (Methane + CO2 + Water) Mixtures, 2. Jackson G, Galindo A, Adjiman CS, Müller EA, 2014, JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 118, Pages: Employing a SAFT equation of state to obtain force fields 14461-14478, ISSN: 1520-6106 for use in coarse-grained molecular simulations, Pages: 12. Braga C, Galindo A, Müller EA, 2014, Nonequilibrium 1231-1232 molecular dynamics simulation of diffusion at the liquid-liquid interface, JOURNAL OF CHEMICAL PHYSICS, Vol: 141, ISSN: 0021-9606 13. Dufal S, Papaioannou V, Sadeqzadeh M, Pogiatzis T, Chremos A, Adjiman CS, Jackson G, Galindo A, 2014, Prediction of Thermodynamic Properties and Phase Behavior of Fluids and Mixtures with the SAFT-gamma Mie Group-Contribution Equation of State, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 59, Pages: 3272-3288, ISSN: 0021-9568 14. Galindo A, 2014, Foreword: Modeling and Simulation of Real Systems, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 59, Pages: 2927-2927, ISSN: 0021-9568 Galindo A, Masters A, 2014, Thermodynamics 2013 Conference, Manchester, UK, 3-6 September 2013 FOREWORD, MOLECULAR PHYSICS, Vol: 112, Pages: 2199-2202, ISSN: Federico Galvanin 0026-8976 15. Markides CN, Solanki R, Galindo A, 2014, Working fluid Lecturer, Department of Chemical Engineering, University selection for a two-phase thermofluidic oscillator: Effect of College London thermodynamic properties, APPLIED ENERGY, Vol: 124, Pages: 167-185, ISSN: 0306-2619 Qualifications 16. Papadopoulos AI, Badr S, Chremos A, Forte E, Zarogiannis T, BSc in Chemical Engineering, University of Padova Seferlis P, Papadokonstantakis S, Adjiman CS, Galindo A, PhD in Chemical Engineering, University of Padova Jackson G, 2014, Efficient screening and selection of
post-combustion CO2 capture solvents, Chemical Engineering Awards and Distinctions Transactions, Vol: 39, Pages: 211-216, ISSN: 2283-9216 Awarded with the 1st prize in “Process Systems Enterprise Ltd. 17. Papaioannou V, Lafitte T, Avendano C, Adjiman CS, Jackson Model-Based Innovation Prize 2014” for the paper: Galvanin, F., M. G, Müller EA, Galindo A, 2014, Group contribution Barolo, R. Padrini, S. Casonato, F. Bezzo (2014). A model-based methodology based on the statistical associating fluid theory approach to the automatic diagnosis of Von Willebrand disease. for heteronuclear molecules formed from Mie segments, AIChE J., 60, 1718-1727. JOURNAL OF CHEMICAL PHYSICS, Vol: 140, Article number 054107, ISSN: 0021-9606 Research Interests 18. Pereira FE, Galindo A, Jackson G, Adjiman C, 2014, On the Dr Galvanin’s research interests lie at the interface between impact of using volume as an independent variable for the mathematical modelling and experimentation. The research activity solution of P-T fluid-phase equilibrium with equations of state, is particularly focused on the use of advanced computational tools COMPUTERS & CHEMICAL ENGINEERING, Vol: 71, Pages: for the development of predictive models for the characterisation of 67-76, ISSN: 0098-1354 complex systems in both chemistry and physiology. He has a 19. Schreckenberg JMA, Dufal S, Haslam AJ, Adjiman CS, specific expertise in the following areas: Jackson G, Galindo A, 2014, Modelling of the thermodynamic • Design of Experiments (DoE) and statistical planning and solvation properties of electrolyte solutions with the • Model-based Design of Experiments (MBDoE) for model statistical associating fluid theory for potentials of variable identification range, MOLECULAR PHYSICS, Vol: 112, Pages: 2339-2364, • Kinetic modelling, chemical reactor modelling ISSN: 0026-8976 • Pharmacokinetics/pharmacodynamics modeling 58
• Modeling of physiological systems doi:10.1016/j.jfoodeng.2013.07.027 • Parameter Estimation Conference Contributions The current research activity is primarily focused on the optimal 1. Galvanin, F., Cao, E., Al-Rifai, N., Dua, V. & Gavriilidis, A. design of experiments for i) the identification of kinetic models (2015). A model-based design of experiments approach for in flow reactors; ii) the development of pharmacokinetic the identification of kinetic models of methanol oxidation on models for the detailed study of physiological systems silver catalyst. In: UK Catalysis Conference 2015. (diabetes and rare coagulation diseases). Loughborough (UK). 2. De Luca, R., Galvanin, F., & Bezzo, F. (2015). A framework for Teaching Interests a direct exploitation of available information in the online Teaching activities are in the areas of process design and simulation model-based redesign of experiments. In M. O. Bertran, T. of chemical processes. Below are the modules he is currently Bisgaard, & F. Frauzem (Eds.), 25th European Symposium on teaching: Computer Aided Process Engineering Vol. Book of Abstracts • CENGM01P/CENGG01P Process Systems Modelling and (pp. 30-31). Copenhagen. Design 3. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. • CENG207P Process Design Principles (2015). A model-based experimental design study for the development of kinetic models of methanol oxidation on silver He is the Deputy Departmental Admissions Tutor at UCL Chemical catalyst. Proceedings of CAPE Forum 2015, 87-93. Engineering. Paderborn, Germany. 4. Galvanin, F., Cao, E., Al-Rifai, N., Gavriilidis, A., & Dua, V. Reviewer for (2015). Model-based design of experiments for the Industrial & Engineering Chemistry & Research, Chemical identification of kinetic models in microreactor platforms. Engineering Science, Journal of Process Control, International Amsterdam (The Netherlands): Elsevier. Journal of Adaptive Control and Signal Processing, Modelling and 5. Galvanin, F., Monte, A., Casonato, A., Padrini, R., Barolo, M., Biological Engineering and Computing. & Bezzo, F. (2014). Towards Model-Based Diagnosis of von Willebrand Disease. In P. S. V. Jiří Jaromír Klemeš, P. Y. Liew Academic Collaborations (Eds.), 24th European Symposium on Computer Aided Process University of Padova on the project: “Optimal design of experiments Engineering (p. 583 – 588). Elsevier. doi:10.1016/B978-0-444- for the identification of physiological models of Von Willebrand 63456-6.50098-3 Diseased” Cardiff Catalysis Institute, Liverpool University, UCL Chemical Engineering (Catalysis Hub) on the project: “Merging information from batch and continuous flow experiments for the identification of kinetic models of benzyl alcohol oxidation”
Industrial Collaborations Collaboration with Syngenta (Bracknell, UK) on the MSc project: “Bringing plant potential to life through optimisation of traveling traders’ exchanges”.
Publications Journal Articles 1. Galvanin, F., Cao, E., Al-Rifai, N., Dua, V., & Gavriilidis, A. (2015). Optimal design of experiments for the identification of kinetic models of methanol oxidation over silver catalyst. Chimica Oggi/Chemistry Today, 33 (3), 51-56. Gonzalo Guillén Gosálbez 2. Galvanin, F., Barolo, M., Padrini, R., Casonato, A., & Bezzo, F. Reader in Process Systems Engineering, Department of (2014). A model-based approach to the automatic diagnosis Chemical Engineering, Imperial College London of von Willebrand disease. AIChE Journal, 60 (5), 1718-1727. doi:10.1002/aic.14373 Qualifications 3. Bernardi, A., Perin, G., Sforza, E., Galvanin, F., Morosinotto, MEng in Chemical Engineering (Top Student Award, Universidad de T., & Bezzo, F. (2014). An Identifiable State Model To Describe Murcia, Murcia, Spain) Light Intensity Influence on Microalgae Growth. Industrial & PhD in Process Systems Engineering (Top Student Award, UPC, Engineering Chemistry Research, 53 (16), 6738–6749. Barcelona, Spain) doi:10.1021/ie500523z 4. Galvanin, F., De Luca, R., Ferrentino, G., Barolo, M., Awards and Distinctions Spilimbergo, S., & Bezzo, F. (2014). Bacterial inactivation on Outstanding Young Investigator Award “Juan López de Peñalver” solid food matrices through supercritical CO2: A correlative (Spanish Royal Academy of Engineering), Oct-2012 study. Journal of Food Engineering, 120, 146-157. Erasmus Staff Mobility for Training (ETH Zürich), June-2012 59
Fulbright Postdoctoral Fellowship (Carnegie Mellon University), Industrial Collaborations Oct-2006 Messer Ibérica de Gases; REPSOL; ExxonMobil Research and Top Doctoral Student Award (UPC), Dec-2005 Engineering Company. FPU Pre-doctoral Scholarship (Spanish Ministry of Education and Science-UPC), Jan-2002-Jan-2006 Publications Top Student Award in Chemical Engineering (Spanish Ministry of Book Chapters Education-UMU), Jun-2001 1. Guillén-Gosálbez, G., You, F. Plant Location: Supply Chain Management. Introduction to Software for Chemical Research Interests Engineers, CRC Press, 2015. Dr. Guillén-Gosálbez’s research interests lie at the interface of 2. Reyes-Labarta, J.A., Salcedo-Díaz, R., Ruiz-Femenia, R., engineering, environmental sciences and computer aided systems Guillén-Gosálbez, G., Caballero, J.A. Handling of uncertainty design. Areas of particular interest include: Sustainable engineering, in life cycle inventory by correlated multivariate lognormal Multi-objective optimisation of sustainable processes, Life cycle distributions: Application to the design of supply chain assessment, Eco-efficiency assessment and optimisation, networks. Computer Aided Chemical Engineering, vol. 33, Stochastic programming and multi-criteria decision-making 1075-1080, 2014, Pergamon-Elsevier Science ltd (UK), ISSN: under uncertainty. 15707946. 3. Vaskan, P., Guillén-Gosálbez, G., Sorribas, A., Alves, R., Reviewer for Jiménez, L.Multi-level optimization framework applied to the Member of the Editorial Board of The Scientific World Journal. systematic evaluation of metabolic objective functions. Computer Aided Chemical Engineering, vol. 33, 961-966, Referee for a number of journals 2014, Pergamon-Elsevier Science ltd (UK), ISSN: 15707946. AIChE Journal; Asia-Pacific Journal of Chemical Engineering; Computers & Chemical Engineering; Desalination; Environmental Journal Articles (“*” stands for corresponding author) Science & Technology; Industrial & Engineering Chemistry Research; 1. Rojas-Torres, G., Nápoles-Rivera, F., Ponce-Ortega, J.M., International Journal of Hydrogen Energy; International Journal of Serna-González, M., Guillén-Gosálbez, G., Jiménez-Esteller, J. Information Technology & Decision Making; Journal of Cleaner Multiobjective optimization for designing and operating more Production; Journal of Environmental Management; Optimization sustainable water management systems for a city in Mexico. and Engineering. AIChE Journal, 61(8), 2428-2446, 2015. 2. Cortés-Borda, D., Guillén-Gosálbez, G.*, Jiménez, L. Reviewer for international funding bodies Assessment of nuclear energy embodied in international trade Spanish Ministry of Science and Innovation (Spain); CONICET following a world multi-regional input-output approach. (Argentina); Fonds National de la Recherche (Luxemburg); National Energy, 91, 91-101, 2015. Agency for the Evaluation of Universities and Research Institutes 3. Galán-Martín, A., Pozo, C., Guillén-Gosálbez, G.*, Vallejo, A., (ANVUR) (Italy); Qatar National Research Fund (Qatar). Esteller, L. Multi-stage linear programming model for optimizing cropping plan decisions under the new Common Academic Collaborations (leading to joint publications) Agricultural Policy. Land Use Policy, 48, 515-524, 2015. Carnegie Mellon University (Pittsburgh, US): Prof. Ignacio E. 4. Pascual-González, J., Pozo, C., Guillén-Gosálbez, G.*, Grossmann, Global Optimization. Jiménez-Esteller, L. Combined use of MILP and multi-linear ETH Zürich (Switzerland): Prof. Stefanie Hellweg, Life Cycle regression to simplify LCA studies. Computers & Chemical Assessment. Engineering, 82, 34-43, 2015. Polytechnic University of Catalonia (Barcelona, Spain): Prof. 5. Cortés-Borda, D., Guillén-Gosálbez, G.*, Jiménez, L. Solar Christian Blum, Hybrid Meta-heuristics. energy embodied in international trade of goods and services: The University of Manchester (UK): Prof. Adisa Azapagic, A multi-regional input-output approach. Energy, 82, 578-588, Sustainable Industrial Systems. 2015. Universidad de Alicante (Alicante, Spain): Prof. José Caballero, 6. Pascual-González, J., Guillén-Gosálbez, G.*, Mateo-Sanz, Simulation-Optimisation for Process Synthesis. J.M., Jiménez-Esteller, L. Statistical analysis of global Universidad de Santander (Santander, Spain): Prof. Ángel Irabien, environmental impact patterns using a world multi-regional Design of Energy Systems. input-output database. Journal of Cleaner Production, 90, Universidad Michoacana de San Nicolás de Hidalgo (Mexico): Prof. 360-369, 2015. Ponce-Ortega,Sustainable Supply Chains. 7. Pozo, C., Miró, A., Guillén-Gosálbez, G.*, Sorribas, A., Alves, Universidad Nacional de Tucumán (San Miguel de Tucumán, R., Jiménez, L. Gobal optimization of hybrid kinetic/FBA Argentina): Prof. Fernando Daniel Mele, Biofuels Supply Chains. models via outer-approximation. Computers & Chemical Universitat de Lleida (Spain): Prof. Albert Sorribas, Systems Biology. Engineering, 72, 325-333, 2015. University of Oklahoma (Norman, US): Prof. Miguel Bagajewicz, 8. Carreras, J., Boer, D., Guillén-Gosálbez, G., Cabeza, L.F., Optimization under Uncertainty. Medrano, M., Jiménez, L. Multi-objective optimization of thermal modelled cubicles considering the total cost and life cycle environmental impact. Energy and Buildings, 88, 335-346, 2015. 60
9. Antipova, E., Pozo, C., Guillén-Gosálbez, G.*, Boer, D., sludge amendment. Industrial & Engineering Chemistry Cabeza, L.F., Jiménez, L. On the use of filters to facilitate the Research, 52 (49), 17640-17647, 2014. post-optimal analysis of the Pareto solutions in multi-objective 22. Brunet, R., Guillén-Gosálbez, G.*, Jiménez, L. Combined optimization. Computers & Chemical Engineering, 74(4), simulation-optimization methodology to reduce the 48-58, 2015. environmental impact of pharmaceutical processes: 10. Cortés-Borda, D., Ruiz-Hernández, A., Guillén-Gosálbez, G.*, Application to the production of Penicillin v. Journal of Cleaner Llop, M., Guimerà, R., Sales-Pardo, M. Identifying strategies Production, 76(1), 55-63, 2014. for mitigating the global warming impact of the EU-25 economy using a multi-objective input-output approach. Conference Contributions Energy Policy, 77 (21-30), 2015. 1. Carreras, J., Boer, D., Jiménez, Guillén-Gosálbez, G. 11. Kostin, A., Guillén-Gosálbez, G.*, Jiménez, L. Dimensionality Combined Use of Dimensionality Reduction and Surrogate reduction applied to the simultaneous optimization of the Modelling for the Multi-Objective Optimization of Buildings. economic and life cycle environmental performance of supply AIChE Annual Meeting, Salt Lake City, US, November 2015. chains. Journal of Production Economics, 159, 223-232, 2. Ewertowska, A., Galán, A., Jiménez, L., Gavaldá, J., Guillén- 2015. Gosálbez, G. Assessment of the Environmental Efficiency of 12. Brunet, R., Boer, D., Guillén-Gosálbez, G.*, Jiménez, L. the Electricity Mix of the Top European Economies Via Data Reducing the cost, environmental impact and energy Envelopment Analysis. AIChE Annual Meeting, Salt Lake City, consumption of biofuel processes through heat integration. US, November 2015. Chemical Engineering Research and Design, 93, 203-212, 3. Galán, A., Jiménez, L., Guillén-Gosálbez, G. Multi-Objective 2015. Optimization Applied to Sustainable Rain-Fed and Irrigated 13. Vaskan, P., Guillén-Gosálbez, G.*, Turkay, M., Jiménez, L. Crop Production: A Case Study of Wheat Production in Spain. Multiobjective optimization of utility plants under several AIChE Annual Meeting. Salt Lake City, US, November 2015. environmental indicators using an MILP-based dimensionality 4. Cortés, D., Jiménez, L., Guillén-Gosálbez, G. Multi-Objective reduction approach. Industrial & Engineering Chemistry Optimization Combined with Input-Output and Eco-Cost Research, 53(50), 19559-19572, 2014. Assessment for Decarbonizing the European Economy. AIChE 14. Copado-Méndez, P.J., Guillén-Gosálbez, G.*, Jiménez, L. Annual Meeting. Salt Lake City, US, November 2015. MILP-based decomposition algorithm for dimensionality 5. Tulus, V., Boer, D., Jiménez, L. Guillén-Gosálbez, G. reduction in multi-objective optimization: Application to Optimization of Thermal Energy Supply By Central Solar environmental and systems biology problems Computers & Heating Plants with Seasonal Storage. AIChE Annual Meeting. Chemical Engineering, 67, 137-147, 2014. Salt Lake City, US, November 2015. 15. Vadenbo, C., Hellweg, S., Guillén-Gosálbez, G. Multi-objective 6. Dauda, I., Jobson, M., Guillén-Gosálbez, G. Combined with optimization of waste and resource management in industrial the Analytic Hierarchy Process for the Design of Chemical networks – Part I: Model description. Resources, Conservation Processes Under Uncertainty: Application to the Synthesis of and Recycling, 89, 41-51, 2014. Heat Exchanger Networks. AIChE Annual Meeting. Salt Lake 16. Antipova, E., Boer, D., Guillén-Gosálbez, G., Cabeza, L.F., City, US, November 2015. Jiménez, L. Multi-objective optimization coupled with life cycle 7. Copado-Méndez, P., Guillén-Gosálbez, G., Jiménez-Esteller, assessment for retrofitting buildings. Energy and Buildings, 82, L. Systematic framework for reducing the number of 92-99, 2014. objectives in multi-objective optimization: Application to the 17. Vadenbo, C., Guillén-Gosálbez, G., Saner, D., Hellweg, S. design of environmentally conscious supply chains. 17th Multi-objective optimization of waste and resource British-French-German Conference on Optimization, London, management in industrial networks – Part II: Model application UK, June 2015. to the treatment of sewage sludge. Resources, Conservation 8. Guillén-Gosálbez, G., Ruíz-Femenia, Caballero, J.A., Jiménez, and Recycling, 89, 52-63, 2014. L. Identifying the Preferred Subset of Alternatives for 18. Sabio, N., Pozo, C., Guillén-Gosálbez, G.*, Jiménez, L., Environmental Improvements Via an MILP Approach Based on Karuppiah, R., Vasudevan, V., Sawaya, N., Farrell, J.T. the Analytic Hierarchy Process. Atalanta, US, November 2014. Multi-objective optimization under uncertainty of the economic 9. Pascual, J., Guillén-Gosálbez, G., Jiménez, L., Mateo-Sanz. and life cycle environmental performance of industrial Statistical Analysis of Global Environmental Impact Patterns processes. AIChE Journal, 60 (6), 2098-2121, 2014. Using a World Multi-Regional Input Output Database. AIChE 19. Brunet, R., Guillén-Gosálbez, G. *, Jiménez, L. Minimization of Annual Meeting. Atalanta, US, November 2014. the nonrenewable energy consumption in bioethanol production processes using a solar-assisted steam generation Invited Lectures and Seminars system. AIChE Journal, 60 (2), 500-506, 2014. 1. Benchmark analysis of a top British University in Chemical 20. Corsano, G., Guillén-Gosálbez, G.*, Montagna, J.M. Solution Engineering, Universitat Rovira i Virgili (Tarragona, Spain), strategies for the design and planning of supply chains and January 2015. embedded plants. Computers & Chemical Engineering, 60, 2. Multi-objective optimisation coupled with life cycle assessment 154-171, 2014. for the development of sustainable processes, Luxembourg 21. Vaskan, P., Guillén-Gosálbez, G.*, Jiménez, L. Decomposition Institute of Science and Technology (LIST) (Luxembourg City, algorithm for GIS-based MILPmodels: Application to sewage Luxembourg), January 2015. 61
3. Systematic tools based on mathematical programming for the Member, Energy Institute life cycle optimisation of sustainable processes, BASF Chartered Engineer, Engineering Council UK (Ludwigshafen, Germany), June 2015. Systematic optimisation tools applied to sustainable engineering, Joint Research Reviewer for Centre in Ispra (Ispra, Italy), May 2015. Energy, Applied Energy, Applied Thermal Engineering, Nature 4. Teaching Design Project at The University of Manchester Climate Change, Energy Policy (Reading, UK), December 2014. 5. Systematic multi-criteria decision-making tools for the design Academic Collaborations and planning of more sustainable processes, Northwestern Collaborator, IEA ECBCS Annex 54 on Residential Microgeneration University (Evanston, US), May 2014. Collaborator, IEA Annex 42 on Residential Cogeneration Researcher, UKERC Microgeneration Theme
Industrial Collaborations Ceres Power Ltd, Techno Economic Modelling of Solid Oxide Fuel Cells EDF, Techno Economic Modelling of Micro‐CHP Systems
Publications Reports 1. Gross R, Speirs J, Hawkes AD, Skillings S, Heptonstall P, 2014, Could retaining old coal lead to a policy own goal? 2. McDowall W, Francis L, Staffell I, Grünewald P, Kansara T, Ekins P, Dodds P, Hawkes AD, Agnolucci Petal., 2014, The role of fuel cells and hydrogen in providing affordable, secure and low carbon heat, London, UK Adam Hawkes Journal Articles 1. Dodds PE, Staffell L, Hawkes AD, Li F, Grunewald P, McDowall Senior Lecturer in Energy Systems, Department of Chemical W, Ekins P, 2015, Hydrogen and fuel cell technologies for Engineering, Imperial College London heating: A review,INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, Vol:40, Pages: 2065‐2083, ISSN: 0360‐3199 Qualifications 2. Xie C, Hawkes AD, 2015, Estimation of inter‐fuel substitution PhD in Energy Systems Modelling possibilities in China’s transport industryusing ridge regression, B.Eng (Hons) ENERGY, Vol: 88, Pages: 260‐267, ISSN: 0360‐5442
3. Hawkes AD, 2014, Long‐run marginal CO2 emissions factors Awards and Distinctions in national electricity systems, APPLIED ENERGY, Vol: 125, Baker Medal, Institution of Civil Engineers, 2011 Pages: 197‐205, ISSN: 0306‐2619 4. Kelly NJ, Tuohy PG, Hawkes AD, 2014, Performance Research Interests assessment of tariff‐based air source heat pumpload shifting Adam’s areas of research interest fall into five categories: in a UK detached dwelling featuring phase change‐enhanced 1. Economy‐wide energy systems modelling buffering, APPLIED THERMAL ENGINEERING, Vol: 71, Pages: 2. Technologies and pathways for low-carbon heat 809‐820, ISSN: 1359‐4311 3. Design and operation of microgrids and more integrated/ 5. Pfenninger S, Hawkes A, Keirstead J, 2014, Energy systems coordinated energy systems modeling for twenty‐first century energy challenges, 4. Fuel cells, polygeneration, and other cutting‐edge energy RENEWABLE & SUSTAINABLE ENERGY REVIEWS, Vol: 33, conversion technologies Pages: 74‐86, ISSN: 1364‐0321 5. Residential energy supply and demand, with a focus on microgeneration Conference Contributions In the field of energy systems modelling, Adam’s research seeks to 1. Hawkes AD, 2014, The taxonomy of energy systems bridge the gap between siloed energy technology assessment and modelling, Energy Systems Conference the role of those technologies in integrated energy systems. 2. Philbin SP, Jones D, Brandon NP, Hawkes AD, 2014, Multi-scale modelling is applied to reflect the critical design and Exploring Research Institutes: Structures,Functioning and operational parameters of energy technologies and infrastructures Typology, Portland International Conference on Management into the energy system as a whole, providing engineers and policy of Engineering & Technology (PICMET), Publisher: IEEE, makers with insight into the value of particular technology Pages: 2569‐2582, ISSN: 2159‐5100 characteristics, and aiding prioritisation of technology R&D. 3. Pinheiro L, Napp T, Hawkes AD, 2014, Can Brazil fulfil long term reduction targets? An evaluation of consequences of delayed Other Activities action on its energy sector, 9th Conference on Sustainable Member, European Council for an Energy Efficient Economy Development of Energy, Water and Environmental Systems (ECEEE), 2013–2015 62
Other Activities 1. 1991‐1996, Member of the Executive Committee of the Statistical Mechanics and Thermodynamics Group (SMTG) of the Faraday Division of the Royal Society of Chemistry 2. 1992‐1998, Founder member of the Centre for Molecular Materials, Sheffield University 3. 1993‐1996, Member of the Executive Committee of the Collaborative Computational Project 5 (CCP5) 4. 1994‐1998, Editor of Molecular Physics 5. 1995‐date, Fellow of the Royal Society of Chemistry, Chartered Chemist (FRSC, CChem) 6. 1997‐2000, Member of Chemistry Programme (Structure and Bonding College) of the EPSRC 7. 1998‐2013, Member of Executive Committee and Special George Jackson Issue Editor of Molecular Physics 8. 1998‐2002, Member of Editorial Board of Molecular Professor of Chemical Physics, Department of Chemical Simulation Engineering, Imperial College London 9. 2000‐date, Member of Editorial Board of Fluid Phase Equilibria 10. 2000‐2007, Member of Peer Review College of the EPSRC Qualifications 11. 2001‐date, Fellow of the Mexican Academy of Molecular DPhil in Physical Chemistry, Exeter College, University of Oxford Engineering BSc Chemistry, Chelsea College, University of London 12. 2003‐date, Member of the Centre for Process Systems Engineering Awards and Distinctions 13. 2003‐2009, Chairman of the Statistical Mechanics and Guggenheim Medal for Excellence in Thermodynamics, Institution of Thermodynamics Group (SMTG) of the Faraday Division of the Chemical Engineers (IChemE, 2015) Royal Society of Chemistry Fellow of the Mexican Academy of Molecular Engineering (2001) 14. 2006‐2011, Council Member of the Faraday Division of the Fellow of the Royal Society of Chemistry (FRSC), Chartered Chemist Royal Society of Chemistry (CChem, 1995) 15. 2006‐2011, Member of the Faraday Standing Committee on Conferences Research Interests 16. 2006‐2013, Member of Management Committee of the A molecular description of matter is the key to understanding and Liquids and Complex Fluids Group of the Institute of Physics predicting the properties of dense fluids and materials. The latest 17. 2007‐2008, Member of Appointments Committee of the developments in statistical-mechanical theories and computer Department of Physics, University of Bergen, Norway simulation (Monte Carlo and molecular dynamics) are used by my 18. 2007‐date, External Examiner, Physical Chemistry, Univ. of group to provide a reliable predictive platform for complex fluids and West Indies (Barbados, Jamaica, Trinidad and Tobago) ordered materials at the molecular level. The focus is on the 19. 2007‐2013, UK Representative to European Federation of phase equilibria of systems which are of industrial relevance, e.g., Chemical Engineering (EFCE), Thermodynamics/Transport mixtures containing hydrogen fluoride (production of refrigerants), 20. 2008‐2011, Honorary Secretary and Treasurer of Faraday aqueous solutions of surfactants (enhanced oil recovery), and Council of the Royal Society of Chemistry hydrogen-bonded liquid crystals (optical devices).
