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User Guide of Computational Facilities
Physical Chemistry Unit Departament de Quimica User Guide of Computational Facilities Beta Version System Manager: Marc Noguera i Julian January 20, 2009 Contents 1 Introduction 1 2 Computer resources 2 3 Some Linux tools 2 4 The Cluster 2 4.1 Frontend servers . 2 4.2 Filesystems . 3 4.3 Computational nodes . 3 4.4 User’s environment . 4 4.5 Disk space quota . 4 4.6 Data Backup . 4 4.7 Generation of SSH keys for automatic SSH login . 4 4.8 Submitting jobs to the cluster . 5 4.8.1 Typical queue system commands . 6 4.8.2 HomeMade scripts . 6 4.8.3 Create your own submit script . 6 4.8.4 Submitting Parallel Calculations . 7 5 Available Software 9 5.1 Chemisty software . 9 5.2 Development Software . 10 5.3 How to use the software . 11 5.4 Non-default environments . 11 6 Your Linux Workstation 11 6.1 Disk space on your workstation . 12 6.2 Workstation Data Backup . 12 6.3 Running virtual Windows XP . 13 6.3.1 The Windows XP Environment . 13 6.4 Submitting calculations to your dekstop . 13 6.5 Network dependent structure . 14 7 Your WindowsXP Workstation 14 7.1 Workstation Data Backup . 14 8 Frequently asked questions 14 1 Introduction This User Guide is aimed to the standard user of the computer facilities in the ”Unitat de Quimica Fisica” in the Universitat Autnoma de Barcelona. It is not assumed that you have a knowledge of UNIX/Linux. However, you are 1 encouraged to take a close look to the linux guides that will be pointed out. -
Supporting Information
Electronic Supplementary Material (ESI) for RSC Advances. This journal is © The Royal Society of Chemistry 2020 Supporting Information How to Select Ionic Liquids as Extracting Agent Systematically? Special Case Study for Extractive Denitrification Process Shurong Gaoa,b,c,*, Jiaxin Jina,b, Masroor Abroc, Ruozhen Songc, Miao Hed, Xiaochun Chenc,* a State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, 102206, China b Research Center of Engineering Thermophysics, North China Electric Power University, Beijing, 102206, China c Beijing Key Laboratory of Membrane Science and Technology & College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, PR China d Office of Laboratory Safety Administration, Beijing University of Technology, Beijing 100124, China * Corresponding author, Tel./Fax: +86-10-6443-3570, E-mail: [email protected], [email protected] 1 COSMO-RS Computation COSMOtherm allows for simple and efficient processing of large numbers of compounds, i.e., a database of molecular COSMO files; e.g. the COSMObase database. COSMObase is a database of molecular COSMO files available from COSMOlogic GmbH & Co KG. Currently COSMObase consists of over 2000 compounds including a large number of industrial solvents plus a wide variety of common organic compounds. All compounds in COSMObase are indexed by their Chemical Abstracts / Registry Number (CAS/RN), by a trivial name and additionally by their sum formula and molecular weight, allowing a simple identification of the compounds. We obtained the anions and cations of different ILs and the molecular structure of typical N-compounds directly from the COSMObase database in this manuscript. -
Multiscale Simulation of Laser Ablation and Processing of Semiconductor Materials
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2012 Multiscale Simulation Of Laser Ablation And Processing Of Semiconductor Materials Lalit Shokeen University of Central Florida Part of the Materials Science and Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Doctoral Dissertation (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation Shokeen, Lalit, "Multiscale Simulation Of Laser Ablation And Processing Of Semiconductor Materials" (2012). Electronic Theses and Dissertations, 2004-2019. 2420. https://stars.library.ucf.edu/etd/2420 MULTISCALE SIMULATION OF LASER PROCESSING AND ABLATION OF SEMICONDUCTOR MATERIALS by LALIT SHOKEEN Bachelor of Science (B.Sc. Physics), University of Delhi, India, 2006 Masters of Science (M.Sc. Physics), University of Delhi, India, 2008 Master of Science (M.S. Materials Engg.), University of Central Florida, USA, 2009 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Mechanical, Materials and Aerospace Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida, USA Fall Term 2012 Major Professor: Patrick Schelling © 2012 Lalit Shokeen ii ABSTRACT We present a model of laser-solid interactions in silicon based on an empirical potential developed under conditions of strong electronic excitations. The parameters of the interatomic potential depends on the temperature of the electronic subsystem Te, which is directly related to the density of the electron-hole pairs and hence the number of broken bonds. -
Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds
J. Comput. Chem. Jpn., Vol. 15, No. 1, pp. 13–21 (2016) ©2016 Society of Computer Chemistry, Japan Technical Paper Quantitative Evaluation of Dissociation Mechanisms in Phenolphthalein and the Related Compounds Toshihiko HANAI Health Research Foundation, Research Institute for Production Development 4F, 15 Shimogamo-morimoto-cho, Sakyo-ku, Kyoto 606-0805, Japan e-mail: [email protected] (Received: October 11, 2015; Accepted for publication: April 14, 2016; Online publication: May 6, 2016) Computational chemistry programs were evaluated as aids to teaching qualitative analytical chemistry. Compu- tational chemical calculations can predict absorption spectra, thus enabling the modeling of indicator dissociation mechanisms by different computational chemical programs using a personal computer. An updated MNDO program among 51 programs was found to be the best predictor to explain the dissociation mechanisms of isobenzofuranones and sulfonephthaleins. Unknown dissociation constants were predicted from atomic partial charges instead of Ham- mett's constants. Keywords: Quantitative analysis of dissociation mechanisms, Isobenzofuranone, Sulfonephthalein, Computational chemistry 1 Introduction the absorption wavelength and electron density changes were not well described. The dissociation mechanisms, maximum How to quantitatively teach qualitative analytical chemistry is wavelengths, and electron density maps of isobenzofuranones a very important subject for analytical chemists. Previously, a and sulfonephthaleins were, therefore, evaluated by in silico method to teach molecular interaction mechanisms in chroma- analysis despite the anticipated poor precision. The experimen- tography was quantitatively achieved using molecular mechan- tally measured dissociation of phenolphthalein is described ics and MOPAC programs [1]. Furthermore, the reaction mech- using four dissociation structures, where the ionization of two anisms of highly sensitive detections were also quantitatively phenolic hydroxyl groups converts the neutral molecular form described [2,3]. -
Computer-Assisted Catalyst Development Via Automated Modelling of Conformationally Complex Molecules
www.nature.com/scientificreports OPEN Computer‑assisted catalyst development via automated modelling of conformationally complex molecules: application to diphosphinoamine ligands Sibo Lin1*, Jenna C. Fromer2, Yagnaseni Ghosh1, Brian Hanna1, Mohamed Elanany3 & Wei Xu4 Simulation of conformationally complicated molecules requires multiple levels of theory to obtain accurate thermodynamics, requiring signifcant researcher time to implement. We automate this workfow using all open‑source code (XTBDFT) and apply it toward a practical challenge: diphosphinoamine (PNP) ligands used for ethylene tetramerization catalysis may isomerize (with deleterious efects) to iminobisphosphines (PPNs), and a computational method to evaluate PNP ligand candidates would save signifcant experimental efort. We use XTBDFT to calculate the thermodynamic stability of a wide range of conformationally complex PNP ligands against isomeriation to PPN (ΔGPPN), and establish a strong correlation between ΔGPPN and catalyst performance. Finally, we apply our method to screen novel PNP candidates, saving signifcant time by ruling out candidates with non‑trivial synthetic routes and poor expected catalytic performance. Quantum mechanical methods with high energy accuracy, such as density functional theory (DFT), can opti- mize molecular input structures to a nearby local minimum, but calculating accurate reaction thermodynamics requires fnding global minimum energy structures1,2. For simple molecules, expert intuition can identify a few minima to focus study on, but an alternative approach must be considered for more complex molecules or to eventually fulfl the dream of autonomous catalyst design 3,4: the potential energy surface must be frst surveyed with a computationally efcient method; then minima from this survey must be refned using slower, more accurate methods; fnally, for molecules possessing low-frequency vibrational modes, those modes need to be treated appropriately to obtain accurate thermodynamic energies 5–7. -