Reviewer for One of our main achievements has been the development of a AIChE Journal, Chemical Physics Letters, Fluid Phase Equilibria, highly accurate equation of state for the thermodynamic properties Industrial and Engineering Chemistry Research, Journal of the of complex fluid mixtures: the statistical associating fluid theory for American Chemical Society, Journal of Chemical Physics, Journal of potentials of variable range SAFT‐VR. We are currently embarking Physical Chemistry, Journal of Physics: Condensed Matter, on extensions of the formalism to polymers, electrolytes, and Macromolecules, Molecular Physics, Molecular Simulation, Nature, inhomogeneous systems. A recent advance is the formation of the Physical Chemistry, Chemical Physics, Physical Review Letters, Molecular Systems Engineering (MSE) Group in which we are Physical Review E. incorporating advanced thermodynamics modelling in process design and optimisation.
Industrial Collaborations In the area of liquid-crystal modelling, the aim is a fundamental BASF, BCURA, Power Ltd, Borealis AS, Britest Ltd., BP, ICI understanding of the effect of association, polar interactions and Research/Akzonobel, Ineos fluor/Mexichem, P&G, Pfizer, Novartis, molecular flexibility on the stability of liquid-crystalline phases Qatar Petroleum, Shell International, Schlumberger Syngenta, Total, (nematic, biaxial, smectic, etc.). We are currently simulating Unilever Research. molecules which incorporate molecular flexibility and dipolar interactions as well as chiral centres. 63
Publications 15. S Dufal, V Papaioannou, M Sadeqzadeh, T Pogiatzis, A Journal Articles Chremos, et al. 2014, Prediction of thermodynamic properties 1. GV Lau, PA Hunt, EA Müller, G Jackson, IJ Ford, 2015, Water and phase behavior of fluids and mixtures with the SAFT‐γ Mie droplet excess free energy determined by cluster mitosis using groupcontribution equation of state, Journal of Chemical & guided molecular dynamics, Journal of Chemical Physics 143, Engineering Data 59, 3272‐3288 244709 16. EA Müller, G Jackson, 2014, Force field parameters from the 2. B Rotenberg, G Jackson, D Frenkel, 2015, Jean‐Pierre SAFT‐γ equation of state for use in coarsegrained molecular Hansen – a stimulating history of simulating fluids, Molecular simulations, Annual Review of Chemical and Biomolecular Physics 113, 2363‐2375 Engineering 5, 405‐427 3. J Jover, A Galindo, G Jackson, EA Müller, AJ Haslam, 2015, 17. L Wu, EA Müller, G Jackson, 2014, Understanding and Fluid–fluid coexistence in an athermal colloid–polymer mixture: describing the liquid‐crystalline states of polypeptide solutions: thermodynamic perturbation theory and continuum molecular‐ A coarse‐grained model of PBLG in DMF, Macromolecules 47, dynamics simulation, Molecular Physics 113, 2608‐2628 1482‐1493 4. L Wu, A Malijevský, G Jackson, EA Müller, C Avendaño, 2015, 18. V Papaioannou, T Lafitte, C Avendaño, CS Adjiman, G Orientational ordering and phase behaviour of binary mixtures Jackson, et al. 2014, Group contribution methodology based of hard spheres and hard spherocylinders, Journal of on the statistical associating fluid theory for heteronuclear Chemical Physics 143, 044906 molecules formed from Mie segments, Journal of Chemical 5. S Dufal, T Lafitte, AJ Haslam, A Galindo, GNI Clark, C Vega, G Physics 140, 054107 Jackson, 2015, The A in SAFT: developing the contribution of 19. L Lu, S Wang, EA Müller, W Cao, Y Zhu, X Lu, G Jackson,
association to the Helmholtz free energy within a Wertheim 2014, Adsorption and separation of CO2+CH4 mixtures using TPT1 treatment of generic Mie fluids, Molecular Physics 113, nanoporous adsorbents by molecular simulation, Fluid Phase 948‐984 Equilibria 362, 227‐234 6. J Burger, V Papaioannou, S Gopinath, G Jackson, A Galindo, 20. AI Papadopoulos, S Badr, A Chremos, E Forte, T Zarogiannis, CS Adjiman, 2015, A hierarchical method to integrated solvent P Seferlis, et al. 2014, Efficient screening and selection of
and process design of physical CO2 absorption using the post‐combustion CO2 capture solvents, Chemical Engineering SAFT‐γ Mie approach, AIChE Journal 61, 3249‐3269 Transactions 39, 211‐216 7. GV Lau, IJ Ford, PA Hunt, EA Müller, G Jackson, 2015, 21. CS Adjiman, A Galindo, G Jackson, 2014, Molecules matter: Surface thermodynamics of planar, cylindrical, and spherical The expanding envelope of process design, Computer Aided vapour‐liquid interfaces of water, Journal of Chemical Physics Chemical Engineering 34, 55 142, 114701 22. E Forte, AJ Haslam, G Jackson, EA Müller, 2014, Effective 8. Lobanova, C Avendaño, T Lafitte, EA Müller, G Jackson, coarse‐grained solid–fluid potentials and their application to 2015, SAFT‐γ force field for the simulation of molecular fluids: model adsorption of fluids on heterogeneous surfaces, 4. A single‐site coarse‐grained model of water applicable over Physical Chemistry Chemical Physics 16, 19165‐19180 a wide temperature range, Molecular Physics 113, 1228‐1249 9. S Dufal, T Lafitte, A Galindo, G Jackson, AJ Haslam, 2015, Keynote/plenary talks given at international conferences Developing intermolecular‐potential models for use with the 1. 2014 “Computing the Pressure and Interfacial Tension of SAFT‐VR Mie Equation of State, AIChE Journal 61, Inhomogenenous Nanoscopic Systems Including Drops and 2891‐2912 Confined Anisotropic Phases: The Devil Is in the Detail,” 10. JF Jover, EA Müller, AJ Haslam, A Galindo, G Jackson, H Annual AIChE Meeting, Atlanta, USA. Toulhoat, et al. 2015, Aspects of asphaltene aggregation 2. 2015 “Coarse Grained Modelling of the Phase Behaviour of obtained from coarse‐grained molecular modelling, Energy & Non‐Ionic Surfactants,.” British Liquid Crystal Conference, Fuels 29, 556–566 Sheffeild. 11. G Jackson, GV Lau, EA Müller, PA Hunt, IJ Ford, 2015, Water 3. 2015 “SAFT‐γ force fields for molecular simulations of the droplet excess free energy determined by cluster mitosis using thermodynamic, structural and transport properties of guided molecular dynamics, American Institute of Physics (AIP) complex fluids and mixtures,” SAFT 25th Anniversary 12. FE Pereira, A Galindo, G Jackson, CS Adjiman, 2014, On the Conference, Houston, USA. impact of using volume as an independent variable for the 4. 2015 “Guggenheim Medal Award: The legacy of Edward solution of P‐T fluid‐phase equilibrium with equations of state, Guggenheim to Statistical Thermodynamics,” Computers & Chemical Engineering 71, 67‐76 Thermodynamics 2015 Conference, Copenhagen, Denmark 13. F Coletti, BD Crittenden, AJ Haslam, GF Hewitt, G Jackson, et al. 2014, Modeling of fouling from molecular to plant scale, Elsevier Inc. 14. JMA Schreckenberg, S Dufal, AJ Haslam, CS Adjiman, G Jackson, et al. 2014, Modelling of the thermodynamic and solvation properties of electrolyte solutions with the statistical associating fluid theory for potentials of variable range, Molecular Physics 112, 2339‐2364 64
Urban Systems, Journal of Urban Technology, International Journal of Sustainable Transportation, Climatic Change, Urban Design and Planning, Environmental Science & Technology, IET Renewable Power Generation, Environment and Planning B, Ecological Modelling, Environmental Research Letters, and others.
Academic Collaborations University of Toronto, Prof. Chris Kennedy University of Minnesota, Prof. Anu Ramaswami Arizona State University, Dr. Mikhail Chester University of Surrey, Prof. Roland Clift University of Bath, Dr Nick McCullen
Industrial Collaborations James Keirstead Arup, AECOM, Hildebrand Ltd
Lecturer in Urban Energy Systems, Department of Civil and Environmental Engineering, Imperial College London
Qualifications BSc in Civil Engineering (First Class Honours, Queen’s University, Canada), MSc Environmental Change and Management (Distinction, University of Oxford) DPhil (University of Oxford).
Awards and Distinctions Chartered Engineer, Member of the Energy Institute Commonwealth Scholar, 2003-2006 British Council Chevening Scholar, 2001-2002 Guinness Book of World Records, 2000, Longest Distance Travelled by Solar Powered Vehicle Alexandros Kiparissides
Lecturer in the Department of Biochemical Engineering, Secondments University College London October 2010, University of Tokyo, Institute for Industrial Science.
Qualifications Research Interests Diploma in Chemical Engineering (Aristotle University of 1. Urban energy systems including systems integration, Thessaloniki, Greece) technologies, and policies PhD in Bioprocess Systems Engineering (Imperial College London, UK) 2. Optimisation methods, agent-based simulation, uncertainty/ sensitivity analysis Research Interests 3. Industrial ecology, particularly urban metabolism Recombinant protein production in mammalian cell cultures, algae biotechnology and bioprocessing. Development of an integrated Other Activities methodology combining Multi‐scale & Metabolic Modelling, Elected board member, Sustainable Urban Systems section, Metabolic Engineering and wet‐lab experiments in order to: (i) Better International Society for Industrial Ecology Technical committee understand cell physiology and metabolism under industrial member, ISIE and ATES conferences, proposal peer review for bioprocessing conditions; (ii) Identify key parameters affecting EPSRC, ESRC, US National Science Foundation, Natural Sciences culture efficiency at the metabolic, bioprocess and reactor design and Engineering and Social Sciences and Humanities Research level; (iii) Enable the model based design and optimisation of Councils of Canada. industrial scale bioreactors.
Reviewer Activities Other Activities Energy Policy, Proceedings of the National Academy of Sciences, Member of the SIG: Biochemical Engineering – IChemE Building Research and Information, Technological Forecasting and MSc Admissions Tutor – Department of Biochemical Engineering, UCL Social Change, Energy, Energy Economics, Journal of Artificial Societies and Social Simulation, Energy Efficiency, The Energy Journal, Journal of Industrial Ecology, Computers, Environment and 65
Reviewer for Biochemical Engineering Journal BMC Bioinformatics Chemical Engineering Research and Design Computers & Chemical Engineering Algal Research, Technology Biomass & Bioenergy
Academic Collaborations Imperial College London (UK), University College Dublin (IRL), University of Surrey (UK), Tufts University (USA), École Polytechnique Fédérale de Lausanne ‐ EPFL (CH), Austrian Centre of Industrial Biotechnology (AUT), Cyprus University of Technology (CY), Centre for Research and Technology Hellas (GR). Cleo Kontoravdi Industrial Collaborations Lonza Biologics Senior Lecturer, Department of Chemical Engineering, Medimmune Imperial College London
Publications Qualifications Journal Articles PhD in Chemical Engineering, Imperial College London 1. Kiparissides A., Pistikopoulos E.N., Mantalaris A., Georgakis MEng in Chemical Engineering, Imperial College London C. (2014). In‐Silico Design of Experiments as a Tool for Nonlinear Sensitivity Analysis of Detailed Models. Ind. Eng. Research Interests Chem. Res., v.53(18), pp: 7517–7525 Mathematical modelling, experiment design and optimisation for 2. Kiparissides A., Pistikopoulos E.N., Mantalaris A. (2015). On biological processes the Model Based Optimisation of Monoclonal Antibody Protein‐producing animal cell cultures Production in GS‐NS0 Cell Cultures. Biotechnology & Protein glycosylation Bioengineering, v.112(3), pp: 536‐548 3. Kiparissides A., Hatzimanikatis V. (2015). Thermodynamics‐ Industrial Collaborations based Metabolite Sensitivity Analysis in Metabolic Networks. Lonza Biologics Metabolic Engineering, Under Revision MedImmune GSK Conference Presentations and Posters Symphogen 1. Vieira Pinto J., Kiparissides A., Hatzimanikatis V. (2014). “Characterization of intracellular metabolic states presenting Reviewer for the Warburg phenotype”, COBRA 2014 ‐ 3rd Conference on Biotechnology Progress Constraint‐Based Reconstruction and Analysis, Charlottesville Biotechnology and Bioengineering (VA), USA. Analytical Biochemistry 2. Kiparissides A., Hatzimanikatis V. (2014). “Deciphering Biochemical Engineering Journal thermodynamics in metabolic networks: A priority list of PLoS ONE candidates for metabolomics”, Metabolic Engineering X, Cytotechnology Vancouver (BC), Canada. Biotechnology and Applied Biochemistry 3. Kiparissides A., Hatzimanikatis V. (2015). “Reducing Bioprocess and Biosystems Engineering uncertainty in metabolic networks through thermodynamics Chemical Engineering Science based flux analysis”, 5th ICBE—International Conference on Computer Applications in Biotechnology Biomolecular Engineering, Austin (TX), USA. Biochemical Engineering Journal
Publications Journal Articles 1. Sou SN, Sellick C, Lee K, Mason A, Kyriakopoulos S, Polizzi KM, Kontoravdi C, 2015, How does mild hypothermia affect monoclonal antibody glycosylation?, Biotechnology and Bioengineering, 112: 1165‐1176 2. Fan Y, Del Val IJ, Muller C, Lund AM, Sen JW, Rasmussen SK, Kontoravdi C, Baycin‐Hizal D, Betenbaugh MJ, Weilguny D, Andersen MR, 2015, A multi‐pronged investigation into the effect of glucose starvation and culture duration on fed‐batch 66
CHO cell culture, Biotechnology and Bioengineering, 112: 2172‐ 2184 3. Polizzi KM, Kontoravdi C, 2015, Genetically‐encoded biosensors for monitoring cellular stress in bioprocessing, Current Opinion in Biotechnology, 31: 50‐56 4. Fan Y, Jimenez del Val I, Muller C, Sen JW, Rasmussen SK, Kontoravdi C, Weilguny D, Andersen MR, 2015, Amino acid and glucose metabolism in fed‐batch CHO cell culture affects antibody production and glycosylation, Biotechnology and Bioengineering, 112: 521‐535 5. Oliveira PH, Mairhofer J, Alves PM, Lara AR, Kontoravdi C, 2015, Advances in the Development of Biotherapeutics, BioMed Research International, Article ID 793876 6. Jedrzejewski PM, Jimenez del Val I, Constantinou A, Dell A, Haslam SM, Polizzi KM, Kontoravdi C, 2014, Towards J Krishnan Controlling the Glycoform: A Model Framework Linking Extracellular Metabolites to Antibody Glycosylation, Senior Lecturer, Department of Chemical Engineering, International Journal of Molecular Sciences, 15: 4492‐4522 Imperial College London. Affiliated with: Institute for Systems 7. Kyriakopoulos S, Kontoravdi C, 2014, A framework for the and Synthetic Biology, Centre for Bioinformatics systematic design of fed‐batch strategies in mammalian cell culture, Biotechnology and Bioengineering, 111: 2466‐2476 Qualifications 8. Niu H, Leak D, Shah N, Kontoravdi C, 2014, Metabolic B.Tech Indian Institute of Technology, Madras characterization and modeling of fermentation process of an Ph.D Princeton University (Chemical Engg) engineered Geobacillus thermoglucosidasius strain for Associate Research Scientist, Electrical Engg, Johns Hopkins bioethanol production with gas stripping, Chemical University Engineering Science, 122: 138‐149 9. Todri E, Amenaghawon AN, del Val IJ, Leak DJ, Kontoravdi C, Research Interests Kucherenko S, Shah N, 2014, Global sensitivity analysis and Information processing in cells and tissues with applications in meta‐modeling of an ethanol production process, Chemical systems and synthetic biology combining (i) mathematical modelling Engineering Science, 114: 114‐127 (ii) theoretical work (iii) systems analysis including tool development 10. Kyriakopoulos S, Kontoravdi C, 2014, Insights on biomarkers (iv) experimental collaboration. Mathematical modelling involves from Chinese hamster ovary ‘omics’ studies, Pharmaceutical temporal, spatial and stochastic descriptions as appropriate, and Bioprocessing, 2: 389‐401 some of the mathematical modelling is explicitly multi‐level (e.g., 11. Behjousiar A, Constantinou A, Polizzi KM, Kontoravdi C, 2014, cells and tissues). This is complemented by theoretical and systems FIBS‐enabled Noninvasive Metabolic Profiling, Jove‐Journal of work involving tools from dynamical systems, systems engineering, Visualized Experiments, doi:10.3791/51200 control engineering, and network analysis. Modelling and systems analysis spans a whole range of levels and scales from the Invited talks enzymatic (multi‐site phosphorylation), to the gene regulatory 2nd BioProNet Symposium, Manchester, U.K., October 2015 (mRNA translation), to the network (information processing in Cell Line Development & Engineering, Vienna, Austria, February network modules, regulation of the cell cycle in dynamic 2014. environments, spatial control of biochemical cascades and pathways), to the cell and tissue levels (effect of intrinsic and induced drug resistance mechanisms at the cell and tissue scales, engineering of patterns at the tissue level). We are also interested in non‐biological analogues of such work in engineered and related physico‐chemical systems.
Reviewer for Systems and Synthetic Biology PLOS Computational Biology, Biophysical Journal, Journal of Theoretical Biology, Integrative Biology, Interface Journal of the Royal Society, Wiley Interdisciplinary Reviews in Systems Biology and Medicine, Biochemical Engineering Journal, IET Systems Biology, BMC Systems Biology, BMC Research Notes, Physical Biology, 67
Advances in Systems Biology (book), IEEE Transactions in NanoBioscience, Molecular Biosystems, Journal of Chemical Physics.
Biomedical Engineering Annals of Biomedical Engineering, Fundamental and Clinical Pharmacology.
Dynamical Systems/Control/Systems Engg IEEE Transactions on Automatic Control, Automatica, Computers and Chemical Engineering, Chemical Engineering Research and Design.
Academic Collaborations Collaborations with experimental groups in systems and synthetic biology (mRNA translation, cell signalling and decision making, Niall Mac Dowell spatial engineering at cell and tissue levels). Lecturer in Energy and Environmental Technology and Policy, Publications Centre for Environmental Policy, Imperial College London Journal Articles 1. Alam‐Nazki A, Krishnan J, 2015, Spatial Control of Qualifications Biochemical Modification Cascades and Pathways, PhD in Chemical Engineering, Imperial College London (2010) BIOPHYSICAL JOURNAL, Vol: 108, Pages: 2912‐2924, ISSN: B.E. in Chemical Engineering, University College Dublin, (2005) 0006‐3495 2. Liu C, Krishnan J, Xu XY, 2015, Intrinsic and induced drug Awards and Distinctions resistance mechanisms: in silico investigations at the cellular Nicklin Medal, Institution of Chemical Engineers, 2015 and tissue scales, INTEGRATIVE BIOLOGY, Vol: 7, Pages: Chartered Chemical Engineer, CEng, Institution of Chemical 1044‐1060, ISSN: 1757‐9694 Engineers, 2013 3. Suwanmajo T, Krishnan J, 2015, Mixed mechanisms of The Qatar Petroleum Award for PhD Research Excellence in Clean multi‐site phosphorylation, JOURNAL OF THE ROYAL Fossil Fuels, Qatar SOCIETY INTERFACE, Vol: 12, Article number: 20141405, Petroleum, 2010 ISSN: 1742‐5689 4. Zhao Y‐B, Krishnan J, 2015, Probabilistic Boolean Modeling Research Interests and Analysis framework for mRNA translation, IEEE/ACM Clean Fossil Fuels TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND Carbon Capture and Storage (CCS) BIOINFORMATICS, Volume: 13, Pages 754-766 ISSN: Low carbon electricity generation
1557‐9964 Biomass Enhanced Carbon Capture and Storage (BECCS) CO2 5. Krishnan J, Mois K, Suwanmajo T, 2014, The behaviour of Capture and utilisation (CCu) basic autocatalytic signalling modules in isolation and Ionic liquids embedded in networks, JOURNAL OF CHEMICAL PHYSICS, Dynamic Process Modelling, Simulation and Optimisation Vol: 141, Article number: 175102, ISSN: 0021‐9606 Mathematical Modelling 6. Liu C, Krishnan, Xu XY, 2014, Towards an integrated systems‐ based modelling framework for drug transport and its effect Other Activities on tumour cells, JOURNAL OF BIOLOGICAL ENGINEERING, Visiting Academic in the Department of Mechanical Engineering, Vol: 8, ISSN: 1754‐ 1611 University of Sheffield 7. Zhao Y‐B, Krishnan J, 2014, mRNA translation and protein Secretary of the Executive Board of the IChemE Energy Centre synthesis: an analysis of different modelling methodologies Appointed to the TechnicalWorking Group of the Zero Emissions and a new PBN based approach, BMC SYSTEMS BIOLOGY, Platform (ZEP) Appointed to the Technical Working Group of the Vol: 8, ISSN: 1752‐0509 Carbon Capture and Storage Association Member, Royal Society of Chemistry, 2015 Book Chapters MAIChE, American Institution of Chemical Engineers, 2008 1. Krishnan J, Liu C, 2014, An investigation of signal MIChemE, Institution of Chemical Engineers, 2004 transduction and irreversible decision making through monostable and bistable switches, A Systems Theoretic Reviewer for Approach to Systems and Synthetic Biology II: Analysis and Energy and Environmental Science Design of Cellular Systems, Pages: 219‐243, ISBN: Molecular Systems Design and Engineering 9789401790468 68
Publications 10. Mac Dowell N, Shah N, 2014, Dynamic modelling and analysis Journal Articles of a coal‐fired power plant integrated with a novel split‐flow
1. Brown S, Mahgerefteh H, Martynov S, Sundara V, Mac Dowell configuration post‐combustion CO2 capture process, N, 2015, A multi‐source flow model for CCS pipeline International Journal of Greenhouse Gas Control, Vol: 27, transportation networks, INTERNATIONAL JOURNAL OF Pages: 103‐119, ISSN: 1750‐ 5836 GREENHOUSE GAS CONTROL, Vol: 43, Pages: 108‐114, ISSN: 1750‐5836 Conference Contributions 2. Mac Dowell N, Shah N, 2015, The multi‐period optimisation of 1. Mehleri ED, Mac Dowell N, Thornhill NF, 2015, Model
an amine‐based CO2 capture process integrated with a Predictive Control of Post‐Combustion CO2 Capture Process super‐critical coal‐fired power station for flexible operation, integrated with a power plant, 12th International Symposium COMPUTERS & CHEMICAL ENGINEERING, Vol: 74, Pages: on Process Systems Engineering (PSE) / 25th European 169‐183, ISSN: 0098‐ 1354 Symposium on Computer Aided Process Engineering 3. Mac Dowell N, Staffell I, 2015, The role of flexible CCS in the (ESCAPE), Publisher: ELSEVIER SCIENCE BV, Pages: UK’s future energy system, International Journal of 161‐166, ISSN: 1570‐7946 Greenhouse Gas Control, ISSN: 1750‐5836 2. Brown S, Martynov S, Mahgerefteh H, Fairweather M, Woolley 4. Martynov S, Mac Dowell N, Brown S, Mahgerefteh H, 2015, RM, Wareing CJ, Falle SAEG, Rutters H, Niemi A, Zhang YC, Assessment of Integral Thermo‐Hydraulic Models for Pipeline Chen S, Besnebat J, Shah N, Mac Dowell N, Proust C, Farret Transportation of Dense‐Phase and Supercritical R, Economou IG, Tsangaris DM, Boulougouris GC, Van
CO2, INDUSTRIAL & ENGINEERING CHEMISTRY Wittenberghe J, 2014, CO(2)QUEST: Techno‐economic
RESEARCH, Vol: 54, Pages: 8587‐8599, ISSN: 0888‐5885 assessment of CO2 quality effect on its storage and transport, 5. A. Buchard, M. North, C. Kozak, E. Remiezowicz, P. Abrantes, 12th International Conference on Greenhouse Gas Control A. Bardow, J. Dodson, C.Williams, J. Albo, I. Ingram, G. V. S. Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, M. Carrera, P. Styring, M. Poliakoff, K. Lamb, E. A. Quadrelli, Pages: 2622‐2629, ISSN: 1876‐6102 N. Mac Dowell, G. Dowson, M. Aresta, R. Heyn, J. A. Castro‐ 3. Lucquiaud M, Fernandez ES, Chalmers H, Mac Dowell N, Osma, W. Webb, R. Silva, A. Marciniak, C. Jones, C. T. Yavuz, Gibbins J, 2014, Enhanced operating flexibility and optimised C. Capacchione, A. Coogan, M. Priestnall, “Atom efficiency in off‐design operation of coal plants with post‐combustion capture, small molecule and macromolecule synthesis: general 12th International Conference on Greenhouse Gas Control discussion”, Faraday discussions, 2015, 183, 97‐123 5. C. Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, Pages: Jones, K. Armstrong, I. Ingram, E. Bay, J. Dodson, P. Abrantes, 7494‐7507, ISSN: 1876‐6102 M. North, P. Styring, N. Mac Dowell, D. Churina, K. Lamb, M. 4. Mac Dowell N, Shah N, 2014, Optimisation of post‐ th Aresta, G. Dowson, R. Heyn, E. A. Quadrelli, R. Silva, A. combustion CO2 capture for flexible operation, 12 Marciniak, N. Meine, K. Dossumov, A. Navarrete, A. Bardow, A. International Conference on Greenhouse Gas Control Coogan, E. Fraga, “Wider Impacts: general discussion”, Faraday Technologies (GHGT), Publisher: ELSEVIER SCIENCE BV, discussions, 2015, 183, 349‐368 Pages: 1525‐1535, ISSN: 1876‐6102 6. Akgul O, Mac Dowell N, Papageorgiou LG, Shah N, 2014, A mixed integer nonlinear programming (MINLP) supply chain Invited Lectures and Seminars
optimisation framework for carbon negative electricity 1. CO2 capture and storage without the Geography, Alternative generation using biomass to energy with CCS (BECCS) in the Carbon Capture and Storage (CCS) Pathways Workshop, UK, INTERNATIONAL JOURNAL OF GREENHOUSE GAS June 2014, St Catherine’s College, Oxford CONTROL, Vol: 28, Pages: 189‐202, ISSN: 1750‐5836 2. On the use of advanced association theories in process 7. Boot‐Handford ME, Abanades JC, Anthony EJ, Blunt MJ, engineering, SAFT Meeting 2014, April 2014, Tróia, Portugal Brandani S, Mac Dowell N, Fernandez JR, Ferrari M‐C, Gross 3. Optimisation of post‐combustion CO2 capture forflexible R, Hallett JP, Haszeldine RS, Heptonstall P, Lyngfelt A, operation, keynote lecture at UKCCSRC Biannual meeting, Makuch Z, Mangano E, Porter RTJ, Pourkashanian M, April 2014, Queens’ College Cambridge, UK Rochelle GT, Shah N, Yao JG, Fennell PS, 2014, Carbon 4. UK power generation: carbon source or sink?, UKCCSRC capture and storage update, ENERGY & ENVIRONMENTAL workshop on Direct Air/Negative Emissions, March 2014, SCIENCE, Vol: 7, Pages: 130‐189, ISSN: 1754‐5692 Imperial College London 8. Chen L, Sharifzadeh M, Mac Dowell N, Welton T, Shah N, 5. Optimisation of post‐combustion CCS for flexible Hallett JP, 2014, Inexpensive ionic liquids: [HSO4] ̄‐based operation,14th Advanced Power Generation Technology solvent production at bulk scale, GREEN CHEMISTRY, Vol: Forum (APGTF) Workshop, April 2014, 1VS Conference 16, Pages: 3098‐3106, ISSN: 1463‐9262 Centre, Westminster, London, UK 9. Mac Dowell N, Llovell F, Sun N, Hallett JP, George A, Hunt PA, Welton T, Simmons BA, Vega LF, 2014, New Experimental Density Data and soft‐SAFT Models of Alkylimidazolium ([CnC1im](+)) Chloride (Cl‐), Methylsulfate ([MeSO4](‐)), and Dimethylphosphate ([Me2PO4](‐)) Based Ionic Liquids, JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 118, Pages: 6206‐6221, ISSN: 1520‐6106 69
Reviewer for ACS Petroleum Research Fund Chemical Engineering Research and Development Chemical Engineering Science Journal of Chemical and Engineering Data Journal of Materials Chemistry Journal of Non‐Newtonian Fluid Mechanics Journal of Rheology Langmuir Molecular Physics Nature Physical Chemistry Chemical Physics Soft Matter
Publications Geoffrey C. Maitland FREng Journal Articles 1. Al Ghafri SZS, Forte E, Galindo A, Maitland GC, Trusler JPM, Professor of Energy Engineering, Department of Chemical 2015, Experimental and Modeling Study of the Phase Engineering, Imperial College London Behavior of (Heptane plus Carbon Dioxide plus Water) Mixtures, JOURNAL OF CHEMICAL AND ENGINEERING Qualifications DATA, Vol: 60, Pages: 3670‐3681, ISSN: 0021‐ 9568 MA in Chemistry (Oxford University) 2. Bailey L, Lekkerkerker HNW, Maitland GC, 2015, Smectite DPhil in Physical Chemistry (Oxford University) clay ‐ inorganic nanoparticle mixed suspensions: phase behaviour and rheology, SOFT MATTER, Vol: 11, Pages: Awards and Distinctions 222‐236, ISSN: 1744‐683X Fellow of the Royal Academy of Engineering 3. Cadogan SP, Hallett JP, Maidand GC, Trusler JPM, 2015, Fellow of the IChemE Diffusion Coefficients of Carbon Dioxide in Brines Measured President of IChemE 2014‐15 Using C‐13 Pulsed‐Field Gradient Nuclear Magnetic Fellow of the Royal Society of Chemistry Resonance, JOURNAL OF CHEMICAL AND ENGINEERING Salters’ Scholar 1969‐72 DATA, Vol: 60, Pages: 181‐184, ISSN: 0021‐9568 ICI Fellowship 1972‐74 4. Dechatiwongse P, Maitland G, Hellgardt K, 2015, Hutchison Medal of the IChemE, 1999 Demonstration of a two‐stage aerobic/anaerobic chemostat IChemE Envoy Award 2010 for the enhanced production of hydrogen and biomass from RSC/SCI Rideal Award 2012 unicellular nitrogen‐fixing cyanobacterium, ALGAL RESEARCH‐BIOMASS BIOFUELS AND BIOPRODUCTS, Vol: Research Interests 10, Pages: 189‐201, ISSN: 2211‐9264 Clean production and use of fossil fuels 5. Hou S‐X, Maitland GC, Trusler JPM, 2015, Phase equilibria of Carbon capture and storage (CO2 + butylbenzene) and (CO2 + butylcyclohexane) at Recovery of non‐conventional hydrocarbons temperatures between (323.15 and 423.15) K and at Real‐time control and management of oil and gas reservoirs pressures up to 21 MPa, FLUID PHASE EQUILIBRIA, Vol: 387, Thermophysical properties of fluids Pages: 111‐116, ISSN: 0378‐3812 Rheology of complex fluids and soft materials 6. Maitland G, 2015, Refining in the reservoir, TCE The Chemical Rock‐fluid interactions Engineer, Pages: 32‐35, ISSN: 0302‐0797 Renewable solar production of hydrogen from water using green 7. McBride‐Wright M, Maitland GC, Trusler JPM, 2015, Viscosity algae and cyanobacteria and Density of Aqueous Solutions of Carbon Dioxide at Temperatures from (274 to 449) K and at Pressures up to 100 Other Activities MPa, JOURNAL OF CHEMICAL AND ENGINEERING DATA, President, Institution of Chemical Engineers 2014‐15 Vol: 60, Pages: 171‐180, ISSN: 0021‐ 9568 Deputy President, Institution of Chemical Engineers 2013‐14 8. Peng C, Crawshaw JP, Maitland GC, Trusler JPM, 2015, EPSRC: Member of Peer Review College Kinetics of calcite dissolution in CO2‐saturated water at Editor, Chemical Engineering Research and Development Soft temperatures between (323 and 373) K and pressures up to Matter Journal: Founder Member of Editorial Board 13.8 MPa, CHEMICAL GEOLOGY, Vol: 403, Pages: 74‐85, Member of IChemE Council and UK Board ISSN: 0009‐2541 Member of Royal Society of Chemistry Publications Board Member 9. Remiezowicz E, Spooren J, Bay E, Cowan A, Ingram I, of Royal Society of Chemistry Faraday Abrantes P, Nunes da Ponte M, North M, Albo J, Styring P, Council with responsibility for liaison with IChemE Associate Member Priestnall M, Lamb K, Aresta M, Quadrelli EA, Heyn R, Bardow University of Wales Institute of Non‐Newtonian Fluid Mechanics A, Webb W, Silva R, Alonso‐Moreno C, Janaky C, Maitland G, Chair, EPSRC Steering Group, Portfolio Grant on Complex Fluids Vaidyanathan S, Carrera GV, Reed D, Vanbroekhoven K, and Complex Flows, Swansea University Yavuz CT, Pant D, Hollingsworth N, 2015, Capture agents, Chair, UK Offshore Oil and Gas Regulatory Review Panel conversion mechanisms, biotransformations and biomimetics: 70
general discussion., Faraday Discuss, Vol: 183, Pages: 463‐487, ISSN: 1359‐6640 10. Schmidt KAG, Pagnutti D, Curran MD, Singh A, Trusler JPM, Maitland GC, McBride‐Wright M, 2015, New Experimental Data and Reference Models for the Viscosity and Density of Squalane, JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 60, Pages: 137‐150, ISSN: 0021‐9568 11. Zhang D, Dechatiwongse P, Del‐Rio‐Chanona EA, Hellgardt K, Maitland GC, Vassiliadis VS, 2015, Analysis of the cyanobacterial hydrogen photoproduction process via model identification and process simulation, CHEMICAL ENGINEERING SCIENCE, Vol: 128, Pages: 130‐146, ISSN: 0009‐2509 12. Zhang D, Dechatiwongse P, del Rio‐Chanona EA, Maitland GC, Hellgardt K, Vassiliadis VS, 2015, Modelling of light and Athanasios (Sakis) Mantalaris temperature influences on cyanobacterial growth and biohydrogen production, ALGAL RESEARCH‐BIOMASS Professor in BioSystems Engineering, Department BIOFUELS AND BIOPRODUCTS, Vol: 9, Pages: 263‐274, of Chemical Engineering, Imperial College London ISSN: 2211‐9264 13. Zhang D, Dechatiwongse P, del Rio‐Chanona EA, Maitland Qualifications GC, Hellgardt K, Vassiliadis VS, 2015, Dynamic modelling of PhD in Chemical Engineering, University of Rochester high biomass density cultivation and biohydrogen production MSc in Chemical Engineering, University of Rochester in different scales of flat plate photobioreactors, BIOTECHNOLOGY AND BIOENGINEERING, Vol: 112, Pages: Awards and Distinctions 2429‐2438, ISSN: 0006‐3592 Fellow of the American Institute of Biological and 14. del Rio‐Chanona EA, Dechatiwongse P, Zhang D, Maitland Medical Engineers 2013 GC, Hellgardt K, Arellano‐Garcia H, Vassiliadis VS, 2015, European Research Council Advanced Investigator Award 2012 Optimal Operation Strategy for Biohydrogen Production, Fellow, American Institute of Medical & Biological Engineering, 2011 INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, Vol: 1st Prize Award, Hellenic Association of Orthopaedics Surgery & 54, Pages: 6334‐6343, ISSN: 0888‐5885 Traumatology, 2009 15. Al Ghafri SZS, Maitland GC, Trusler JPM, 2014, Experimental Rector’s Award for Research Excellence, Imperial College, 2006 and modeling study of the phase behavior of synthetic crude Live Demo Award, ISCAS, 2006
oil + CO2, FLUID PHASE EQUILIBRIA, Vol: 365, Pages: 20‐40, Jounitor Moulton Award, IChemE, 2004 ISSN: 0378‐3812 16. Al Ghafri SZS, Forte E, Maitland GC, Rodriguez‐Henriquez JJ, Research Interests Trusler JPM, 2014, Experimental and Modeling Study of the Modelling of Biological Systems, Mammalian Cell Bioprocessing,
Phase Behavior of (Methane + CO2 + Water) Mixtures, Stem Cell Bioprocessing and Tissue Engineering. JOURNAL OF PHYSICAL CHEMISTRY B, Vol: 118, Pages: 14461‐14478, ISSN: 1520‐ 6106 Other Activites 17. Bailey L, Lekkerkerker HNW, Maitland GC, 2014, Rheology Member of the Executive Board of the European Society for modification of montmorillonite dispersions by colloidal silica, Biochemical Engineering Sciences (ESBES) RHEOLOGICA ACTA, Vol: 53, Pages: 373‐384, ISSN: Member of the Advisory Board for Prometheus 0035‐4511 Catholic University of Leuven 18. Cadogan SP, Maitland GC, Trusler JPM, 2014, Diffusion
Coefficients of 2CO and N‐2 in Water at Temperatures Reviewer for between 298.15 K and 423.15 K at Pressures up to 45 MPa, Tissue Engineering JOURNAL OF CHEMICAL AND ENGINEERING DATA, Vol: 59, Biomaterials, Stem Cells & Development Pages: 519‐525, ISSN: 0021‐9568 Biochemical Engineering Journal 19. Dechatiwongse P, Srisamai S, Maitland G, Hellgardt K, 2014, Biotechnology & Bioengineering Effects of light and temperature on the photoautotrophic growth and photoinhibition of nitrogen‐fixing cyanobacterium Academic Collaborations Cyanothece sp ATCC 51142, ALGAL RESEARCH‐BIOMASS University of Thessaloniki ETH BIOFUELS AND BIOPRODUCTS, Vol: 5, Pages: 103‐111, Temple University ISSN: 2211‐9264 NTU
20. Maitland G, 2014, Putting CO2 in its place, TCE The Chemical Engineer, Pages: 34‐37, ISSN: 0302‐0797 71