A Comparative Study of the Efficiency of HCV NS3/4A Protease Drugs
Life Sciences 217 (2019) 176–184 Contents lists available at ScienceDirect Life Sciences journal homepage: www.elsevier.com/locate/lifescie A comparative study of the efficiency of HCV NS3/4A protease drugs against different HCV genotypes using in silico approaches T ⁎ Ahmed A. Ezat , Wael M. Elshemey Biophysics Department, Faculty of Science, Cairo University, 12613 Giza, Egypt ARTICLE INFO ABSTRACT Keywords: Aims: To investigate the efficacy of Direct Acting Antivirals (DAAs) in the treatment of different Hepatitis C HCV Virus (HCV) genotypes. NS3/4A protease Main methods: Homology modeling is used to predict the 3D structures of different genotypes while molecular Molecular docking docking is employed to predict genotype – drug interactions (Binding Mode) and binding free energy (Docking Homology modeling Score). Key findings: Simeprevir (TMC435) and to a lesser degree MK6325 are the best drugs among the studied drugs. The predicted affinity of drugs against genotype 1a is always better than other genotypes. P2–P4 macrocyclic drugs show better performance against genotypes 2, 3 and 5. Macrocyclic drugs are better than linear drugs. Significance: HCV is one of the major health problems worldwide. Until the discovery of DAAs, HCV treatment faced many failures. DAAs target key functional machines of the virus life cycle and shut it down. NS3/4A protease is an important target and several drugs have been designed to inhibit its functions. There are several NS3/4A protease drugs approved by Food and Drug Administration (FDA). Unfortunately, the virus exhibits resistance against these drugs. This study is significant in elucidating that no one drug is able to treat different genotypes with the same efficiency. -
Starting SCF Calculations by Superposition of Atomic Densities
Starting SCF Calculations by Superposition of Atomic Densities J. H. VAN LENTHE,1 R. ZWAANS,1 H. J. J. VAN DAM,2 M. F. GUEST2 1Theoretical Chemistry Group (Associated with the Department of Organic Chemistry and Catalysis), Debye Institute, Utrecht University, Padualaan 8, 3584 CH Utrecht, The Netherlands 2CCLRC Daresbury Laboratory, Daresbury WA4 4AD, United Kingdom Received 5 July 2005; Accepted 20 December 2005 DOI 10.1002/jcc.20393 Published online in Wiley InterScience (www.interscience.wiley.com). Abstract: We describe the procedure to start an SCF calculation of the general type from a sum of atomic electron densities, as implemented in GAMESS-UK. Although the procedure is well known for closed-shell calculations and was already suggested when the Direct SCF procedure was proposed, the general procedure is less obvious. For instance, there is no need to converge the corresponding closed-shell Hartree–Fock calculation when dealing with an open-shell species. We describe the various choices and illustrate them with test calculations, showing that the procedure is easier, and on average better, than starting from a converged minimal basis calculation and much better than using a bare nucleus Hamiltonian. © 2006 Wiley Periodicals, Inc. J Comput Chem 27: 926–932, 2006 Key words: SCF calculations; atomic densities Introduction hrstuhl fur Theoretische Chemie, University of Kahrlsruhe, Tur- bomole; http://www.chem-bio.uni-karlsruhe.de/TheoChem/turbo- Any quantum chemical calculation requires properly defined one- mole/),12 GAMESS(US) (Gordon Research Group, GAMESS, electron orbitals. These orbitals are in general determined through http://www.msg.ameslab.gov/GAMESS/GAMESS.html, 2005),13 an iterative Hartree–Fock (HF) or Density Functional (DFT) pro- Spartan (Wavefunction Inc., SPARTAN: http://www.wavefun. -
3D-Printing Models for Chemistry