Industrial Collaborations Dynamics and Umbrella Sampling Simulations, JOURNAL OF Novalung CHEMICAL INFORMATION AND MODELING, Vol: 54, Pages: 2093‐2104, ISSN: 1549‐9596 Publications 11. Misener R, Chin J, Lai M, Gari MF, Velliou E, Panoskaltsis N, Journal Articles Pistikopoulos EN, Mantalaris A, 2014, Robust Superstructure 1. Kang Y, Georgiou AI, MacFarlane RJ, Klontzas ME, Heliotis M, Optimisation of a Bioreactor that Produces Red Blood Cells, Tsiridis E, Mantalaris A, 2015, Fibronectin stimulates the 24th EUROPEAN SYMPOSIUM ON COMPUTER AIDED osteogenic differentiation of murine embryonic stem cells., J PROCESS ENGINEERING, PTS A AND B, Vol: 33, Pages: Tissue Eng Regen Med 91‐96, ISSN: 1570‐7946 2. Kiparissides A, Pistikopoulos EN, Mantalaris A, 2015, On the 12. Misener R, Gari MF, Rende M, Velliou E, Panoskaltsis N, Model‐Based Optimization of Secreting Mammalian Cell Pistikopoulos EN, Mantalaris A, 2014, Global superstructure (GS‐NS0) Cultures, BIOTECHNOLOGY AND optimisation of red blood cell production in a parallelised BIOENGINEERING, Vol: 112, Pages: 536‐548, ISSN: hollow fibre bioreactor, COMPUTERS & CHEMICAL 0006‐3592 ENGINEERING, Vol: 71, Pages: 532‐553, ISSN: 0098‐1354 3. Muenzer DGG, Ivarsson M, Usaku C, Habicher T, Soos M, 13. Muenzer DGG, Kostoglou M, Georgiadis MC, Pistikopoulos Morbidelli M, Pistikopoulos EN, Mantalaris A, 2015, An EN, Mantalaris A, 2014, A Cyclin Distributed Cell Cycle Model unstructured model of metabolic and temperature dependent in GS‐NS0, 24th EUROPEAN SYMPOSIUM ON COMPUTER cell cycle arrest in hybridoma batch and fed‐batch cultures, AIDED PROCESS ENGINEERING, PTS A AND B, Vol: 33, BIOCHEMICAL ENGINEERING JOURNAL, Vol: 93, Pages: Pages: 19‐24, ISSN: 1570‐7946 260‐273, ISSN: 1369‐703X 14. Pefani E, Panoskaltsis N, Mantalaris A, Georgiadis MC, 4. Fauzi I, Panoskaltsis N, Mantalaris A, 2014, Early Exposure of Pistikopoulos EN, 2014, Chemotherapy Drug Scheduling for Murine Embryonic Stem Cells to Hematopoietic Cytokines the Induction Treatment of Patients With Acute Myeloid Differentially Directs Definitive Erythropoiesis and Leukemia, IEEE TRANSACTIONS ON BIOMEDICAL Cardiomyogenesis in Alginate Hydrogel Three‐Dimensional ENGINEERING, Vol: 61, Pages: 2049‐2056, ISSN: 0018‐9294 Cultures, STEM CELLS AND DEVELOPMENT, Vol: 23, Pages: 15. Rende M, Panoskaltsis N, Morilla R, Mantalaris A, 2014, Novel 2720‐2729, ISSN: 1547‐3287 successful cytokine‐free culture of acute leukemic cells in a 5. Fuentes‐Gari M, Misener R, Garcia‐Munzer D, Velliou E, perfused hollow‐fiber bioreactor, JOURNAL OF TISSUE Georgiadis M, Kostoglou M, Panoskaltsis N, Pistikopoulos S, ENGINEERING AND REGENERATIVE MEDICINE, Vol: 8, Mantalaris S, 2014, Development and experimental validation Pages: 48‐48, ISSN: 1932‐6254 of a cyclin‐based population balance model of the cell cycle in 16. Teo A, Mantalaris A, Lim M, 2014, Influence of culture pH on leukemia cell lines, JOURNAL OF TISSUE ENGINEERING proliferation and cardiac differentiation of murine embryonic AND REGENERATIVE MEDICINE, Vol: 8, Pages: 489‐489, stem cells, BIOCHEMICAL ENGINEERING JOURNAL, Vol: 90, ISSN: 1932‐6254 Pages: 8‐15, ISSN: 1369‐703X 6. Gamie Z, MacFarlane RJ, Tomkinson A, Moniakis A, Gui TT, 17. Teo A, Mantalaris A, Song K, Lim M, 2014, A novel perfused Gamie Y, Mantalaris A, Tsiridis E, 2014, Skeletal tissue rotary bioreactor for cardiomyogenesis of embryonic stem engineering using mesenchymal or embryonic stem cells: cells, BIOTECHNOLOGY LETTERS, Vol: 36, Pages: 947‐ 960, clinical and experimental data, EXPERT OPINION ON ISSN: 0141‐5492 BIOLOGICAL THERAPY, Vol: 14, Pages: 1611‐1639, ISSN: 18. Velliou E, Dos Santos SB, Gari MF, Misener R, Panoskaltsis N, 1471‐2598 Pistikopoulos E, Mantalaris A, 2014, Evolution of an AML 7. Kiparissides A, Georgakis C, Mantalaris A, Pistikopoulos EN, model system under oxidative & starvation stress: a 2014, Design of In Silico Experiments as a Tool for Nonlinear comparison between two and three dimensional cultures, Sensitivity Analysis of Knowledge‐Driven Models, INDUSTRIAL JOURNAL OF TISSUE ENGINEERING AND REGENERATIVE & ENGINEERING CHEMISTRY RESEARCH, Vol: 53, Pages: MEDICINE, Vol: 8, Pages: 383‐383, ISSN: 1932‐6254 7517‐7525, ISSN: 0888‐5885 19. Velliou E, Fuentes‐Gari M, Misener R, Pefani E, Rende M, 8. Krieger A, Panoskaltsis N, Mantalaris A, Georgiadis MC, Panoskaltsis N, Mantalaris A, Pistikopoulos EN, 2014, A Pistikopoulos EN, 2014, Modeling and Analysis of framework for the design, modeling and optimization of Individualized Pharmacokinetics and Pharmacodynamics for biomedical systems, PROCEEDINGS OF THE 8th Volatile Anesthesia, IEEE TRANSACTIONS ON BIOMEDICAL INTERNATIONAL CONFERENCE ON FOUNDATIONS OF ENGINEERING, Vol: 61, Pages: 25‐34, ISSN: 0018‐9294 COMPUTER‐AIDED PROCESS DESIGN, Vol: 34, Pages: 9. Lee K‐Y, Buldum G, Mantalaris A, Bismarck A, 2014, More 225‐236, ISSN: 1570‐ 7946 Than Meets the Eye in Bacterial Cellulose: Biosynthesis, 20. Yeo DC, Wiraja C, Mantalaris AS, Xu C, 2014, Nanosensors Bioprocessing, and Applications in Advanced Fiber for Regenerative Medicine, JOURNAL OF BIOMEDICAL Composites, MACROMOLECULAR BIOSCIENCE, Vol: 14, NANOTECHNOLOGY, Vol: 10, Pages: 2722‐2746, ISSN: Pages: 10‐32, ISSN: 1616‐5187 1550‐7033 10. Marzinek JK, Bond PJ, Lian G, Zhao Y, Han L, Noro MG, Pistikopoulos EN, Mantalaris A, 2014, Free Energy Predictions of Ligand Binding to an alpha‐Helix Using Steered Molecular 72
21. Zavitsanou S, Mantalaris A, Georgiadis MC, Pistikopoulos EN, Research Interests 2014, Optimization of Insulin Dosing in Patients with Type 1 Research Domain: Optimisation Methods & Computation. Diabetes Mellitus, 24th EUROPEAN SYMPOSIUM ON Foundations: Global optimisation of mixed‐integer nonlinear COMPUTER AIDED PROCESS ENGINEERING, PTS A AND programs (MINLP); Numerical optimisation algorithms; B, Vol: 33, Pages: 1459‐1464, ISSN: 1570‐7946 Computational optimisation frameworks; Implementations and 22. Zhao Y, Marzinek JK, Bond PJ, Chen L, Li Q, Mantalaris A, software for global optimisation. Pistikopoulos EN, Noro MG, Han L, Lian G, 2014, A Study on Applications: Optimal chemotherapy scheduling for leukaemia; Fe2+ ‐ alpha‐Helical‐Rich Keratin Complex Formation Using Bioprocess optimisation under uncertainty; Cell cycle modelling; Isothermal Titration Calorimetry and Molecular Dynamics Superstructure optimisation of chemical and petrochemical plants Simulation, JOURNAL OF PHARMACEUTICAL SCIENCES, for energy efficiency; Process network design and operations. Vol: 103, Pages: 1224‐1232, ISSN: 0022‐3549 Other Activities Conference Contributions Software development/maintenance of MINLP global optimization 1. Misener R, Allenby M, Gari MF, Rende M, Velliou E, solvers ANTIGONE and GloMIQO. Panoskaltsis N, Pistikopoulos S, Mantalaris A, 2014, Optimisation under uncertainty for a bioreactor that produces Reviewer for red blood cells ADCHEM, AIChE Journal, Computational Optimization & Applications; Computers & Chemical Engineering (Top Reviewer, 2013; Top 10% in reviews completed, 2014 ‐ 2015); European Journal of Operational Research; Industrial & Engineering Chemistry Research; Journal of Global Optimization; Journal of Optimization Theory & Applications; Management Science; Mathematical Programming; Operations Research Letters; Optimization Letters.
Academic Collaborations MIT, Texas A&M, University of Liége
Industrial Collaborations GAMS Development Corp
Publications Book Chapters Ruth Misener 1. Fuentes‐Gari M., Misener R., Georgiadis M. C., Kostoglou M., Pistikopoulos E. N., Panoskaltsis N., Mantalaris A. Lecturer & Royal Academy of Engineering Research Fellow, Chemotherapy Optimization in Leukemia: Selecting the Right Department of Computing, Imperial College London Mathematical Models for the Right Biological Processes. 9th IFAC Symposium on Biological & Medical Systems. Vol. 48 of Qualifications IFAC‐ PapersOnLine. Berlin, DE; 2015; pp 534‐539. BSc in Chemical Engineering (Massachusetts Institute of Technology) 2. Savvopoulos S. V., Misener R., Panoskaltsis N., Pistikopoulos PhD in Chemical Engineering (Princeton University) E. N., Mantalaris A. Global Sensitivity Analysis for a Dynamic Model of Chronic Lymphocytic Leukemia Disease Trajectories. Awards and Distinctions In Gernaey, Huusom, Gani (Eds), 12th International Symposium Royal Academy of Engineering Research Fellowship, 2012‐2017 on Process Systems Engineering & 25th European Symposium Imperial College Junior Research Fellowship (declined), 2012‐2015 on Computer Aided Process Engineering. Vol. 37 of W. David Smith, Jr. Graduate Student Paper Award (2014) Computer‐Aided Chemical Engineering. Copenhagen, DK; Best Paper of 2013; Journal of Global Optimization (awarded in 2014) 2015; pp 185‐190. Top Reviewer; Computers & Chemical Engineering, 2013 3. Fuentes‐Gari M., Misener R., Pefani E., Garcia‐Munzer D., Best Poster; 2nd Belgian Symposium on Tissue Engineering Kostoglou M., Georgiadis M. C., Panoskaltsis N., (BSTE), 2013 Pistikopoulos E. N., Mantalaris A. Cell cycle model selection USA National Science Foundation Graduate Research Fellowship, for leukemia and its impact in chemotherapy outcomes. In 2007‐2012 Gernaey, Huusom, Gani (Eds), 12th International Symposium Princeton University Gordon Y. S. Wu Fellowship, 2007‐2012 on Process Systems Engineering & 25th European Symposium Robert C. Byrd Honors Scholarship, 2003‐2007 on Computer Aided Process Engineering. Vol. 37 of Excellence in Teaching; Princeton School of Engineering & Applied Computer‐Aided Chemical Engineering. Copenhagen, DK; Sciences, 2010 2015; pp 2159‐2164. Member, MIT Tau Beta Pi‐Engineering Honor Society, 2007 4. Misener R., Chin J., Lai M., Fuentes‐Gari M., Velliou E., Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Robust Superstructure Optimisation of a Bioreactor that Produces 73
Red Blood Cells. In Klemes, Varbanov, Liew (Ed.), 24th blood cells (RBCs) in a novel 3D hollow fibre bioreactor. European Symposium on Computer Aided Process TERMIS. Boston, MA, 09/2015. Engineering. Vol. 33 of Computer‐Aided Chemical 3. Fuentes‐Gari M., Misener R., Georgiadis M. C., Kostoglou M., Engineering. Budapest, Hungary; 2014; pp 91‐96 Pistikopoulos E. N., Panoskaltsis N., Mantalaris A. Chemotherapy Optimization in Leukemia: Selecting the Right Mathematical Journal Articles Models for the Right Biological Processes. 9th IFAC Symposium 1. Fuentes‐Gari M., Misener R., Georgiadis M. C., Kostoglou M., on Biological & Medical Systems. Berlin, DE; 09/2015 Pistikopoulos E. N., Panoskaltsis N., Mantalaris A. Selecting a 4. Misener R., Mistry M. Solving MINLP with Heat Exchangers: differential equation cell cycle model for simulating leukemia Special Structure Detection and Large‐ Scale Global treatment; Industrial & Engineering Chemistry Research; Optimisation. 13th EUROPT Workshop on Advances in 54:8847‐8859, 2015. Continuous Optimisation, Edinburgh, Scotland; 07/2015. 2. Velliou E., Brito dos Santos S., Papathanasiou M. M., Fuentes‐ 5. Misener R., Fuentes‐Gari M., Allenby M. C., Panoskaltsis N., Gari M., Misener R., Panoskaltsis N., Mantalaris A., Pistikopoulos E. N., Mantalaris A. Stem Cell Bioprocessing Pistikopoulos E. N. Towards unravelling the kinetics of an under Uncertainty: A Case Study in Optimising Red Blood Cell Acute Myeloid Leukaemia model system under oxidative and Production. 17th British‐ French‐German Conference on starvation stress: A comparison between two and three Optimization. London, UK; 06/2015. dimensional cultures; Bioprocess & Biosystems Engineering; 6. Savvopoulos S. V., Misener R., Panoskaltsis N., Pistikopoulos 38:1589‐1600, 2015. E. N., Mantalaris A. Global Sensitivity Analysis for a Dynamic 3. Fuentes‐Gari M., Velliou E., Misener R., Pefani E., Rende M., Model of Chronic Lymphocytic Leukemia Disease Trajectories. Panoskaltsis N., Mantalaris A., Pistikopoulos E. N. A 12th International Symposium on Process Systems systematic framework for the design, simulation and Engineering & 25th European Symposium on Computer Aided optimization of personalized healthcare: Making and healing Process Engineering. Copenhagen, DK; 06/2015. blood; Computers & Chemical Engineering; 81:80‐93, 2015. 7. Misener R., Fuentes‐Gari M., Velliou E., Panoskaltsis N., 4. Fuentes‐Gari M., Misener R., Garcia‐Munzer D., Velliou E., Pistikopoulos E. N., Mantalaris A. Ro‐ bust Design and Operation Georgiadis M. C., Kostoglou M., Pistikopoulos E. N., of Red Blood Cell Production in a Parallelised Hollow Fibre Panoskaltsis N., Mantalaris A. A mathematical model of sub‐ Bioreactor. AIChE Annual Meeting. Atlanta, GA; 11/2014. population kinetics for the deconvolution of leukaemia 8. Velliou E., Brito Dos Santos S., Fuentes‐Gari M., Misener R., heterogeneity. Journal of The Royal Society Interface; 12(108), Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Towards in 2015. vitro Optimization of Chemotherapy for Leukaemia Under 5. Misener R., Smadbeck J. B., Floudas C. A. Dynamically‐ Environ‐ mental Stress: Moving from Two to Three Dimensional generated cutting planes for mixed‐integer quadratically‐ Cultures. AIChE Annual Meeting. Atlanta, GA; 11/2014. constrained quadratic programs and their incorporation into 9. Fuentes‐Gari M., Misener R., Garcia‐Munzer D., Velliou E., GloMIQO 2; Optimization Methods & Software; 30: Georgiadis M. C., Kostoglou M., Panoskaltsis N., 215‐249, 2015. Pistikopoulos E. N., Mantalaris A. Towards Personalized 6. Velliou E., Brito dos Santos S., Fuentes‐Gari M., Misener R., Treatments for Leukemia Based on Cell Cycle Heterogeneity: Pefani E., Panoskaltsis N., Mantalaris A., Pistikopoulos E. N. An Experimental/Modeling Approach. AIChE Annual Meeting. Key environmental stress biomarker candidates for the Atlanta, GA; 11/2014. optimisation of chemotherapy treatment of leukaemia; Malta 10. Misener R., Fuentes‐Gari M., Velliou E., Panoskaltsis N., Journal of Health Sciences; 1: 29‐34, 2014. Pistikopoulos E. N., Mantalaris A. Robust Design and 7. Misener R., Fuentes‐Gari M., Rende M., Velliou E., Operation of Red Blood Cell Production in a Parallelised Panoskaltsis N., Pistikopoulos E. N., Mantalaris A., Global Hollow Fibre Bioreactor. INFORMS Annual Meeting. San Superstructure Optimisation of Red Blood Cell Production in a Francisco, CA; 11/2014. Parallelised Hollow Fibre Bioreactor, Computers & Chemical 11. Velliou E., Fuentes‐Gari M., Misener R., Pefani E., Rende M., Engineering; 71: 532‐553, 2014. Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. A framework 8. Misener R., Floudas C. A. ANTIGONE: Algorithms for for the design, modeling and optimization of biomedical systems. coNTinuous / Integer Global Optimization of Nonlinear 8th International Conference on Foundations of Computer‐Aided Equations, Journal of Global Optimization; 59: 503‐526, 2014. Process Design. Cle Elum, WA; 07/2014. 9. Misener R., Floudas C. A. A framework for globally optimizing 12. Misener R., Chin J., Lai M., Fuentes‐Gari M., Velliou E., mixed‐integer signomial programs. Journal of Optimization Panoskaltsis N., Pistikopoulos E. N., Mantalaris A. Robust Theory & Applications; 161: 905‐932, 2014. Superstructure Optimisation of a Bioreactor that Produces Red Blood Cells. 24th European Symposium on Computer Conference Contributions Aided Process Engineering. Budapest, Hungary; 06/2014. 1. Mistry M., Misener R. Solving MINLP with Heat Exchangers: Special Structure Detection and Large‐ Scale Global Invited Lectures and Seminars Optimisation. AIChE Annual Meeting. Salt Lake City, UT, 11/2015. 1. Misener R. Mixed‐Integer Nonlinear Optimisation: Energy 2. Allenby M. C., Tahlawi A., Brito Dos Santos S., Misener R., Efficiency Applications. School of Mathematics; University of Hwang Y., Panoskaltsis N., Mantalaris A. Development of a Edinburgh; Invited by Dr A Grothey and Prof K McKinnon; hematopoietic microenvironment for the production of red 10/2015. 74
2. Ceccon F., Misener R. Detecting Pooling Network Structure. Research Interests Short Research Announcement at the Oberwolfach MINLP Molecular simulation of complex fluids (liquid crystals, asphaltenes, Workshop, Oberwolfach, DE; 10/2015. polymers, etc.) adsorption and interfacial phenomena (activated 3. Misener R., Mistry M. Solving MINLP with Heat Exchangers: carbons, nanotubes, colloids) Special Structure Detection and Large‐ Scale Global Phase equilibria and thermophysical properties (VLE, supercritical Optimisation. 22nd International Symposium on Mathematical fluids, etc.) bridging size scales from atomistic simulations to Programming, Pittsburgh, PA; Invited by Prof C Floudas; equation of state modelling (SAFT) 07/2015. Focus on application to engineering, environmental problems and 4. Misener R. Global Optimisation; Centre for Process Systems high performance computing for engineering Engineering Advanced Optimisation Course, Imperial College London, England; Invited by Prof C Adjiman; 04/2015. Other Activities 5. Misener R. Stem Cell Bioprocessing under Uncertainty: A Fellow, Royal Society of Chemistry, 2011 Case Study in Optimising Red Blood Cell Production. Centre Member, International Adsorption Society for Computational Engineering Science; RWTH Aachen; Senior Member, AIChE Invited by Prof A Mitsos; 02/2015. 6. Misener R. Global Optimisation for Process Optimisation. Links with Other Academic Bodies Process Systems Enterprise; London, England; Invited by Dr P Visiting Professor, Universidad de Concepcion Kleniati; 01/2015. Visiting Researcher, Cornell University 7. Misener R. Deterministic Global Optimisation for Process Visiting Researcher, North Carolina State University Optimisation. Centre for Process Systems Engineering Annual Visiting Researcher, Danmarks Techniske Højskole Industrial Consortium Meeting, Imperial College London, Visiting Researcher, Universidad de Sevilla England; Invited by Prof N Shah; 12/2014. Visiting Professor, Universidad Pablo de Olavide 8. Misener R. Relating MINLP Model Formulations to Algorithmic Solution Strategies. Department of Electronics, Computer Publications Sciences and Systems; University of Bologna; Invited by Prof Journal Articles A Lodi; 06/2014. 1. Braga, Carlos, Amparo Galindo, and Erich A Müller. 9. Misener R. Mixed‐Integer Nonlinear Optimization: Foundations “Nonequilibrium Molecular Dynamics Simulation of Diffusion at and Applications. Department of Computing; Imperial College the Liquid‐Liquid Interface.” Journal of Chemical Physics 141, London; Job Talk; 03/2014. (2014): 154101. doi:10.1063/1.4897159. 10. Misener R. Making and Healing Blood: An Engineer’s 2. Cumicheo, Constanza, Marcela Cartes, Hugo Segura, Erich A Approach. Department of Chemical Engineering; University of Müller, and Andrés Mejía. “High‐ Pressure Densities and Surrey, England; Invited by Prof K Kirkby; 01/2014. Interfacial Tensions of Binary Systems Containing Carbon Dioxide+n‐Alkanes: (n‐Dodecane, n‐Tridecane, n‐ Tetradecane).” Fluid Phase Equilibria 380 (2014): 82– 92. doi:10.1016/j.fluid.2014.07.039. 3. Forte, Esther, Andrew J. Haslam, George Jackson, and Erich A Müller. “Effective Coarse‐ Grained Solid‐Fluid Potentials and Their Application to Model Adsorption of Fluids on Heterogeneous Surfaces.” Physical Chemistry Chemical Physics 16 (2014): 19165–80. doi:10.1039/C4CP00670D. 4. Frentrup, Hendrik, Kyle Hart, Coray Colina, and Erich Muller. “In Silico Determination of Gas Permeabilities by Non‐Equilibrium
Molecular Dynamics: CO2 and He Through PIM‐1.” Membranes 5, (2015): 99–119. doi:10.3390/membranes5010099. 5. Herdes, Carmelo, Erik E Santiso, Craig James, Julian Eastoe, and Erich A Müller. “Modelling the Interfacial Behaviour of Dilute Light‐Switching Surfactant Solutions.” Journal of Colloid and Interface Science 445, (2015): 16–23. doi:10.1016/j. Erich A. Müller jcis.2014.12.040. 6. Herdes, Carmelo, Tim S Totton, and Erich A Müller. “Coarse Professor of Thermodynamics, Department of Chemical Grained Force Field for the Molecular Simulation of Natural Engineering, Imperial College London Gases and Condensates.” Fluid Phase Equilibria 406 (2015): 91–100. doi:10.1016/j.fluid.2015.07.014. Qualifications 7. Jover, Julio F, Erich A Müller, Andrew J. Haslam, Amparo Ph.D. in Chemical Engineering, Cornell University (USA) Galindo, George Jackson, Hervé Toulhoat, and Carlos M.Sc. in Chemical Engineering (honor mention), Universidad Simón Nieto‐Draghi. “Aspects of Asphaltene Aggregation Obtained Bolívar, (Venezuela) From Coarse‐Grained Molecular Modeling.” Energy and Fuels 29 (2015): 556–66. doi:10.1021/ef502209j. 75
8. Jover, Julio, Amparo Galindo, George Jackson, Erich A Müller, and Andrew J. Haslam. “Fluid– Fluid Coexistence in an Athermal Colloid–Polymer Mixture: Thermodynamic Perturbation Theory and Continuum Molecular‐Dynamics Simulation.” Molecular Physics 113, (2015): 2608–28. doi:10.1 080/00268976.2015.1047425. 9. Lau, Gabriel V, Ian J Ford, Patricia A Hunt, Erich A Müller, and George Jackson. “Surface Thermodynamics of Planar, Cylindrical, and Spherical Vapour‐Liquid Interfaces of Water.” Journal of Chemical Physics 142, (2015): 114701. doi:10.1063/1.4913371. 10. Lobanova, Olga, Carlos Avendaño, Thomas Lafitte, Erich A Müller, and George Jackson. “SAFT‐ Γ Force Field for the Simulation of Molecular Fluids: 4. a Single‐Site Coarse‐ Grained Model of Water Applicable Over a Wide Temperature Costas C. Pantelides FREng Range.” Molecular Physics 113, (2015): 1228–49. doi:10.1080 /00268976.2015.1004804. Professor of Chemical Engineering, Department of Chemical 11. Mejía, Andrés, Marcela Cartes, Hugo Segura, and Erich A Müller. Engineering, Imperial College London “Use of Equations of State and Coarse Grained Simulations to Complement Experiments: Describing the Interfacial Properties Qualifications of Carbon Dioxide + Decane and Carbon Dioxide + Eicosane BSc (Eng.) in Chemical Engineering (Imperial College London) Mixtures.” Journal of Chemical and Engineering Data 59, (2014): MSc in Chemical Engineering (MIT) 2928–41. doi:10.1021/je5000764. PhD, DIC in Symbolic & numerical solution methods (Imperial 12. Müller, E A, C Herdes, and T S Totton. Coarse‐Grained College London) Models for Crude Oils: a Direct Link Between Equations of State and Molecular Simulations. OTC Brasil, Offshore Awards and Distinctions Technology Conference, 2015. doi:10.4043/26155‐MS. 2015 The Sargent Medal, The Institution of Chemical Engineers 13. Müller, Erich A, and George Jackson. “Force‐Field Parameters 2015 The President’s Medal for Excellence in Innovation and From the SAFT‐Γ Equation of State for Use in Coarse‐Grained Entrepreneurship, Imperial College London Molecular Simulations.” Annual Review of Chemical and 2010 Fellow of the Royal Academy of Engineering Biomolecular Engineering 5, (2014): 405–27. doi:10.1146/ 2009 Fellow of the Institution of Chemical Engineers annurev‐chembioeng‐061312‐ 103314. 2007 MacRobert Award of the Royal Academy of Engineering, 14. Ramrattan, N S, C Avendaño, E A Müller, and A Galindo. “A awarded for the innovation of gPROMS Corresponding‐States Framework for the Description of the 1998 Beilby Medal from the SCI, RSC and IoM for contributions to Mie Family of Intermolecular Potentials.” Molecular Physics process systems engineering 113, (2015): 932–47. doi:10.1080/00268976.2015.1025112. 15. Theodorakis, Panagiotis E, Erich A Müller, Richard V Craster, Research Interests and O. K Matar. “Modelling the Superspreading of Surfactant‐ Process modelling methodologies & tools Laden Droplets with Computer Simulation.” Soft Matter 11, Systems‐based Pharmaceutics (2015): 9254–61. doi:10.1039/C5SM02090E. Ab initio prediction of crystal structures 16. Theodorakis, Panagiotis E, Erich A Müller, Richard V Craster, and O. K Matar. “Insights Into Surfactant‐Assisted Other Activities Superspreading.” Current Opinion in Colloid & Interface Managing Director, Process Systems Enterprise Ltd. Science 19, (2014): 283–89. doi:10.1016/j.cocis.2014.04.007. 17. Theodorakis, Panagiotis E, Erich A Müller, Richard V Craster, Publications and O. K Matar. “Superspreading: Mechanisms and Molecular Journal Articles Design.” Langmuir 31, (2015): 2304–9. doi:10.1021/ 1. Habgood M, Sugden IJ, Kazantsev AV, Adjiman CS, la5044798. Pantelides CC, 2015, Efficient Handling of Molecular Flexibility 18. Wu, Liang, Alexandr Malijevský, George Jackson, Erich A in Ab Initio Generation of Crystal Structures, JOURNAL OF Müller, and Carlos Avendaño. “Orientational Ordering and CHEMICAL THEORY AND COMPUTATION, Vol: 11, Pages: Phase Behaviour of Binary Mixtures of Hard Spheres and Hard 1957‐1969, ISSN: 1549‐9618 Spherocylinders.” Journal of Chemical Physics 143, (2015): 2. Vasileiadis M, Pantelides CC, Adjiman CS, 2015, Prediction of 044906–14. doi:10.1063/1.4923291. the crystal structures of axitinib, a polymorphic pharmaceutical molecule, CHEMICAL ENGINEERING SCIENCE, Vol: 121, Pages: 60‐76, ISSN: 0009‐2509 3. Pantelides CC, Adjiman CS, Kazantsev AV, 2014, General Computational Algorithms for Ab Initio Crystal Structure Prediction for Organic Molecules, PREDICTION AND 76
CALCULATION OF CRYSTAL STRUCTURES: METHODS Industrial Collaborations AND APPLICATIONS, Vol: 345, Pages: 25‐58, ISSN: Bayer, Syngenta, Unilever. 0340‐1022 Publications Conference Contributions Journal Articles 1. Rodriguez J, Andrade A, Lawal A, Samsatli N, Calado M, 1. Li, F. G. N., McDowall, W., Agnolucci, P., Akgul, O., & Ramos A, Lafitte T, Fuentes J, Pantelides CC, 2014, An Papageorgiou, L. G. (2015). Designing optimal infrastructures integrated framework for the dynamic modelling of for delivering hydrogen to consumers. In R. B. Gupta, A.
solventbased CO2 capture processes, 12th International Basile, T. N. Veziroglu (Eds.), Conference on Greenhouse Gas Control Technologies, Energy 2. Compendium of Hydrogen Energy, Volume 2: Hydrogen Procedia, Vol: 63, Pages: 1206‐1217, ISSN: 1876‐6102 Storage, Distribution and Infrastructure. Woodhead Publishing. 3. Bennett, L., Kittas, A., Muirhead, G., Papageorgiou, L. G., & Tsoka, S. (2015). Detection of Composite Communities in Multiplex Biological Networks. SCIENTIFIC REPORTS, 5, ARTN 10345. doi:10.1038/srep10345 4. Liu, S., Simaria, A. S., Farid, S. S., & Papageorgiou, L. G. (2015). Mathematical programming approaches for downstream processing optimisation of biopharmaceuticals. CHEMICAL ENGINEERING RESEARCH AND DESIGN, 94, 18‐31. doi:10.1016/j.cherd.2014.12.002 5. Yang, L., Ainali, C., Kittas, A., Nestle, F. O., Papageorgiou, L. G., & Tsoka, S. (2015). Pathway‐level disease data mining through hyper‐box principles. MATHEMATICAL BIOSCIENCES, 260, 25‐34. doi:10.1016/j.mbs.2014.09.005 6. Calderon, A. J., Guerra, O. J., Papageorgiou, L. G., Siirola, J. J., & Reklaitis, G. V. (2015). Preliminary Evaluation of Shale Lazaros G. Papageorgiou Gas Reservoirs: Appraisal of Different Well‐Pad Designs via Performance Metrics. INDUSTRIAL & ENGINEERING Professor in Chemical Engineering, Department of Chemical CHEMISTRY RESEARCH, 54 (42), 10334‐10349. Engineering, University College London doi:10.1021/acs.iecr.5b01590 7. Yang, L., Liu, S., Tsoka, S., & Papageorgiou, L. G. (2015). Qualifications Sample re‐weighting hyper box classifier for multi‐class data Dipl. Eng. in Chemical Engineering (NTUA, Greece) classification. COMPUTERS AND INDUSTRIAL PhD in Chemical Engineering (Imperial College London) ENGINEERING, 85, 44‐56. doi:10.1016/j.cie.2015.02.022 8. Akgul, O., Mac Dowell, N., Papageorgiou, L. G., & Shah, N. Research Interests (2014). A mixed integer nonlinear programming (MINLP) Computer‐aided process engineering, production planning and supply chain optimisation framework for carbon negative scheduling, supply-chain optimisation, mixed-integer optimisation electricity generation using biomass to energy with CCS (BECCS) in the UK. INTERNATIONAL JOURNAL OF Other Activities GREENHOUSE GAS CONTROL, 28, 189‐202. doi:10.1016/j. Member of IChemE CAPE Subject Group Committee ijggc.2014.06.017 Member of EPSRC Peer Review College 9. Liu, S., Simaria, A. S., Farid, S. S., & Papageorgiou, L. G. International Programme Committee member –ESCAPE21, ESCAPE22 (2014). An Optimisation‐based approach for Editorial board member of Current Opinion in Chemical Engineering biopharmaceutical manufacturing. COMPUTER AIDED Editorial board member of ISRN Chemical Engineering CHEMICAL ENGINEERING, 33, 1183‐1188. doi:10.1016/ B978‐0‐444‐63455‐9.50032‐5 Reviewer for 10. Siganporia, C. C., Ghosh, S., Daszkowski, T., Papageorgiou, Industrial & Engineering Chemistry Research, Computers and L. G., & Farid, S. S. (2014). Capacity planning for batch and Chemical Engineering, AIChE Journal, Chemical Engineering perfusion bioprocesses across multiple biopharmaceutical Research and Design, International Journal of Production facilities. BIOTECHNOLOGY PROGRESS, 30 (3), 594‐606. Economics, European Journal of Operational Research, Computers doi:10.1002/btpr.1860 and Industrial Engineering, Biotechnology Progress. 11. Bennett, L., Kittas, A., Liu, S., Papageorgiou, L. G., & Tsoka, S. (2014). Community Structure Detection for Overlapping Academic Collaborations Modules through Mathematical Programming in Protein Imperial College London, King’s College London, University College Interaction Networks. PLOS ONE, 9 (11), ARTN e112821. London, Technical University of Crete, Aristotle University of doi:10.1371/journal.pone.0112821 Thessaloniki, National Technical University of Athens, University of Wisconsin, Instituto Superior Tecnico. 77
12. Zhang, D., Liu, S., & Papageorgiou, L. G. (2014). Fair cost Research Interests distribution among smart homes with microgrid. ENERGY Development and analysis of algorithms for large scale optimisation CONVERSION AND MANAGEMENT, 80, 498‐508. problems doi:10.1016/j.enconman.2014.01.012 13. Zhang, D., Evangelisti, S., Lettieri, P., & Papageorgiou, L. G. Other Activities (2014). Optimal design of CHP‐based microgrids: Athena‐Swan representative for the Department of Computing Multiobjective optimisation and life cycle assessment. ENERGY, 85, 181–193, doi:10.1016/j.energy.2015.03.036 Reviewer for 14. Liu, S., Yahia, A., & Papageorgiou, L. G. (2014). Optimal Automatica, Computational and Applied Mathematics, Production and Maintenance Planning of Biopharmaceutical Computational Management Science, Computational Optimization Manufacturing under Performance Decay. INDUSTRIAL & and Applications, Computational Statistics and Data Analysis, ENGINEERING CHEMISTRY RESEARCH, 53 (44), Computers and Operations Research, European Journal of 17075‐17091. doi:10.1021/ie5008807 Operational Research, IMA Journal of Management 15. Akgul, O. (2014). Optimisation of Bioenergy Supply Chains Mathematics, Information Processing Letters, INFORMS Journal on (Doctoral dissertation). UCL. Computing, International Review of Economics and Finance, 16. Liu, S., Simaria, A. S., Farid, S. S., & Papageorgiou, L. G. Journal of Computational Finance, Journal of Global Optimization, (2014). Optimising chromatography strategies of antibody Journal of the Operational Research Society, Kybernetika, purification processes by mixed integer fractional Management Science, Mathematics of Operations Research, programming techniques. COMPUTERS AND CHEMICAL Mathematical Programming, Operations Research, Optimization ENGINEERING, 68, 151‐164. doi:10.1016/j. Methods and Software, Quantitative Finance, SIAM Journal on compchemeng.2014.05.005 Control and Optimization. 17. Yang, L., Ainali, C., Tsoka, S., & Papageorgiou, L. G. (2014). Pathway activity inference for multiclass disease classification Academic Collaborations through a mathematical programming optimisation framework. MIT Engineering Systems Division BMC Bioinformatics, 15, 390‐?. doi:10.1186/ Department of Statistical Science Duke University s12859‐014‐0390‐2 Department of Mathematics Edinburgh 18. Al‐Salem, S. M., Papageorgiou, L. G., & Lettieri, P. (2014). School of Pharmacy Nottingham Techno‐economic assessment of thermo‐ chemical treatment (TCT) units in the Greater London area. CHEMICAL Industrial Collaborations ENGINEERING JOURNAL, 248, 253‐263. doi:10.1016/j. IBM cej.2014.03.053 Publications Journal Articles 1. Wright, R., Abraham, E., Parpas, P., and Stoianov, I. Control of Water Distribution Networks with Dynamic DMA Topology using Strictly Feasible Sequential Convex Programming, Journal of Water Resources Research, 2015. 2. P. Parpas, B. Ustun, M. Webster and Q.K. Tran. Importance Sampling in Stochastic Programming with MCMC, INFORMS Journal on Computing, Published Online: April 24, 2015, Page Range: 358 ‐ 377 3. C.P Ho, P. Parpas. Singularly Perturbed Markov Decision Processes: A Multiresolution Algorithm, SIAM Journal on Control and Optimization, 52(6), 3854‐3886, 2014. 4. R. Wright, I. Stoianov, P. Parpas, K. Henderson, J. King. Panos Parpas Adaptive Water Distribution Networks with Dynamically Reconfigurable Topology, Journal of Hydroinformatics, Senior Lecturer, Department of Computing, Imperial College November 2014, 16 (6) 1280‐1301. London 5. P. Parpas, and M. Webster. A stochastic multiscale model for electricity generation capacity expansion, European Journal of Qualifications Operational Research, Volume 232, Issue 2, Pages 359‐374, PhD in Computer Science, Imperial College London (2006) January 2014. MSc in Computer Science, Imperial College London (2002)
Awards and Distinctions MIT CIY Fellowship 78
Book Series Editor Advances in Computational Management Science Advances in Computational Economics
Organiser & Programme Committee Co-chair 17th British‐French‐German Conference on Optimization,15‐17 June 2015, London, http://optimisation.doc.ic.ac.uk/bfg2015/
Activities Associate Director ‐ Research ‐ Centre for Process Systems Engineering, Imperial College
Publications Berc Rustem Journal Articles 1. Kapsos M, Christofides N, Rustem B, 2014, Worst‐case Professor of Computational Methods in Operations robust Omega ratio, European Journal of Operational Research, Department of Computing, Imperial Research, Vol:234, Pages:499‐507 College London 2. Kakouris I, Rustem B, 2014, Robust portfolio optimization with copulas, European Journal of Operational Research, Vol:235, Qualifications Pages:28‐37 B.S. MSc, PhD, FIMA, CMath 3. Kapsos M, Zymler S, Christofides N, et al., 2014, Optimizing the Omega ratio using linear programming, Journal of Computational Finance, Vol:17, Pages:49‐57 Awards and Distinctions President of Society of Computational Economics, 2002‐04 Special issue of Computational Economics in honour of Berc Rustem (V. 27, Nos 2‐3, 2006) Special issue of Computational Management Science in honour of Berc Rustem (V. 11, No. 3, 2014)
Research Interests Optimisation Algorithms, Decision and Design Under Uncertainty, Worst‐Case Design, Stochastic Optimisation
Other Activities Past Managing Editor: Journal of Economic Dynamics & Control: 1987‐2002.
Academic Collaborations Eva Sørensen University of Warwick; University of Florida Professor of Chemical Engineering, Department of Chemical Industrial Collaborations Engineering, University College London Commerzbank; BAe Systems Deputy Head of Department (Education)
Editor Qualifications Automatica (2003‐2015) MSc in Chemical Engineering (NTNU, Norway) Computational Management Science (2002‐2012) PhD in Chemical Engineering (NTNU, Norway) MA in Education (University College London) Editorial Advisory Board Chartered Engineer (CEng) Journal of Economic Dynamics & Control Chartered Scientist (CSci)
Associate Editor Awards and Distinctions Royal Society Proceedings (Series A; 2008‐14) Fellow of the Institution of Chemical Engineers (IChemE) Computational Economics Fellow of the Higher Education Academy (HEA) Journal of Global Optimization IChemE Sustainability Teaching Award (2015) Optimization Letters ExxonMobil Award for Excellence in Teaching Computational Science & Engineering Royal Academy of Engineering (2013) 79
Royal Academy of Engineering Secondment Award (2005) Industrial Collaborations Faculty Teaching Award for Outstanding Achievements in Teaching BioMarin, Eli Lilly Faculty of Engineering, University College London, UK (2001) Publications Postdoctoral Research Scholarship, Norwegian Research Journal Articles Foundation (1995‐1996) 1. Akinmolayan, F., Thornhill, N., & Sorensen, E. (2015). A Research Scholarship, Norwegian Research Foundation (1993‐1994) Detailed Mathematical Modelling Representation of Clean University Scholarship, NTNU, Norway (1990‐1993) Water Treatment Plants. 12TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING AND 25th Secondments EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS BP Refining Technology (2005) ENGINEERING, PT C, 37, 2537‐2542. 2. Patel, N., Bracewell, D., & Sorensen, E. (2015). Dynamic Research Interests Simulation of a Batch Aqueous Two‐Phase Extraction Process Systematic methodologies for mathematical modelling of fluid for α‐Amylase. COMPUTER AIDED CHEMICAL separation processes, in particular, distillation, membrane ENGINEERING, 37, 713‐718. doi:10.1016/ separation, chromatography and hybrids thereof B978‐0‐444‐63578‐5.50114‐6 Optimal design and operation of fluid separation processes 3. Triana, C. F., Fraga, E. S., & Sorensen, E. (2015). Energy Micro‐scale separation processes assessment of different configurations for the ethanol Optimal separation process selection production process from lignocellulosic biomass. COMPUTER Optimal process design, operation and control AIDED CHEMICAL ENGINEERING, 37, 2285‐2290. Education doi:10.1016/B978‐0‐444‐63576‐1.50075‐3 4. Brunazzi, E., Repke, J. ‐. U., & Sorensen, E. (2015). Special Other Activities Issue Distillation and Absorption. CHEMICAL ENGINEERING Editor‐in‐Chief of Chemical Engineering Research & Design RESEARCH & DESIGN, 99, 1. doi:10.1016/j. Member of the European Federation of Chemical Engineers (EFCE) cherd.2015.06.006 Executive Board 5. Close, E. J., Salm, J. R., Bracewell, D. G., & Sorensen, E. Member of EFCE’s Working Party on Fluid Separations (2014). A model based approach for identifying robust Member of IChemE’s Education & Accreditation Board operating conditions for industrial chromatography with Member of Engineering Council’s Engineering Accreditation Board process variability. CHEMICAL ENGINEERING SCIENCE, 116, Member of IChemE’s Education Special Interest Group Committee 284‐295. doi:10.1016/j.ces.2014.03.010 Member of IChemE’s Fluid Separations Special Interest Group 6. Manage, M. N., Sorensen, E., Simons, S., & Brett, D. J. L. Committee (2014). A modelling approach to assessing the feasibility of the Member of American Institute of Chemical Engineers (AIChE) integration of power stations with steam electrolysers. Member of European Society for Engineering Education (SEFI) CHEMICAL ENGINEERING RESEARCH AND DESIGN, 37, Member of EFSRC Peer Review College 2285-2290. doi:10.1016/j.cherd.2014.07.015 Editorial Board Member of Chemical Engineering & Technology 7. Ng, C. K. S., Rousset, F., Valery, E., Bracewell, D. G., & Chair of Organising Committee for Distillation & Absorption Sorensen, E. (2014). Design of high productivity sequential Conference, 2006 multi‐column chromatography for antibody capture. FOOD AND BIOPRODUCTS PROCESSING, 92 (C2), 233‐241. Reviewer for doi:10.1016/j.fbp.2013.10.003 Deutsche Forschungsgemeinschaft (DFG) 8. Close, E., Salm, J., Sorensen, E., & Bracewell, D. G. (2014). Dutch Technology Foundation (STW) Minimalist approach to mechanistic modelling of CONICYT Chile chromatography for intermediate purification and polishing AIChE Journal steps. ABSTRACTS OF PAPERS OF THE AMERICAN Biomass and Bioenergy CHEMICAL SOCIETY, 247. Chemical Engineering & Processing 9. Close, E. J., Salm, J. R., Bracewell, D. G., & Sorensen, E. Chemical Engineering & Technology (2014). Modelling of industrial biopharmaceutical Chemical Engineering Science multicomponent chromatography. CHEMICAL ENGINEERING Computers and Chemical Engineering RESEARCH & DESIGN, 92 (7), 1304‐ 1314. doi:10.1016/j. Journal of Membrane Science cherd.2013.10.022 Journal of the Science of Food and Agriculture Journal of European Engineering Education
Academic Collaborations University College London, Department of Biochemical Engineering Imperial College London, Department of Chemical Engineering Dortmund University, Germany 80
Catalytic Systems”. Journal of Physics: Condensed Matter 27: 013001. [Invited review article] 2. Nikbin, N., Austin, N., Vlachos, D. G., Stamatakis, M. and G. Mpourmpakis (2015). “Catalysis at the Sub‐ Nanoscale: Complex CO Oxidation Chemistry on a Few Au Atoms”. Catalysis Science & Technology 5(1): 134‐141. [Featured on the cover of the issue]. 3. Piccinin, S. and M. Stamatakis (2014). “CO Oxidation on Pd(111): A First‐Principles Based Kinetic Monte Carlo Study”. ACS Catalysis 4: 2143‐2152. 4. Herrmann, S., Stamatakis, M., Andriotis, A. N. and G. Mpourmpakis (2014). “Adsorption Behavior of Noble Metal Clusters and Their Alloys”. Journal of Computational and Theoretical Nanoscience 11(2): 511‐520.