3D-Printing Models for Chemistry: A Step-by-Step Open-Source Guide for Hobbyists, Corporate ProfessionAls, and Educators and Student in K-12 and Higher Education Poster Elisabeth Grace Billman-Benveniste+, Jacob Franz++, Loredana Valenzano-Slough+* +Department of Chemistry, Michigan Technological University, ++Department of Mechanical Engineering, Michigan Technological University *Corresponding Author References 1. “LulzBot TAZ 5.” LulzBot, 14 Aug. 2018, www.lulzbot.com/store/printers/lulzbot-taz-5 2. Gaussian 16, Revision B.01, Frisch, M. J.; Trucks, G. W.; Schlegel, H. B.; Scuseria, G. E.; Robb, M. A.; Cheeseman, J. R.; Scalmani, G.; Barone, V.; Petersson, G. A.; Nakatsuji, H.; Li, X.; Caricato, M.; Marenich, A. V.; Bloino, J.; Janesko, B. G.; Gomperts, R.; Mennucci, B.; Hratchian, H. P.; Ortiz, J. V.; Izmaylov, A. F.; Sonnenberg, J. L.; Williams-Young, D.; Ding, F.; Lipparini, F.; Egidi, F.; Goings, J.; Peng, B.; Petrone, A.; Henderson, T.; Ranasinghe, D.; ZakrzeWski, V. G.; Gao, J.; Rega, N.; Zheng, G.; Liang, W.; Hada, M.; Ehara, M.; Toyota, K.; Fukuda, R.; HasegaWa, J.; Ishida, M.; NakaJima, T.; Honda, Y.; Kitao, O.; Nakai, H.; Vreven, T.; Throssell, K.; Montgomery, J. A., Jr.; Peralta, J. E.; Ogliaro, F.; Bearpark, M. J.; Heyd, J. J.; Brothers, E. N.; Kudin, K. N.; Staroverov, V. N.; Keith, T. A.; Kobayashi, R.; Normand, J.; Raghavachari, K.; Rendell, A. P.; Burant, J. C.; Iyengar, S. S.; Tomasi, J.; Cossi, M.; Millam, J. M.; Klene, M.; Adamo, C.; Cammi, R.; Ochterski, J. W.; Martin, R. L.; Morokuma, K.; Farkas, O.; Foresman, J. B.; Fox, D. J. Gaussian, Inc., Wallingford CT, 2016. 3. -
Implementation of Methods to Accurately Predict Transition Pathways and the Underlying Potential Energy Surface of Biomolecular Systems
IMPLEMENTATION OF METHODS TO ACCURATELY PREDICT TRANSITION PATHWAYS AND THE UNDERLYING POTENTIAL ENERGY SURFACE OF BIOMOLECULAR SYSTEMS By DELARAM GHOREISHI A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2019 c 2019 Delaram Ghoreishi I dedicate this dissertation to my mother, my brother, and my partner. For their endless love, support, and encouragement. ACKNOWLEDGMENTS I am thankful to my advisor, Adrian Roitberg, for his guidance during my graduate studies. I am grateful for the opportunities he provided me and for allowing me to work independently. I also thank my committee members, Rodney Bartlett, Xiaoguang Zhang, and Alberto Perez, for their valuable inputs. I am grateful to the University of Florida Informatics Institue for providing financial support in 2016, allowing me to take a break from teaching and focus more on research. I like to acknowledge my group members and friends for their moral support and technical assistance. Natali di Russo helped me become familiar with Amber. I thank Pilar Buteler, Sunidhi Lenka, and Vinicius Cruzeiro for daily conversations regarding science and life. Pancham Lal Gupta was my cpptraj encyclopedia. I thank my physicist colleagues, Ankita Sarkar and Dustin Tracy, who went through the intense physics coursework with me during the first year. I thank Farhad Ramezanghorbani, Justin Smith, Kavindri Ranasinghe, and Xiang Gao for helpful discussions regarding ANI and active learning. I also thank David Cerutti from Rutgers University for his help with NEB implementation. I thank Pilar Buteler and Alvaro Gonzalez for the good times we had camping and climbing. -
Computational Studies on Carbohydrates: I. Density Functional Ab Initio Geometry Optimization on Maltose Conformations
Computational Studies on Carbohydrates: I. Density Functional Ab Initio Geometry Optimization on Maltose Conformations F. A. MOMANY, J. L. WILLETT Plant Polymer Research, National Center for Agricultural Utilization Research, USDA, Agricultural Research Service, 1815 N. University St., Peoria, Illinois 61604 Received 10 September 1999; accepted 10 May 2000 ABSTRACT: Ab initio geometry optimization was carried out on 10 selected conformations of maltose and two 2-methoxytetrahydropyran conformations using the density functional denoted B3LYP combined with two basis sets. The 6-31G∗ and 6-311CCG∗∗ basis sets make up the B3LYP/6-31G∗ and B3LYP/6-311CCG∗∗ procedures. Internal coordinates were fully relaxed, and structures were gradient optimized at both levels of theory. Ten conformations were studied at the B3LYP/6-31G∗ level, and five of these were continued with ∗∗ full gradient optimization at the B3LYP/6-311CCG level of theory. The details of the ab initio optimized geometries are presented here, with particular attention given to the positions of the atoms around the anomeric center and the effect of the particular anomer and hydrogen bonding pattern on the maltose ring structures and relative conformational energies. The size and complexity of the hydrogen-bonding network prevented a rigorous search of conformational space by ab initio calculations. However, using empirical force fields, low-energy conformers of maltose were found that were subsequently gradient optimized at the two ab initio levels of theory. Three classes of conformations were studied, as defined by the clockwise or counterclockwise direction of the hydroxyl groups, or a flipped conformer in which the -dihedral is rotated by ∼180◦.Different combinations of ! side-chain rotations gave energy differences of more than 6 kcal/mol above the lowest energy structure found. -