Michail Stamatakis Conference Contributions 1. Piccinin, S. and M. Stamatakis. “Rationalising the Relation Lecturer in Chemical Engineering, Department of Chemical Between Adlayer Structure and Observed Kinetics in CO Engineering, University College London Oxidation on Pd(111)”. American Institute of Chemical Engineers Annual Meeting, Salt Lake, UT, USA. Nov 10, 2015. Qualifications 2. Nikbin, N., Austin, N., Christiansen, M., Vlachos, D. G., MEng in Chemical Engineering (NTUA, Greece) Stamatakis, M. and G. Mpourmpakis. “Unravelling the PhD in Chemical and Biomolecular Engineering (Rice University, USA) Complexity of CO Oxidation Catalysis on Au Nanoclusters”. Short oral presentation within the Discussion symposium 6 ‐ “Oxidation Awards and Distinctions Catalysis ‐ Pollution control”, XII European Congress on Catalysis 2015 ‐ Shortlisted for IChemE Global Awards – Research Project of (EuropaCatXII), Kazan, Russia. Sep 2, 2015. the Year 3. Piccinin, S. and M. Stamatakis. “Coverage Effects for the CO 2013 ‐ Top Reviewer, Computers & Chemical Engineering Oxidation Reaction on O‐Rich Pd(111)”. Inaugural UK 2007 ‐ Outstanding Teaching, Department of Chemical and Catalysis Conference, Loughborough, UK. Jan 9, 2015. Biomolecular Engineering, Rice University 4. Piccinin, S. and M. Stamatakis. “CO Oxidation on O‐Rich 2007 ‐ Kobayashi Fellowship, Department of Chemical and Pd(111): How Does Adlayer Structure Affect Reactivity?”. Biomolecular Engineering, Rice University American Institute of Chemical Engineers Annual Meeting, Atlanta, GA, USA. Nov 17, 2014. Research Interests First‐principles based chemical process modelling tools Invited Lectures and Seminars Computational catalyst engineering 1. Stamatakis, M., Michaelides, A. and E. C. H. Sykes “Catalysis on Single Atom Alloys: Theoretical Investigations and Reviewer for Opportunities”. Energy Frontier Research Center “Integrated ACS Catalysis, ACS Nano, AIChE Journal, Biofabrication, Mesoscale Architectures for Sustainable Catalysis”, Harvard Biophysical Journal, BMC Bioinformatics, Catalysis Science & University, Boston, USA, Oct 16. 2015. [Invited seminar via Technology, Chemical Engineering and Processing: Process teleconference] Intensification, Chemical Engineering Journal, Chemical Engineering 2. M. Stamatakis. “Unravelling the Complexity of Catalytic Research and Design, Computers & Chemical Engineering, Kinetics: Computational Method Development, Applications Industrial & Engineering Chemistry Research, Journal of and Perspective”. Institute of Energy and Process Systems Chemical Physics, Journal of Mathematical Biology, Journal of Engineering, Technische Universität Braunschweig, Germany, Molecular Liquids, Journal of Multiscale Modeling & Simulation Mar 9, 2015. (SIAM), Journal of Physical Chemistry, Physical Review E, Physical 3. M. Stamatakis. “Elucidating the Catalytic Activity of Transition Review Letters, PLoS One, Science Advances, Surface Science. Metal Surfaces via First‐Principles Kinetic Modelling: Method Development and Applications”. International Max Planck Academic Collaborations Research School Functional Interfaces in Physics and Thomas Young Centre, UK Catalysis Hub, University College Chemistry, Workshop “Micro to Macro”, Schloss Ringberg, London, Oxford University, University of Pittsburgh, University of Kreuth, Germany, Feb 12, 2015. Wisconsin at Madison, Tufts University, Integrated Mesoscale 4. M. Stamatakis. “Pushing the Frontiers of Ab Initio Kinetic Architectures for Sustainable Catalysis – Energy, Frontier Research Simulations in Heterogeneous Catalysis”. Centre Blaise Pascal, Centre, Harvard University. École Normale Supérieure de Lyon, France. Oct 24, 2014. 5. M. Stamatakis. “Unravelling the complexity of catalytic Publications kinetics: computational method development, applications Journal Articles and perspective”. Chemical Engineering Department, 1. M. Stamatakis. (2015). “Kinetic Modelling of Heterogeneous University of Newcastle, UK. Oct 21, 2014. 81
6. M. Stamatakis. “Pushing the Frontiers of Ab Initio Kinetic Research interests Simulations in Heterogeneous Catalysis”. Workshop: From the Industrial data analysis using time series analysis and signal Chemical Bond to the Chemical Plant: Computational and processing; Plant‐wide performance assessment; Applications in oil Materials Challenges in Gas Conversion Technologies, and gas, chemicals, bioprocesses and electricity supply. International Centre for Materials Science, Jawaharlal Nehru Centre for Advanced Scientific Research, Jakkur, Bangalore, Other Activities India. Aug 25, 2014. IChemE: Chair of Process Management & Control Subject Group 7. M. Stamatakis. “From Fundamental Understanding to Catalyst Associate Editor of Control Engineering Practice 2006‐2013 Design: Pushing the Frontiers of First‐Principles Kinetic Simulation in Catalysis”. Workshop on International Research and Education Reviewer for on Computational Materials Design in Asia, Department of Automatica Applied Physics, Osaka University, Osaka, Japan. Jun 3, 2014. Biotechnology and Bioengineering 8. M. Stamatakis. “Structure Sensitive or Not? The Effect of Chemical Engineering Research and Design Catalytic Surface Morphology on H2 Production via the Water‐ Computers & Chemical Engineering Gas Shift Reaction”. JSPS Core‐to‐Core Program: A. Advanced Control Engineering Practice Research Networks ‐ International Workshop of Computational IEEE Transactions on Control System Technology Nano‐Materials Design on Green Energy, Toyonaka Campus, Industrial and Engineering Chemistry Research Osaka University, Osaka, Japan. Jun 2, 2014. Journal of Process Control
Academic Collaborations Helmut Schmidt University, Hamburg, Institut für Automatisierungstechnik Imperial College London, Department of Electrical and Electronic Engineering Imperial College London, Department of Mechanical Engineering Norwegian University of Science and Technology – NTNU Trondheim University of Alberta, Department of Chemical and Materials University College London, Department of Biochemical Engineering
Industrial collaborations ABB Corporate Research Nina F. Thornhill FREng ABB Strategic R&D for Oil, Gas and Petrochemicals ESD Training Simulation Professor of Process Automation, Department of Chemical BASF Engineering, Imperial College London, Holder of ABB/Royal BP Exploration and Production Academy of Engineering Research Chair in Process Fingrid Oyj Automation National Grid Statnett SF Qualifications BA in Physics (Oxford University) Publications MSc in Control Systems (Imperial College) Journal Articles PhD (UCL) 1. Cicciotti, M., Xenos, P.D., Bouaswaig, A.E.F., Thornhill, N.F. and Martinez‐Botas, R.F., 2015, Physical modelling of Awards and Distinctions industrial multistage centrifugal compressors for monitoring Fellow of the Royal Academy of Engineering and simulation, Journal of Mechanical Engineering Science, Fellow of the IChemE 229, 3433‐3448. Fellow of the IET 2. Barocio, E., Pal, B.C., Thornhill, N.F., and Messina A.R., 2015, A dynamic mode decomposition framework for global power Secondments system oscillation analysis, IEEE Transactions on Power Marie Curie Fellowship secondment to ABB Corporate Research, Systems, 30, 2902‐2912. Poland, 2012 and 2013 3. Cecilio, I., Ottewill, J.R., Fretheim, H., and Thornhill, N.F., Royal Academy of Engineering Global Research Award with ABB 2015, Multivariate detection of transient disturbances for uni‐ Corporate Research, Norway, April‐September 2005 and multi‐rate systems, IEEE Transactions on Control Systems Royal Academy of Engineering Foresight Award with University of Technology, 23, 1477‐1493, http://dx.doi.org/10.1109/ Alberta, Canada, January‐September 2001 TCST.2014.2377182 Royal Society Industry Fellowship with BP International, 1992‐5 4. Kopanos, G.M., Xenos, P.D., Cicciotti, M., Pistikopoulos, E.N and Thornhill, N.F., 2015, Operational and maintenance 82
planning in networks of compressors in parallel: the air ESCAPE 25), 37, 1583‐1588, 2015. separation plant case, Applied Energy, 146, 453‐470 http:// 8. Romero, D.D., Graven, T‐G., and Thornhill, N.F., 2015, Linking dx.doi.org/10.1016/j.apenergy.2015.01.080 process, electrical and logical connectivity for supported fault 5. Xenos, D.P., Cicciotti, M., Kopanos, G.M., Bouaswaig, A.E.F., diagnosis, Computer Aided Chemical Engineering Kahrs, O., Martinez‐Botas, R.F., and Thornhill, N.F., 2015, (Proceedings of ESCAPE 25), 37, 965‐970, 2015. Optimization of compressors in parallel: Real Time 9. Yang, Y., Velayudhan, A., Thornhill, N.F., and Farid, S.S., 2015, Optimization (RTO) of compressors in chemical plants ‐ An Manufacturability indices for highconcentration monoclonal industrial case study, Applied Energy, 144, 51‐63. antibody formulations, Computer Aided Chemical Engineering 6. Cecilio, I., Ottewill, J., Pretlove, J., and Thornhill, N.F., 2014, (Proceedings of ESCAPE 25), 37, 2147‐2152, 2015. Nearest neighbors method for detecting transient 10. Akinmolayan, F., Thornhill, N.F., Sorensen., E., 2015, A disturbances in process and electromechanical systems, detailed mathematical modelling representation of clean water Journal of Process Control, 24, 1382‐1393. treatment plants, Computer Aided Chemical Engineering 7. Cecilio, I., Ottewill, J.R., Pretlove, J., and Thornhill, N.F., 2014, (Proceedings of ESCAPE 25), 37, 2537‐2542, 2015. Nearest neighbors method for detecting transient 11. Xenos, D.P., Lunde, E., and Thornhill, N.F., 2015, Optimal disturbances in process and electromechanical systems, operation and maintenance of gas compressor stations: an Journal of Process Control, 24, 1382‐1393. integrated framework applied to a large‐scale industrial case, 8. Ikram, W., Petersen, S., Orten, P., and Thornhill, N.F., 2014, ASME Turbo Expo 2015, June 16‐20 2014, Montreal, Adaptive multi‐channel transmission power control for Canada, June 15‐19, 2015. industrial wireless instrumentation, IEEE Transactions on 12. Zhang, Y., Larsson, M., Pal, B.C., and Thornhill, N.F., 2015, Industrial Informatics, 10, 978‐990. Simulation approach to reliability analysis of WAMPAC system, 9. Yang, Y., Farid, S.S., Thornhill, N.F., 2014, Data mining in rapid Presented at IEEE PES ISGT 2015, Washington DC, Feb prediction and debottlenecking of biomanufacturing facilities, 17‐20 2015. Journal of Biotechnology, 179, 17‐25. 13. Romero, D.D., Gravel, T‐G and Thornhill, N.F., 2014, Towards the development of a tool for visualising plantwide Conference Presentations dependencies, 19th IEEE International Conference on 1. Cecilio, I.M., Ottewill, J.R., and Thornhill, N.F., 2015, Adapting Emerging Technologies and Factory Automation, Sept 16‐19th nearest neighbors‐based monitoring methods to irregularly 2014, Barcelona, Spain. sampled measurements, Annual Conference of the PHM 14. Romero, D.D., and Thornhill, N.F., 2014, Integration, Society 2015, San Diego, California, USA, Oct 19‐24. navigation and exploration of plant topology networks using 2. Budinis, S., and Thornhill, N.F., 2015, 2015, Control of the property‐graph model, 2014 IEEE/SICE International centrifugal compressors via model predictive control for Symposium on System Integration, Tokyo, Japan, December enhanced oil recovery applications. 2nd IFAC Workshop on 15‐17, 2014. Paper SuP2C.2, pp743‐748. Automatic Control in Offshore Oil and Gas Production OOGP 15. Ikram, W., Jansson, N., Harvei, T., Aakvaag, N., Halvorsen, I., 2015 — Florianópolis, Brazil, 27–29 May 2015, IFAC‐ Petersen, S., Carlsen, S., and Thornhill, N.F., 2014, Wireless PapersOnLine, 48(6), 9‐14. communication in process control loop: Requirements analysis, 3. Leng, D., and Thornhill, N.F., 2015, Process disturbance industry practices and experimental evaluation, IEEE EFTA cause & effect analysis using Bayesian networks, 9th IFAC Conference, Barcelona, Spain, September 16th‐19th 2014. Symposium on Fault Detection, Supervision and Safety for 16. Arroyo, E., Schulze, D., Christiansen, L., Fay, A., and Thornhill, Technical Processes SAFEPROCESS 2015 — Paris, 2–4 N.F., 2014, Derivation of diagnostic models based on September 2015, IFAC PapersOnLine, 48(21), 1457‐1464. formalized process knowledge, IFAC World Congress, August 4. Cecilio, I.M., Ottewill, J.R., and Thornhill, N.F., 2015, 24‐29, 2014, Cape Town, South Africa, pp 3456‐3464. Determining the propagation path of a disturbance in 17. Dionysios P. Xenos, Nina F. Thornhill, Matteo Cicciotti, Ala E.F. multi‐rate systems, 9th IFAC Symposium on Fault Detection, Bouaswaig, 2014, Preprocessing of raw data for developing Supervision and Safety for Technical Processes steady‐state data‐driven models for optimizing compressor SAFEPROCESS 2015 — Paris, 2–4 September 2015, IFAC stations, UKACC 10th International Conference on Control, PapersOnLine, 48(21), 784‐789. Loughborough, 9‐11 July 2014, 438‐443. 5. Mohd Noor, I., Fretheim, H., Thorud, E., and Thornhill, N.F., 2015, 18. Budinis, S., and Thornhill, N.F., 2014, An integrated control Quantifying the demand‐side response capability of industrial technique foe compressor operation, UKACC 10th International plants to participate in power system frequency control schemes, Conference on Control, Loughborough, 9‐11 July 2014. 444‐449. IEEE PowerTech Eindhoven, June 29‐July 2nd 2015. 19. Ersdal A.E., Fabozzi, D., Imsland, L., and Thornhill, N.F., 2014, 6. Mechleri, E.D., Mac Dowell, N., and Thornhill, N.F., Model Model predictive control for power system frequency control.
predictive control of post‐combustion CO2 capture process taking into account imbalance uncertainty, IFAC World Congress, integrated with a gas‐fired power plant, Computer Aided August 24‐29, 2014, Cape Town, South Africa, pp 981‐986. Chemical Engineering (Proceedings of ESCAPE 25), 37, 20. Xenos, D.P., Cicciotti, M., Bouaswaig, A.E.F., Thornhill,. N.F., and 161‐166, 2015. Martinez‐Botas, R.F., 2014, Modeling and optimization of 7. Budinis, S., and Thornhill, N.F., 2015, Supercritical gas recycle industrial centrifugal compressor stations employing data‐driven analysis for surge control of centrifugal compressors, methods, ASME Turbo Expo 2014, June 16‐20 2014, Computer Aided Chemical Engineering (Proceedings of Düsseldorf, Germany. 83
21. Cicciotti, M., Xenos, D.P., Martinez‐Botas, R.F., Thornhill,. N.F., Asia‐Pacific Journal of Operational Research, Automatica, 2014, Performance monitoring of centrifugal industrial Computational Management Science, The Computer Journal, compressors using meanline modelling and recursive least‐ Computers & Chemical Engineering, Energy Systems, European squares, ASME Turbo Expo 2014, June 16‐20 2014, Journal of Operational Research, IIE Transactions, Journal of Global Düsseldorf, Germany. Optimization, Journal of Network and Systems Management, 22. Cicciotti, M., Xenos, D.P., Bouaswaig, A.E.F., Martinez‐Botas, Management Science, Mathematical Programming, Mathematics of R.F., Manenti, F., Thornhill,. N.F., and Bouaswaig, A.E.F., 2014, Operations Research, Operations Research, Operations Research Simultaneous nonlinear reconciliation and update of parameters Letters, Optimization and Engineering, Optimization Letters, SIAM for online use of first‐principle models: An industrial case‐study Journal on Optimization, Transportation Science, as well as, the IFAC on compressors, 24th European Conference on Computer Aided Conference on Manufacturing, Modelling, Management and Control. Process Engineering (ESCAPE 24). 23. Xenos, D.P., Kopanos, G.M., Cicciotti, M., Pistikopoulos, E.S., Academic Collaborations and Thornhill,. N.F., 2014, Operational optimization of Carnegie Mellon University compressors in parallel considering condition‐based Columbia University maintenance, 24th European Conference on Computer Aided National University of Singapore Process Engineering (ESCAPE 24). Princeton University 24. Mechleri, E.D., Biliyok, C., and Thornhill, N.F., 2014, Dynamic
simulation of post‐combustion CO2 capture with MEA in a gas Publications based power plant, 24th European Conference on Computer Journal Articles Aided Process Engineering (ESCAPE 24). 1. Hanasusanto GA, Kuhn D, Wiesemann W, 2015, K-Adaptability 25. Romero, D., Thornhill, N.F., and Graven, T‐G., 2014, in Two-Stage Robust Binary Programming, Operations Research, Investigations on information‐rich visualizations to explore Vol: 63, Pages: 877-891, ISSN: 0030-364X process connectivity and causality, 24th European Conference 2. Hanasusanto GA, Kuhn D, Wiesemann W, 2015, on Computer Aided Process Engineering (ESCAPE 24). K-Adaptability in Distributionally Robust Binary Programming, Operations Research Letters, Vol: 44, Pages: 6-11, ISSN: 0167-6377 3. Hanasusanto GA, Roitch V, Kuhn D, Wiesemann W, 2015, A distributionally robust perspective on uncertainty quantification and chance constrained programming, Mathematical Programming, Vol: 151, Pages: 35-62, ISSN: 0025-5610 4. Hanasusanto GA, Kuhn, D, Wiesemann, W, 2015, A Comment on “Computational Complexity of Stochastic Programming Problems”, Mathematical Programming, Vol: 159, Pages: 557-569, ISSN: 0025-5610 5. Rujeerapaiboon, N, Kuhn, D, Wiesemann, W, 2015, Robust Growth-Optimal Portfolios, Management Science, Vol: 62, Pages: 2090-2109, ISSN: 1526-5501 6. Wiesemann W, Kuhn D, Sim M, 2014, Distributionally Robust Convex Optimization, Operations Research, Vol: 62(6), Pages: Wolfram Wiesemann 1358-1376
Associate Professor of Management Science and Operations; Invited Lectures and Seminars Fellow of the KPMG Centre for Advanced Business Analytics, 1. Tesco Analytics, Welwyn Garden City (UK), November 2015. Imperial College London 2. Faculty of Economics and Business, KU Leuven (Belgium), October 2015. Qualifications 3. International Workshop on Vehicle Routing under Uncertainty, MSc in Management and Computing at Darmstadt University of TU Dortmund (Germany), September 2015. Technology (2006) 4. Workshop on Generalized Convexity and Set Computation, PhD in Operations Research at Imperial College London (2010) London (UK), August 2015. 5. 21st International MENDEL Conference, Brno (Czech Research Interests Republic), June 2015. Dr Wolfram Wiesemann’s research focuses on the development of 6. School of Mathematics, University of Edinburgh (UK), March 2015. tractable computational methods for the solution of stochastic and 7. School of Mathematics, Computer Science & Engineering, robust optimisation problems, as well as, applications in operations City University London (UK), February 2015. management, finance and health care. 8. London Optimization Workshop, King’s College London (UK), June 2014. Reviewer for 9. Operations Group, Judge Business School, University of Annals of Operations Research, Applied Mathematical Modelling, Cambridge (UK), April 2014 84
CPSE Academics and Staff Directory
Emeritus and Honorary Academics Imperial College London Professor Roger Benson Dr Graham Elkes Department of Chemical Engineering Professor John Perkins Professor Nilay Shah, FREng, Professor of Process Systems Professor Efstratios (Stratos) Pistikopoulos Engineering, Director CPSE Professor Berc Rustem, Professor of Computing Professor Claire S. Adjiman, FREng, Professor of Chemical Professor Paul Rutter Engineering Professor Roger W. H. Sargent Dr Benoît Chachuat, Reader in Process Systems Engineering Dr Peter DiMaggio, Senior Lecturer Professor Amparo Galindo, Professor of Physical Chemistry Dr Gonzalo Guillén-Gosálbez, Reader in Process Systems University College London Engineering Department of Chemical Engineering Dr Adam Hawkes, Senior Lecturer in Energy Systems Department of Chemical Engineering Professor George Jackson, Professor of Chemical Physics Professor I. David Bogle, FREng, Professor of Chemical Engineering Dr Cleo Kontoravdi, Senior Lecturer and Head of UCL Graduate School Dr J Krishnan, Senior Lecturer Dr Vivek Dua, Senior Lecturer Professor Geoffrey C. Maitland, FREng, Professor of Energy Professor Eric S. Fraga, Professor of Process Systems Engineering Engineering Dr Federico Galvanin, Lecturer Professor Athanasios (Sakis) Mantalaris, Professor of BioSystems Professor Lazaros Papageorgiou, Professor of Chemical Engineering Engineering Professor Erich Müller, Professor of Thermodynamics Professor Eva Sørensen, Deputy Head for Education and Professor Professor Costas C. Pantelides, FREng, Professor of Chemical Chemical Engineering Engineering Dr Michail Stamatakis, Lecturer Professor Nina F. Thornhill, FREng, Professor of Process Automation
Department of Biochemical Engineering Business School Dr Alexandros Kiparissides, Lecturer Dr Wolfram Wiesemann, Assistant Professor
Centre for Environmental Policy Dr Niall MacDowell, Lecturer in Energy and Environmental Technology and Policy
Department of Civil and Environmental Engineering Dr James Keirstead, Lecturer
Department of Computing Dr Marc Deisenroth, Lecturer in Statistical Machine Learning Dr Ruth Misener, Lecturer in Computing Dr Panos Parpas, Senior Lecturer
Department of Earth Science & Engineering Professor Nigel Brandon, OBE FREng, Director of the Sustainable Gas Institute (SGI) 85
Academic Staff Dr Do Yeon Kim [email protected] Dr Oleksiy Klymenko [email protected] Professor Nilay Shah (CPSE Director) [email protected] Dr Sergei Kucherenko [email protected] Professor Claire S Adjiman [email protected] Dr Kamal Kuriyan [email protected] Professor I David L Bogle [email protected] Dr Romain Lambert romain.lambert [email protected] Professor Nigel Brandon [email protected] Dr Lianfang Cai [email protected] Dr Benoît Chachuat [email protected] Dr Songsong Liu [email protected] Dr Marc Deisenroth [email protected] Dr Ryan Luong [email protected] Dr Peter DiMaggio [email protected] Dr Evgenia Mechleri [email protected] Dr Vivek Dua [email protected] Dr Marta Moreno Benito [email protected] Professor Eric S Fraga [email protected] Dr Jordan Muscatello [email protected] Professor Amparo Galindo [email protected] Dr HongXing Niu [email protected] Dr Federico Galvanin [email protected] Dr Antonio Marco Pantaleo [email protected] Dr Gonzalo Guillén-Gosálbez [email protected] Dr Remigijus Paulavicius [email protected] Dr Adam Hawkes [email protected] Dr Bharat Kumar Varma Penumathsa [email protected] Professor George Jackson [email protected] Dr Pedro Rivotti [email protected] Dr James Keirstead [email protected] Dr Nouri Samsatli [email protected] Dr Alexandros Kiparissides [email protected] Dr Sheila Samsatli [email protected] Dr Cleo Kontoravdi [email protected] Dr Saurabh Mahesh Kumar Shah [email protected] Dr J Krishnan [email protected] Dr Mahdi Sharifzadeh [email protected] Dr Niall Mac Dowell [email protected] Dr Javier Silvente [email protected] Professor Geoffrey C Maitland [email protected] Dr Edward Smith [email protected] Professor Athanasios Mantalaris [email protected] Dr Si Nga Sou [email protected] Dr Ruth Misener [email protected] Dr Isaac Sugden [email protected] Professor Erich Müller [email protected] Dr Panagiotis Theodorakis [email protected] Professor Costas C Pantelides [email protected] Dr Koen Van Dam [email protected] Professor Lazaros Papageorgiou [email protected] Dr Xiaonan Wang [email protected] Dr Panos Parpas p.parpasATimperial.ac.uk Dr Yang Yang [email protected] Prof Berc Rustem [email protected] Dr Ioannis Zacharoudiou [email protected] Professor Eva Sørensen [email protected] Dr Di Zhang [email protected] Dr Michail Stamatakis [email protected] Dr Sophie Zemenides [email protected] Professor Nina F Thornhill [email protected] Dr Fessehaye Zemichael [email protected] Dr Wolfram Wiesemann [email protected] Support Staff Emeritus and Honorary Academics CPSE Administration and Research Officer Dr Graham Elkes [email protected] Miss Cristina Romano [email protected] Professor John Perkins [email protected] Professor Efstratios N Pistikopoulos [email protected] CPSE External Relations Manager Professor Paul Rutter [email protected] Miss Senait Selassie [email protected] Professor Roger W.H. Sargent [email protected] Head of Computing Services Research Associates Mr Graham Stuart [email protected]
Dr Salvador Acha Izquierdo [email protected] Dr Aiman Alam Nazki [email protected] Dr Adrian Aguirre [email protected] Dr John Blamey [email protected] Dr Carlos Henrique Correia Braga [email protected] Dr Sara Fadda [email protected] Dr Sara Giarola [email protected] Dr Miao Guo [email protected] Dr Andrew Haslam [email protected] Dr Carmelo Herdes Moreno [email protected] Dr Philip Jedrzejewski [email protected] Dr Maria Guadalupe Serratos Jimenez [email protected] 86
CPSE Research Project List Professor Paul Rutter
“Continuing advances in computing power and artificial intelligence will extend the reach, capability and usability of process systems engineering to help industry and society deal with the challenges that confront us all in the next century.” 87
CPSE Research Project List
Ali Salim Al Qahtani Mark C. Allenby Technical, Economic and Environmental Impact of Future Fuel Development of a Bio‐Inspired in Silico‐in Vitro Platform: Towards Formulations Personalised Healthcare through Optimisation of a Bone Marrow Supervisor: Prof Nilay Shah Mimicry Bioreactor Start date: October 2010 Supervisors: Prof Athanasios Mantalaris and Prof Efstratios Finish date: October 2016 Pistikopoulos Start date: October 2013 Adam Alexandros Finish date: April 2017 Integrated Heating and Power Systems for Dwellings Supervisor: Prof Eric Fraga Nihal Almuraikhi Start date: October 2011 Stem Cell Bioprocessing Finish date: May 2016 Supervisor: Prof Athanasios Mantalaris Start date: October 2010 Folashade Akinmolayan Finish date: August 2016 Real‐Time Operational Risk Management through Advanced Multi‐Scale Modelling Diego Alonso Martinez Supervisors: Prof Eva Sørensen and Prof Nina Thornhill Profiling the Methylome Targets of Histone Lysine Start date: August 2011 Methyltransferases Finish date: July 2016 Supervisor: Dr Peter DiMaggio Start date: September 2013 Yasmeen Aldawsari Finish date: September 2017 Systems Analysis of Transport Decarbonisation Options Supervisor: Prof Nilay Shah Tamador Alsobaie Start date: September 2013 Stem Cell Bioprocessing Finish date: September 2017 Supervisor: Prof Athanasios Mantalaris Start date: May 2012 Amos B. Aleji Finish date: January 2016 Experimental and Modelling of Viscosity and Density of Mixtures of Crude oil + CO2 Daniel E. Aluma Supervisors: Prof Geoffrey Maitland and Prof Martin Trusler Model‐Based Optimisation of the Operation of Integrated Natural Start date: February 2011 Gas Production & Processing Networks Finish date: August 2016 Supervisors: Prof Nilay Shah and Prof Costas Pantelides Start date: November 2012 Sakhr Alhuthali Finish date: November 2016 Understanding the Interplay Between Upstream and Downstream Bioprocessing by a Sequence of Mathematical Models Oluwamayowa Amusat Supervisor: Dr Cleo Kontoravdi Design of Renewables‐Based Integrated Energy Systems for Start date: October 2015 Stand‐Alone Continuous Processes Finish date: May 2019 Supervisor: Prof Eric Fraga Start date: November 2013 Finish date: November 2016 88
Benaiah Uchechukwu Anabaraonye Hao Bian Experimental and Modelling Studies of Reservoir Minerals Studies of Production, Inhibition and Exchange Processes for
Dissolution Following CO2 Injection Gas Hydrates Supervisor: Prof Geoffrey Maitland Supervisor: Prof Geoffrey Maitland Start date: October 2013 Start date: July 2013 Finish date: October 2016 Finish date: June 2016
William Ashworth Moiz Bohra Systems Biology of the Liver Optimising Qatar’s Transition to Renewable Energy through Supervisors: Prof David Bogle and Dr Nathan Davies (UCL Division Model-Based Analysis of Medicine) Supervisor: Professor Nilay Shah Start date: October 2013 Start date: April 2016 Finish date: May 2017 End date: December 2019
Vitali Avagyan Aaron Borg Essays on Risks and Profitability of the UK Electricity Industry Characterising the Function of Chromatin‐Modifying Protein Supervisors: Prof Berc Rustem, Dr Panos Parpas and Prof Richard Complexes Green Supervisor: Dr Peter DiMaggio Start date: October 2012 Start date: August 2012 Finish date: September 2016 Finish date: July 2016
Vijay Avinash Jonathan Bosch Integration of Decentralised Energy Resources with the Electricity Renewable Energy Potentials for Global Energy Systems Models Balancing System Supervisor: Dr Adam Hawkes Supervisor: Dr Adam Hawkes Start date: October 2014 Start date: April 2014 Finish date: June 2017 Finish date: April 2017 Susana Isabel Brito dos Santos Styliani Avraamidou In Vitro Erythropoiesis in a 3D Bone Marrow Biomimicry: Distributed Multi‐Parametric Model Protective Control Applied on Reproducing Physiologic Biochemical and Microenvironmental Biological and Biomedical Processes Factors Involved in Red Blood Cell Formation Supervisors: Prof Athanasios Mantalaris and Prof Efstratios Supervisors: Prof Athanasios Mantalaris and Dr Nicki Panoskaltsis Pistikopoulos Start date: March 2014 Start date: October 2014 Finish date: March 2018 Finish date: April 2018 Pantelis Broukos Radu Baltean-Lugojan Urban Energy Systems Structure Exploitation in Large Scale Non‐Convex Optimization Supervisors: Prof Nilay Shah and Dr James Keirstead Supervisor: Dr Ruth Misener Start date: September 2012 Start date: April 2015 Finish date: December 2015 Finish date: April 2018 Sara Budinis Davide Bascone ENERGY‐SMARTOPS Modelling and Optimisation of the Nuclear Fuel Cycle Supervisor: Prof Nina Thornhill Supervisor: Prof Eric Fraga Start date: September 2011 Start date: March 2015 Finish date: December 2015 Finish date: March 2019 Gizem Buldum Asif Bhatti Bacterial Cellulose Production Synthesis and Design of Biological Systems Under Uncertainty Supervisor: Prof Athanasios Mantalaris Supervisor: Dr Vivek Dua Start date: October 2011 Start date: October 2010 Finish date: October 2016 Finish date: September 2016 Gonzalo Bustos-Turu Integrated Modelling of Future Urban Energy Systems Supervisor: Prof Nilay Shah Start date: March 2014 Finish date: March 2017 89
Renato Cabral A Quantification of the Value Provided by Flexible Oxy‐Combustion Constanza Cumicheo Melgarejo CCS to the UK Energy System The Combination of Bioenergy, Natural Gas and CCS for Negative Supervisor: Dr Niall Mac Dowell Emissions Start date: October 2015 Supervisors: Dr Niall Mac Dowell and Prof Nilay Shah Finish date: September 2018 Start date: November 2015 Finish date: June 2019 Claudio Calabrese Viscosity and Density of Reservoir Fluids under CO2 Addition Ibrahim Daher Supervisors: Prof Geoffrey Maitland and Prof Martin Trusler The Effect of Salt Precipitation on Permeability and Porosity in Start date: November 2013 Fractured Carbonates System Finish date: October 2016 Supervisors: Dr John Crawshaw and Prof Geoffrey Maitland Start date: January 2013 Andres Calderon Vargera Finish date: January 2017 Optimisation of Biomass‐Based Supply Chains Supervisor: Prof Lazaros Papageorgiou Matthew Thomas Darby Start date: May 2013 First‐Principles Simulations of Molecular Phenomena on Bimetallic Finish date: April 2017 Hydrogenation Catalysts Supervisor: Dr Michail Stamatakis Raúl Calvo Serrano Start date: October 2013 Process Optimisation and Sustainability Analysis Finish date: May 2016 Supervisor: Dr Gonzalo Guillén Gosálbez Start date: April 2016 Pedro de Oliveira Filho Finish date: March 2019 Development, Implementation and Application of a Language for Modelling Uncertainty in Design and Process Optimisation Juan Sebastian Campos Salazar Supervisor: Prof Eric Fraga Multilevel Optimization for Large Scale Semidefinite Programming Start date: October 2015 Supervisor: Dr Panos Parpas Finish date: September 2019 Start date: October 2013 Finish date: October 2017 Aikaterini Diamanti Design of Optimal Reaction Conditions: Temperature and Solvent Vassilis M. Charitopoulos Effects Uncertainty-Aware Planning and Scheduling in the Process Supervisors: Prof Claire Adjiman and Prof Amparo Galindo Industries Start date: October 2012 Supervisors: Dr Vivek Dua and Prof Lazaros Papageorgiou Finish date: October 2016 Start date: September 2015 Finish date: September 2019 David Dorantes Romero Capture and Analysis of Process Connectivity and Topology Florence Yu Tsing Chow Supervisor: Prof Nina Thornhill The Effect of Impurities on the Interfacial Tension between Start date: October 2012
CO2 and Reservoir Fluids Finish date: September 2018 Supervisor: Prof Geoffrey Maitland Start date: September 2012 Daniel Kunisch Eriksen Finish date: September 2015 Molecular Modelling and Thermodynamics of Oil Systems in the
Presence of Brine and CO2 Cheng-Ta Chu Supervisors: Prof Amparo Galindo and Prof George Jackson Global Electricity Sector Decarbonisation Modelling Start date: October 2012 Supervisor: Dr Adam Hawkes Finish date: August 2016 Start date: October 2015 Finish date: October 2019 Karl Fairhurst Molecular Simulation of Associating Fluids, Using a Combination of Edward James Close Molecular Dynamics (MD) and Monte Carlo (MC) Simulations, with The Derivation of Bioprocess Understanding from Mechanistic Coarse‐Grained Models Models of Chromatography Supervisors: Prof Erich Müller and Prof George Jackson Supervisors: Prof Eva Sørensen and Dr Dan Bracewell (UCL) Start date: October 2015 Start date: September 2010 Finish date: September 2019 Finish date: October 2014 90
Sara Febra Yingjian Guo Molecular Systems Engineering Methods for Solubility Prediction Modelling the Role of Gas T&D Infrastructure in Future Low Carbon of Active Pharmaceutical Ingredients Energy Systems Supervisor: Prof Amparo Galindo Supervisor: Dr Adam Hawkes Start date: March 2014 Start date: October 2015 Finish date: March 2017 Finish date: April 2019
Christina-Anna Gatsiou Clara Heuberger Crystal Structure Prediction Energy System Optimisation and Technology Valuation, in Particular Supervisors: Prof Claire Adjiman and Prof Costas Pantelides of Flexible CCS Start date: March 2012 Supervisors: Dr Niall Mac Dowell, Prof Nilay Shah and Dr Iain Staffell Finish date: March 2016 Start date: January 2015 Finish date: June 2018 Anastasia Georgiou Generation of Mineralised Cellular Constructs Using Mouse Ching-Pang Ho Embryonic Stem Cells Encapsulated in Alginate Hydrogels and Optimization Algorithms for Multiscale Models Cultured within a Custom‐Made Rotating Wall Vessel Perfusion Supervisors: Dr Panos Parpas and Dr Wolfram Wiesemann Bioreactor Start date: October 2012 Supervisor: Prof Athanasios Mantalaris Finish date: September 2016 Start date: October 2009 Finish date: January 2016 Rayane Hoballah Solubility of Gases in Water or Brines at Reservoir Conditions Solomos Georgiou Supervisors: Prof Martin Trusler and Prof Geoffrey Maitland Decarbonisation of Food Supply Chains: A Holistic Approach Start date: December 2012 Supervisors: Prof Nilay Shah and Dr Christos Markides Finish date: February 2017 Start date: October 2015 Finish date: September 2019 Vahan Hovhannisyan Multi‐Level Convex Optimisation in Machine Learning Cher Hui Goey Supervisors: Dr Panos Parpas and Dr Stefanos Zafeiriou Cascading Effects in Bioprocessing: The impact of Cell Culture Start date: September 2013 Environment on Mammalian Cell Behaviour and Host Cell Protein Finish date: September 2017 Species Supervisor: Dr Cleo Kontoravdi Sei Howe Start date: February 2013 Singularly Perturbed Optimal Control Systems Finish date: February 2017 Supervisor: Dr Panos Parpas Start date: October 2012 Smitha Gopinath Finish date: March 2017 Developing a Methodology for Integrated Molecular and Process Design Panatpong Hutacharoen Supervisors: Prof George Jackson, Prof Claire Adjiman and Prof Prediction of Octanol‐Water Partition Coefficients of Active Amparo Galindo Pharmaceutical Ingredients by the SAFT‐γ Mie Group‐Contribution Start date: September 2013 Equation of State Finish date: March 2017 Supervisors: Prof Claire Adjiman, Prof Amparo Galindo and Prof George Jackson Edward Graham Start date: May 2013 The Integrated Molecular and Process Modelling of Carbon Dioxide Finish date: October 2016 Capture in Amine Solvents Supervisors: Prof Claire Adjiman, Prof George Jackson and Prof Frederike Jaeger Amparo Galindo Flow of Fluids through Porous Media with Application to Start date: December 2014 Membranes: from the Molecular to the Continuum Scale Finish date: December 2017 Supervisors: Prof Erich Müller and Prof Omar Matar Start date: October 2014 Boram Gu Finish date: September 2017 Modelling of RO Membrane Process Performance and Transport Phenomena for Performance Analysis and Optimisation Supervisors: Prof Claire Adjiman and Prof Yun Xu Start date: April 2014 Finish date: October 2016 91
Francisca Jalil Vega Qingyuan Kong Novel Approaches to Modelling Whole System Heat An Optimisation‐Based Framework for the Conceptual Design of Decarbonisation Reaction‐Separation Processes Supervisor: Dr Adam Hawkes Supervisor: Prof Nilay Shah Start date: December 2013 Start date: October 2014 Finish date: April 2017 Finish date: June 2018