Kingston University London the Antibiotic Resistance Growth Plate
Kingston University London The Antibiotic Resistance Growth Plate (ARGP) as an experimental evolution tool to explore the phenotypic and genotypic mutational pathways underlying the emergence of antimicrobial resistance in Escherichia coli. A thesis submitted in partial fulfilment for the degree of Doctor of Philosophy By Lucky Bonnie Lucia CULLEN Faculty of Science, Engineering and Computing February 2019 Declaration This thesis entitled ‘The Antibiotic Resistance Growth Plate (ARGP)’ as an experimental evolution tool to explore the phenotypic and genotypic mutational pathways underlying the emergence of antimicrobial resistance in Escherichia coli’ is based upon the work conducted in the Faculty of Science, Engineering and Computing at Kingston University London and in collaboration with Dr Philip Aldridge at Newcastle University and Katie Hopkins and Neil Woodford from Public Health England. All the work described is the candidate’s own original work unless otherwise stated. None of the work presented has been submitted for another degree internally or externally. i Acknowledgements At the start of this PhD I had a dream, a dream which could have never been accomplished without the support of many people. Firstly, I would like to express my sincere appreciation to my director of studies Professor Mark Fielder, your provision, guidance and unconditional belief in my potential has contributed significantly to the completion of this thesis. I would also like to acknowledge the overwhelming support received from, Dr Scott Lawton, Camilla Eldridge and Ben Jones, your wealth of knowledge and expertise in the field of evolutionary biology and bioinformatics has assisted greatly in concluding the work within this PhD. I would also like to praise the incredible multidisciplinary support received at Kingston University, specifically that from Dr Gary-Forster Wilkins, Dr Adam Le Gresley, Dr Brian Rooney, Dr James Denholm-Price and Richard Giddens. -
Conformational Analysis with Scigress
CONFORMATIONAL ANALYSIS WITH SCIGRESS During this laboratory period you will use two computational chemistry methods to carry out conformational analysis experiments on butane, cyclohexanol and cis-1,3-cyclohexanediol. Mechanics is a method which uses classical Newtonian mechanics to compute the energies of molecules. Bonds are treated as springs and atoms as balls attached to these springs. MOPAC is a method which uses quantum mechanics to calculate the energies of molecules and determine their optimum geometries and other properties; MOPAC is an acronym for Molecular Orbital PACkage Conformational Energy of Butane 1. Build and beautify a molecule of butane. Save your drawing with the name "butane." 2. Highlight (select) the four carbon atoms (in order). All other atoms should be grayed out. Choose Adjust→Dihedral Angle from the menu bar. Select “Define Geometry Label” and “Search”. Apply and then click OK. The workspace containing the butane molecule will reappear with the dihedral angle written in blue across it. The letter S will appear next to the value of the dihedral angle indicating that it is a search label. Re-save the drawing 3. Choose Experiment→New from the menu bar; the experiment dialog box should appear. Choose chemical sample conformations (CAChe 5.0 experiments) from the “Property of” box. Choose optimized map in the “Property” box. Click Start (if an error appears click OK and re-try). 4. Two adjacent windows should appear presenting the results of the calculation. The left window is a plot of potential energy versus dihedral angle for the butane molecule. The graph colors represent the relative energies of the butane molecule with various dihedral angles.