Elnaz Jamili Georgia Kouyialis Model‐Based Optimal Control of Non‐Viral Gene Delivery Exploiting Symmetry in Mixed Integer Non‐Linear Optimisation Supervisors: Dr Vivek Dua and Dr Michail Stamatakis Supervisor: Dr Ruth Misener Start date: November 2012 Start date: October 2014 Finish date: October 2016 Finish date: September 2017
Erin Johnson Gabriel Lau UK Green Gas: Exploring Sustainable Gas Potential as a Relevant Droplets: From Molecular Nanoclusters to the Atmospheric Aerosols Low Carbon Energy Stream Supervisor: Prof George Jackson Supervisor: Professor Nilay Shah Start date: March 2013 Start date: October 2015 Finish date: September 2016 Finish date: October 2018 Georgia Lazarou Suela Jonuzaj Modelling the Effect of pH on the Thermodynamics of Electrolyte Optimisation Approaches to Mixture Design Solutions Using the Statistical Associating Fluid Theory Supervisor: Prof Claire Adjiman Supervisors: Prof Claire Adjiman, Prof Amparo Galindo, Prof George Start date: August 2013 Jackson and Prof Erich Müller Finish date: July 2017 Start date: October 2013 Finish date: September 2017 Ashkan Kavei Development and Application of Stack Segmented Fuel Cell Duncan Leeson Systems Energy Cascading in Complex Downstream Operations Supervisors: Prof Nigel Brandon, Dr Gregory J Offer, Dr Billy Wu and Supervisors: Prof Nilay Shah, Dr Paul Fennell and Dr Niall Mac Dr Vladimir Yufit Dowell Start date: September 2015 Start date: October 2014 Finish date: September 2019 Finish date: April 2018
Nikolaos Kazazakis David Leng Development of Deterministic Global Optimization Methods Fault Propagation, Detection and Analysis in Process Systems Supervisor: Prof Claire Adjiman Supervisor: Prof Nina Thornhill Start date: September 2012 Start date: September 2013 Finish date: August 2016 Finish date: June 2018
Esma Koca Yunjie Liao Product Release Strategies in Single and Multiple Markets Development and Validation of a Model of Energy Differential Supervisors: Dr Wolfram Wiesemann and Prof Tommaso Valletti Production Across the Liver Sinusoid Start date: October 2013 Supervisors: Prof David Bogle and Dr Nathan Davies (UCL Division Finish date: September 2017 of Medicine) Start date: October 2015 Mariya Koleva Finish date: September 2019 Optimisation of Wastewater Systems Supervisor: Prof Lazaros Papageorgiou Phantisa Limleamthong Start date: March 2013 Systematic Computer Aided Process Engineering Tools for the Finish date: December 2016 Optimal Design and Planning of Sustainable Chemical Processes Supervisor: Dr Gonzalo Guillén‐Gosálbez Clea Kolster Start date: April 2016 Multi‐Scale Modelling and Analysis of the Dynamic CO2 Injection Finish date: March 2019 and Storage Supervisors: Dr Niall Mac Dowell and Dr Sam Krevor Start date: October 2014 Finish date: October 2017 92
Tom Lindeboom Miten Mistry Molecular Origins of the Thermodynamic Properties, Phase Integrating Mixed Integer Nonlinear Programming and Satisfiability Separation Behaviour and Structure of Biomolecules in Aqueous Modulo Theories for Next‐Generation Optimisation Algorithms Solutions Supervisor: Dr Ruth Misener Supervisors: Prof George Jackson and Prof Amparo Galindo Start date: October 2015 Start date: October 2015 Finish date: September 2019 Finish date: September 2019 Nur Amirah Izzati Mohd Noor Maximilian Lularevic Industrial Smart Grid A Combined Multi‐Scale Modelling and Experimental Investigation Supervisor: Prof Nina Thornhill of the Effects of Lactate Metabolism on Mammalian Cell Start date: September 2013 Bioprocessing Finish date: September 2017 Supervisors: Dr Alexandros Kiparissides and Dr Cleo Kontoravdi Start date: September 2015 Eðvald Moller Finish date: September 2019 Model Development and Evaluation Supervisors: Prof Nilay Shah and Prof Lazaros Papageorgiou Robert MacFarlane Start date: November 2010 The Production of 3‐Dimensional Mineralised Cellular Implants for Finish date: January 2018 Bone Tissue Engineering Applications Supervisor: Prof Athanasios Mantalaris Ioana Nascu Start date: October 2013 Advances in Explicit/Multi‐Parametric Model Predictive Control with Finish date: September 2017 applications in Anaesthesia Supervisor: Prof Efstratios Pistikopoulos Nikiforos Maragkos Start date: January 2012 Novel Composite Materials Design for Economic Infrastructure Finish date: April 2016 Equipment Supervisors: Prof Efstratios Pistikopoulos and Prof Alexander Dimitrios Nerantzis Bismarck Deterministic Global Optimisation Techniques Start date: October 2009 Supervisor: Prof Claire Adjiman Finish date: PENDING (Interruption of Studies) Start date: September 2012 Finish date: September 2016 Amit M. Manthanwar Multiscale Design, Robust Optimisation and Robust Model Andreas Nikolaou Predictive Control of Fuel Cell Energy Systems Multi‐Scale Modelling of Light‐limited Growth in Microalgae Supervisor: Prof Efstratios Pistikopoulos Production Systems Start date: February 2012 Supervisor: Dr Benoît Chachuat Finish date: May 2016 Start date: November 2011 Finish date: November 2015 Kristian Mc Caul A Multiscale and Multiphysics Modelling Framework for Processes Richard Oberdieck Involved in Production of Fuels from Lignocelluloses Theoretical and Algorithmic Developments in Multi‐Parametric Supervisors: Prof Nilay Shah, Dr Cleo Kontoravdi and Prof Yun Xu Optimization and Control Start date: September 2013 Supervisors: Prof Athanasios Mantalaris and Prof Efstratios Finish date: March 2017 Pistikopoulos Start date: September 2013 Calum J McIntosh Finish date: August 2016 Controlling the Quality of Novel Glycoprotein Therapeutics Supervisor: Dr Cleo Kontoravdi Funmilayo Olabode Start date: November 2015 Parameter Estimation Using Neural Networks Finish date: November 2019 Supervisor: Dr Vivek Dua Start date: January 2014 Govind Menon Finish date: January 2019 Elucidating Temporal and Spatial Aspects of Cellular Information Processing Supervisor: Dr J Krishnan Start date: October 2014 Finish date: April 2018 93
Anna Panteli Ana Luz Quiroga Campano Biorenewable Value Chain Optimization with Multi‐Layered Value Mathematical Modelling and Experimental Validation for the Chains and Advanced Analytics Optimization and Control of Mammalian Cell Culture Systems Supervisor: Prof Nilay Shah Supervisor: Prof Athanasios Mantalaris Start date: July 2014 Start date: October 2012 Finish date: July 2017 Finish date: October 2016
Maria Papathanasiou Sadia Rahman Multi‐Parametric Model Based Control for Nonlinear, Periodic Computer Simulation of Coarse‐Grained Models of Ionic Surfactants Systems: An Application to Biopharmaceutical Processes Supervisors: Prof Erich Müller, Prof Amparo Galindo and Prof Supervisors: Prof Efstratios Pistikopoulos and Prof Athanasios George Jackson Mantalaris Start date: September 2012 Start date: November 2012 Finish date: August 2016 Finish date: November 2016 Jai Rajyaguru Nehal Patel Rigorous Numerical Analysis with Polynomial Models: Applications Comparison of Chromatographic and Two‐Phase Separations for to Implicit and Differential‐Algebraic Equations Novel Biopharmaceuticals Supervisor: Dr Benoît Chachuat Supervisor: Prof Eva Sørensen Start date: October 2011 Start date: September 2012 Finish date: February 2016 Finish date: September 2016 Shakeel Ramjanee Carlos Perez-Galvan Integrated Production Modelling Systems for the Upstream Oil & Global Optimisation of Dynamic Process Systems Gas Industry and Field Performance Supervisor: Prof David Bogle Supervisors: Prof Nilay Shah, Dr Benoît Chahuat and Prof Ann Start date: January 2013 Muggeridge Finish date: December 2016 Start date: October 2015 Finish date: October 2018 Nikola Peric Towards the Next Generation of Algorithms and Software for Global Krisztian Ronaszegi Optimization of Energy and Environmental Systems Water Splitting for Hydrogen Production for Use in Dwellings Supervisor: Dr Benoît Chachuat Supervisor: Prof Eric Fraga Start date: October 2013 Start date: May 2011 Finish date: September 2016 Finish date: September 2016
Stefan Pfenninger Daniel Ross Multi‐Scale Energy Systems Modelling Multi‐Scale Simulation of the Transport of Hydrocarbons in Porous Supervisor: Dr James Keirstead Engine Deposits Start date: October 2012 Supervisor: Prof Erich Müller Finish date: September 2015 Start date: October 2012 Finish date: September 2016 Catalina Pino Electrodes by Design ‐ Improved Electrodes for Redox Flow Victor Sanchez Tarre Batteries A Combined Multi‐Scale Modelling and Experimental Approach to Supervisor: Prof Nigel Brandon Optimize Algal Culture Efficiency at the Metabolic, Process and Start date: October 2015 Reactor Design Level Finish date: September 2019 Supervisors: Dr Alexandros Kiparissides and Dr Gary Lye Start date: September 2015 Channarong Puchongkawarin Finish date: September 2019 Optimisation‐Based Methodology for the Design and Operation of Sustainable Wastewater Treatment Facilities Symeon Savvopoulos Supervisors: Dr Benoît Chachuat and Prof David Stuckey Mathematical Modelling of Chronic Lymphocytic Leukaemia Start date: November 2011 Supervisor: Prof Athanasios Mantalaris Finish date: February 2016 Start date: March 2014 Finish date: March 2018 94
Oliver Schmidt Muxin Sun Innovation Potential of Energy Storage Technologies and the Value Design of Tractable MPC and NCO‐Tracking Controllers using of Storage in Low‐Carbon Energy Systems Parametric Programming Supervisor: Dr Adam Hawkes Supervisors: Prof Efstratios Pistikopoulos and Dr Benoît Chachuat Start date: October 2015 Start date: September 2013 Finish date: October 2018 Finish date: September 2016
Marzia Sesini Thapanar Suwanmajo Gas Storage and its Strategic Coordination within the EU Market: A Modelling and Systems Engineering Approaches for Elucidating Qualitative and Quantitative Approach Dynamics and Information Processing of Multi-Site Phosphorylation Supervisor: Dr Adam Hawkes Systems Start date: October 2015 Supervisor: Dr Jawahar Krishnan Finish date: October 2019 Start date: April 2011 Finish date: July 2016 Olivia Sloan Combined CO2 Storage and Enhanced Oil Recovery in the North Asma Tahlawi Sea. Rock Heterogeneity and Flow in Geologic Systems with Low Development of a Three‐Dimensional Biomimicry for the Culture of
Flow Potential – applications to Subsurface CO2 Injection Normal and Abnormal Haematopoietic Cells Supervisors: Dr Sam Krevor, Dr Niall McDowell and Dr Jerome Supervisor: Prof Athanasios Mantalaris Neufeld (University of Cambridge) Start date: September 2013 Start date: October 2015 Finish date: November 2017 Finish date: October 2019 Naveed Tariq Bowen Song Model Based Analysis of Low Carbon Energy Pathways based on Solid Oxide Fuel Cell Natural Gas Supervisor: Prof Nigel Brandon Supervisor: Prof Nilay Shah and Prof Paul Fennell Start date: October 2015 Start date: October 2012 Finish date: October 2018 Finish date: October 2016
Si Nga Sou Quang Tran Understanding the Impact of Bioprocess Conditions on Monoclonal Sampling Algorithms for Stochastic Programming Using Importance Antibody Glycosylation in Mammalian Cell Cultures through Sampling and Markov Chain Monte Carlo Experimental and Computational Analyses Supervisors: Prof Berc Rustem and Dr Panos Parpas Supervisors: Dr Cleo Kontoravdi and Dr Karen M Polizzi Start date: October 2011 Start date: October 2011 Finish date: June 2016 Finish date: February 2016 Cristian Triana Graham Stevenson Heat Integration for Bioethanol Process from Lingocellulosic Engineering Ceramic Scaffold Electrodes for Solid Oxide Fuel Cells Biomass and Solid Oxide Electrolyzer Cells Supervisors: Prof Eric Fraga and Prof Eva Sørensen Supervisor: Prof Nigel Brandon Start date: October 2011 Start date: September 2015 Finish date: June 2016 Finish date: September 2019 Argyro Tsipa Flávio Strutzel Connecting Transcriptional Regulation to Microbial Growth Kinetics Economically Optimal Integrated Process and MPC Control Design in Cultures of Pseudomonas Putida Supervisor: Prof David Bogle Supervisors: Prof Athanasios Mantalaris and Prof Efstratios Start date: October 2014 Pistikopoulos Finish date: September 2018 Start date: September 2011 Finish date: February 2016 Carlos Ricardo Suarez Heredia Development of a Combined Mathematical and Experimental Platform for the Design and Optimisation of Metabolically Balanced Nutrient Supplementation Strategies in Semi‐Continuous Mammalian Cell Cultures Supervisor: Dr Alexandros Kyparissidis Start date: April 2016 Finish date: March 2020 95
Chonlatep Usaku An Integrated Experimental and Modelling Approach for the Study of Apoptosis in GS‐NS0 Cell Cultures Supervisors: Prof Athanasios Mantalaris and Prof Efstratios Pistikopoulos Start date: October 2010 Finish date: March 2016
Mario Villanueva Set‐Theoretic Methods for Analysis, Estimation and Control of Nonlinear Systems Supervisor: Dr Benoît Chachuat Start date: October 2011 Finish date: September 2015
Yukun Wang Set Theoretic Approaches in Estimation and Optimization of Large‐ Scale Process Systems Supervisor: Dr Benoît Chachuat Start date: October 2015 Finish date: March 2019
Carmen Wouters Optimal Design and Regulation of Residential Distributed Energy Systems Supervisors: Prof Eric Fraga and Dr Adrian James Start date: February 2013 Finish data: February 2017
Dionysios Xenos ENERGY‐SMARTOPS Supervisor: Prof Nina Thornhill Start date: September 2011 Finish date: December 2015
Iván Ying Xuan Electricity Demand‐Side Response from Heavy Industrial Loads Supervisor: Prof Nina Thornhill Start date: October 2015 Finish date: October 2018
Joseph Yao Biomass Combustion with In‐Situ CO2 Capture Via the Calcium Loop Supervisor: Prof Geoffrey Maitland Start date: October 2012 Finish date: September 2015
Mauricio Javier Zamorano Mosnaim Human Dental Pulp Stem Cells: Characterisation and In Vitro 3D Bone Ontogenesis Supervisor: Prof Athanasios Mantalaris Start date: January 2012 Finish date: February 2016 96
PhD Graduates 2014–2015
On completion of their studies, our graduates quickly find employment in many sectors including: industry, academia, consulting, finance and software.
Dr Ozlem Akgul Dr Alireza Behjousiar Optimisation of Bioenergy Supply Chains In Situ FRET Biosensors for the In Vivo Measurement of Important Supervisors: Professor Lazaros Papageorgiou and Professor Metabolites during Cell Culture Nilay Shah Supervisors: Dr Cleo Kontoravdi and Dr Karen Polizzi Employer: Baringa Employer: Gap year
Dr Aiman Alam Nazki Dr Shane Cadogan
Elucidating the Spatial Organization and Control of Information Diffusion of CO2 in Fluids Relevant to Carbon Capture, Utilisation Processing in Cell Signalling Networks: From Network and and Storage Enzymatic Building Blocks to Concrete Systems Supervisors: Professor Geoffrey Maitland and Professor Martin Supervisor: Dr Jawahar Krishnan Trusler Employer: Awarded EPSRC Prize Fellowship, Imperial College Employer: Erlangen Graduate School in Advanced Optical London Technologies (SAOT) Friedrich‐Alexander‐Universität Erlangen‐ Nürnberg (FAU), Germany Dr Saif Al Ghafri Phase Behaviour and Physical Properties of Reservoir Fluids Under Dr Inês Da Mata Cecilio Addition of Carbon Dioxide Study of Simulated Moving Bed Reactor (SMBR) for Para‐Xylene Supervisors: Professor Martin Trusler and Professor Geoffrey Production Maitland Supervisor: Professor Nina Thornhill Employer: Research Fellow, University of Western Australia Employer: Research Scientist at Schlumberger
Dr Ahmed Alhajaj Dr Emily Chapman
Multiscale Design and Analysis of CO2 Capture, Transport and Micro‐Model Pore‐Scale Flow Studies of Fluid Displacement in
Storage Networks Carbonate Rock with Application to CO2 Storage Supervisors: Professor Nilay Shah, Professor Nigel Brandon and Supervisor: Dr Edo Boek Professor Velisa Vesovic Employer: Associate at Expand Research ‐ A Company of the Employer: Masdar Institute Boston Consulting Group
Dr Christos Argyropoulos Dr Donald O’Donoghue A Combined Immersed Boundary/Phase‐Field Method for Mathematical Modelling of Ion Transport in Healthy and Cystic Simulating Two‐Phase Pipe flows Fibrosis Human Airway Epithelia Supervisor: Dr Edo Boek Supervisor: Dr Vivek Dua Employer: Postdoctoral Research Associate at Texas A&M Employer: Quantitative Analyst at Irish Life Investment Managers University and Mary Kay O’ Connor Process Safety Center at Qatar Dr Pongsathorn Dechatiwongse Dr Joakim Beck A Study of the Growth and Hydrogen Production of Cyanothece sp. Efficient Targeted Optimisation for the Design of Pressure Swing ATCC 51142
Adsorption Systems for CO2 Capture in Power Plants Supervisors: Professor Klaus Hellgardt and Professor Supervisor: Professor Eric Fraga Geoffrey Maitland Employer: Department of Statistical Science, UCL Employer: Walailak University, Nakhon Si Thammarat, Thailand 97
Dr Nasim Elahi Dr Alexandra Krieger Multiscale Modelling of Carbon Capture and Storage Modelling, Optimisation and Explicit Model Predictive Control of Supervisor: Professor Nilay Shah Anaesthesia Drug Delivery Systems Employer: Research Associate, Supply Chain Optimisation, Machine Supervisor: Professor Efstratios Pistikopoulos learning, Data Science, Imperial College Employer: Research Assistant, RWTH Aachen, Germany
Dr Hendrik Frentrup Dr Sarantos Kyriakopoulos Molecular Simulation of Diffusive Mass Transport in Porous Materials Amino Acid Metabolism in Chinese Hamster Ovary Cell Culture Supervisor: Professor Erich Müller Supervisor: Dr Cleo Kontoravdi Employer: R&D Engineer, Dyson Employer: BioMarin, Ireland
Dr Maria Fuentes Gari Dr Romain Lambert A Mathematical Model of Cell Cycle Heterogeneity for Personalizing Approximation Methodologies for Explicit Model Predictive Control Leukemia Chemotherapy of Complex Systems Supervisor: Professor Athanasios Mantalaris Supervisor: Professor Efstratios Pistikopoulos Employer: Process System Enterprise Limited (PSE), London, Employer: Research Associate, Imperial College London United Kingdom Dr Olga Lobanova Dr Zara Ganase Development of Coarse‐Grained Force Fields from a Molecular An Experimental Study on the Effects of Solvents on the Rate and Based Equation of State for Thermodynamic and Structural Selectivity of Organic Reactions Properties of Complex Fluids Supervisors: Professor Clare Adjiman, Professor Amparo Galindo Supervisors: Professor George Jackson and Professor Erich Müller and Professor Alan Armstrong (Imperial Chemistry) Employer: Syngenta Employer: Intel, Ireland Dr Duy Luong Dr David Garcia Munzer Optimisation for Image Processing Cell Cycle Heterogeneity Study by an Integrated Modelling and Supervisors: Professor Berc Rustem, Dr Panos Parpas and Experimental Approach Professor Daniel Rueckert Supervisors: Professor Athanasios Mantalaris and Professor Employer: Imperial College London Efstratios Pistikopoulos Employer: Postdoctoral Associate, Novartis, Switzerland Dr Mithila Manage An Investigation into the Feasibility of Integrating Intermediate‐ Dr Michael Hadjiyiannis Temperature Solid Oxide Electrolysers with Power Plants Decision Under Uncertainty: Problems in Control Theory, Robust Supervisor: Professor Eva Sørensen Optimization and Game Theory Employer: NNL Supervisor: Dr Daniel Kuhn Employer: A company in Cyprus Dr Jan Marzinek Molecular Dynamics Modelling of Skin and Hair Proteins Dr Grani Hanasusanto Supervisors: Professor Athanasios Mantalaris and Professor Decision Making Under Uncertainty: Robust and Data‐Driven Efstratios Pistikopoulos Approaches Employer: Postdoctoral Research Fellow, A *STAR/National Supervisors: Dr Daniel Kuhn and Dr Wolfram Wieseman University of Singapore, Singapore Employer: Faculty member at UT Austin Dr Ali Mehdizadeh Dr Abdihakim Hassan Food Industry Supply Chain Planning with Product Quality Indicators Modelling Solvent Mixtures and their Effects on Reactions Supervisor: Professor Nilay Shah Supervisors: Professor Claire Adjiman and Professor Amparo Employer: Strategy and Operation, Supply Chain (Consultancy), Galindo Birds Eye Iglo Limited Employer: Shell Dr Silvia Padula Dr Philip Jedrzejewski Capacity Planning for Water Supply Networks A Platform for the Optimisation of Metabolic Pathways for Supervisor: Professor Lazaros Papageorgiou Glycosylation to Achieve a Narrow and Targeted Glycoform Employer: University of Manchester Distribution Supervisor: Dr Cleo Kontoravdi Employer: Gap year 98
Dr Antonio Marco Pantaleo Dr Saurabh Mahesh Kumar Shah Perspectives on the Role of Bioenergy for Distributed Heat and Multi-Scale Pore Imaging of Multiphase Flow in Porous Media Power Generation Supervisor: Dr Edo Boek Supervisor: Professor Nilay Shah Employer: QCCSRC Experimental Officer, Imperial College London Employer: Imperial College London Dr Roochi Solanki Dr Nicole Papaioannou Modelling of a Two‐Phase Thermofluidic Oscillator for Low‐Grade Environmental Impact Assessment and Optimization of Urban Heat Utilisation Energy Systems Supervisors: Dr Christos Markides and Professor Amparo Galindo Supervisor: Professor Nilay Shah Employer: Carbon Credentials Employer: Principal Consultant ‐ Gas & Power at Wood Mackenzie Dr Ioanna Stefani Dr Olga Parkes Unravelling the Progression of Endoplasmic Reticulum Stress in Defining a Comprehensive Methodology for Sustainability Familial Alzheimer’s Disease Assessment of Mega‐Event Projects Supervisors: Dr Cleo Kontoravdi and Dr Karen Polizzi Supervisors: Professor David Bogle and Professor Paola Lettieri Employer: ICON (Medical Consulting) Employer: UK Dept of Energy and Climate Change Dr Ailing Teo Dr Eleni Pefani Exploring New Bioprocess Considerations for Cardiomyogenesis of Modelling and Optimisation Based Drug Delivery Systems for the Embryonic Stem Cells Treatment of Acute Myeloid Leukemia (AML) Supervisors: Professor Athanasios Mantalaris and Professor Lim Supervisors: Professor Efstratios Pistikopoulos and Dr Nicki Mayasari Panoskaltsis Employer: Associate Patent Examiner at Intellectual Property Office Employer: GlaxoSmithKline, Stevenage, United Kingdon of Singapore
Dr Cheng Peng Dr Lingjian Yang Chemical Interactions Between CO2 Acidified Aqueous Fluids and Optimisation Approaches for Data Mining in Biological Systems Carbonate Minerals Supervisor: Professor Lazaros Papageorgiou Supervisors: Professor Geoffrey Maitland, Professor Martin Trusler Employer: PDRA at University of Manchester and Dr John Crawshaw Employer: Shell Global Solutions International B.V., Rijswijk, Dr Lara Yaroson Netherlands Force Field Parameters from the SAFT Equation of State for the Molecular Simulation of Fused Molecules Dr Vladimir Roitch Supervisors: Professor George Jackson, Professor Erich Müller and Optimisation Applied to Cloud Computing Professor Amparo Galindo Supervisors: Dr Daniel Kuhn and Dr Wolfram Wiesemann Employer: Syngenta Employer: Lecturer at City University Dr Stamatina Zavitsanou Dr Pedro Rivotti Modeling and Multi Parametric Control Drug Delivery Systems for Multi‐Parametric Programming and Explicit Model Predictive Control Diabetes Type 1 of Hybrid Systems Supervisor: Professor Efstratios Pistikopoulos Supervisor: Professor Efstratios Pistikopoulos Employer: Postdoctoral Research Scholar at SEAS, Harvard Employer: Research Associate, Imperial College London University
Dr Cyrus Siganporia Production Planning for Biopharmacicals Supervisor: Professor Lazaros Papageorgiou Employer: Research Associate, University College London
Dr Erini Siougkrou Systematic Methods for Solvent Design: Towards Better Reactive Processes Supervisors: Professor Claire Adjiman and Professor Amparo Galindo Employer: Marie Curie Research Fellow at National Technical University of Athens
Centre for Process Systems Engineering (CPSE), Imperial College London, Roderic Hill Building, South Kensington Campus, London SW7 2AZ, Email: [email protected], Phone: +44 (0)207 594 6605/11 http://www3.imperial.ac.uk/centreforprocesssystemsengineering