Electron Energy-Loss Spectroscopy: DFT Modelling and Application to Experiment
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Introducing ONETEP: Linear-Scaling Density Functional Simulations on Parallel Computers Chris-Kriton Skylaris,A) Peter D
THE JOURNAL OF CHEMICAL PHYSICS 122, 084119 ͑2005͒ Introducing ONETEP: Linear-scaling density functional simulations on parallel computers Chris-Kriton Skylaris,a) Peter D. Haynes, Arash A. Mostofi, and Mike C. Payne Theory of Condensed Matter, Cavendish Laboratory, Madingley Road, Cambridge CB3 0HE, United Kingdom ͑Received 29 September 2004; accepted 4 November 2004; published online 23 February 2005͒ We present ONETEP ͑order-N electronic total energy package͒, a density functional program for parallel computers whose computational cost scales linearly with the number of atoms and the number of processors. ONETEP is based on our reformulation of the plane wave pseudopotential method which exploits the electronic localization that is inherent in systems with a nonvanishing band gap. We summarize the theoretical developments that enable the direct optimization of strictly localized quantities expressed in terms of a delocalized plane wave basis. These same localized quantities lead us to a physical way of dividing the computational effort among many processors to allow calculations to be performed efficiently on parallel supercomputers. We show with examples that ONETEP achieves excellent speedups with increasing numbers of processors and confirm that the time taken by ONETEP as a function of increasing number of atoms for a given number of processors is indeed linear. What distinguishes our approach is that the localization is achieved in a controlled and mathematically consistent manner so that ONETEP obtains the same accuracy as conventional cubic-scaling plane wave approaches and offers fast and stable convergence. We expect that calculations with ONETEP have the potential to provide quantitative theoretical predictions for problems involving thousands of atoms such as those often encountered in nanoscience and biophysics. -
Natural Bond Orbital Analysis in the ONETEP Code: Applications to Large Protein Systems Louis P
WWW.C-CHEM.ORG FULL PAPER Natural Bond Orbital Analysis in the ONETEP Code: Applications to Large Protein Systems Louis P. Lee,*[a] Daniel J. Cole,[a] Mike C. Payne,[a] and Chris-Kriton Skylaris[b] First principles electronic structure calculations are typically Generalized Wannier Functions of ONETEP to natural atomic performed in terms of molecular orbitals (or bands), providing a orbitals, NBO analysis can be performed within a localized straightforward theoretical avenue for approximations of region in such a way that ensures the results are identical to an increasing sophistication, but do not usually provide any analysis on the full system. We demonstrate the capabilities of qualitative chemical information about the system. We can this approach by performing illustrative studies of large derive such information via post-processing using natural bond proteins—namely, investigating changes in charge transfer orbital (NBO) analysis, which produces a chemical picture of between the heme group of myoglobin and its ligands with bonding in terms of localized Lewis-type bond and lone pair increasing system size and between a protein and its explicit orbitals that we can use to understand molecular structure and solvent, estimating the contribution of electronic delocalization interactions. We present NBO analysis of large-scale calculations to the stabilization of hydrogen bonds in the binding pocket of with the ONETEP linear-scaling density functional theory package, a drug-receptor complex, and observing, in situ, the n ! p* which we have interfaced with the NBO 5 analysis program. In hyperconjugative interactions between carbonyl groups that ONETEP calculations involving thousands of atoms, one is typically stabilize protein backbones. -
Density Functional Theory (DFT)
Herramientas mecano-cuánticas basadas en DFT para el estudio de moléculas y materiales en Materials Studio 7.0 Javier Ramos Biophysics of Macromolecular Systems group (BIOPHYM) Departamento de Física Macromolecular Instituto de Estructura de la Materia – CSIC [email protected] Webinar, 26 de Junio 2014 Anteriores webinars Como conseguir los videos y las presentaciones de anteriores webminars: Linkedin: Grupo de Química Computacional http://www.linkedin.com/groups/Química-computacional-7487634 Índice Density Functional Theory (DFT) The Jacob’s ladder DFT modules in Maretials Studio DMOL3, CASTEP and ONETEP XC functionals Basis functions Interfaces in Materials Studio Tasks Properties Example: n-butane conformations Density Functional Theory (DFT) DFT is built around the premise that the energy of an electronic system can be defined in terms of its electron probability density (ρ). (Hohenberg-Kohn Theorem) E 0 [ 0 ] Te [ 0 ] E ne [ 0 ] E ee [ 0 ] (easy) Kinetic Energy for ????? noninteracting (r )v (r ) dr electrons(easy) 1 E[]()()[]1 r r d r d r E e e2 1 2 1 2 X C r12 Classic Term(Coulomb) Non-classic Kohn-Sham orbitals Exchange & By minimizing the total energy functional applying the variational principle it is Correlation possible to get the SCF equations (Kohn-Sham) The Jacob’s Ladder Accurate form of XC potential Meta GGA Empirical (Fitting to Non-Empirical Generalized Gradient Approx. atomic properties) (physics rules) Local Density Approximation DFT modules in Materials Studio DMol3: Combine computational speed with the accuracy of quantum mechanical methods to predict materials properties reliably and quickly CASTEP: CASTEP offers simulation capabilities not found elsewhere, such as accurate prediction of phonon spectra, dielectric constants, and optical properties. -
Compact Orbitals Enable Low-Cost Linear-Scaling Ab Initio Molecular Dynamics for Weakly-Interacting Systems Hayden Scheiber,1, A) Yifei Shi,1 and Rustam Z
Compact orbitals enable low-cost linear-scaling ab initio molecular dynamics for weakly-interacting systems Hayden Scheiber,1, a) Yifei Shi,1 and Rustam Z. Khaliullin1, b) Department of Chemistry, McGill University, 801 Sherbrooke St. West, Montreal, QC H3A 0B8, Canada Today, ab initio molecular dynamics (AIMD) relies on the locality of one-electron density matrices to achieve linear growth of computation time with systems size, crucial in large-scale simulations. While Kohn-Sham orbitals strictly localized within predefined radii can offer substantial computational advantages over density matrices, such compact orbitals are not used in AIMD because a compact representation of the electronic ground state is difficult to find. Here, a robust method for maintaining compact orbitals close to the ground state is coupled with a modified Langevin integrator to produce stable nuclear dynamics for molecular and ionic systems. This eliminates a density matrix optimization and enables first orbital-only linear-scaling AIMD. An application to liquid water demonstrates that low computational overhead of the new method makes it ideal for routine medium-scale simulations while its linear-scaling complexity allows to extend first- principle studies of molecular systems to completely new physical phenomena on previously inaccessible length scales. Since the unification of molecular dynamics and den- LS methods restrict their use in dynamical simulations sity functional theory (DFT)1, ab initio molecular dy- to very short time scales, systems of low dimensions, namics (AIMD) has become an important tool to study and low-quality minimal basis sets6,18–20. On typical processes in molecules and materials. Unfortunately, the length and time scales required in practical and accurate computational cost of the conventional Kohn-Sham (KS) AIMD simulations, LS DFT still cannot compete with DFT grows cubically with the number of atoms, which the straightforward low-cost cubically-scaling KS DFT. -
Quantum Chemistry (QC) on Gpus Feb
Quantum Chemistry (QC) on GPUs Feb. 2, 2017 Overview of Life & Material Accelerated Apps MD: All key codes are GPU-accelerated QC: All key codes are ported or optimizing Great multi-GPU performance Focus on using GPU-accelerated math libraries, OpenACC directives Focus on dense (up to 16) GPU nodes &/or large # of GPU nodes GPU-accelerated and available today: ACEMD*, AMBER (PMEMD)*, BAND, CHARMM, DESMOND, ESPResso, ABINIT, ACES III, ADF, BigDFT, CP2K, GAMESS, GAMESS- Folding@Home, GPUgrid.net, GROMACS, HALMD, HOOMD-Blue*, UK, GPAW, LATTE, LSDalton, LSMS, MOLCAS, MOPAC2012, LAMMPS, Lattice Microbes*, mdcore, MELD, miniMD, NAMD, NWChem, OCTOPUS*, PEtot, QUICK, Q-Chem, QMCPack, OpenMM, PolyFTS, SOP-GPU* & more Quantum Espresso/PWscf, QUICK, TeraChem* Active GPU acceleration projects: CASTEP, GAMESS, Gaussian, ONETEP, Quantum Supercharger Library*, VASP & more green* = application where >90% of the workload is on GPU 2 MD vs. QC on GPUs “Classical” Molecular Dynamics Quantum Chemistry (MO, PW, DFT, Semi-Emp) Simulates positions of atoms over time; Calculates electronic properties; chemical-biological or ground state, excited states, spectral properties, chemical-material behaviors making/breaking bonds, physical properties Forces calculated from simple empirical formulas Forces derived from electron wave function (bond rearrangement generally forbidden) (bond rearrangement OK, e.g., bond energies) Up to millions of atoms Up to a few thousand atoms Solvent included without difficulty Generally in a vacuum but if needed, solvent treated classically -
EPSRC Service Level Agreement with STFC for Computational Science Support
CoSeC Computational Science Centre for Research Communities EPSRC Service Level Agreement with STFC for Computational Science Support FY 2016/17 Report and Update on FY 2017/18 Work Plans This document contains the 2016/17 plans, 2016/17 summary reports, and 2017/18 plans for the programme in support of CCP and HEC communities delivered by STFC and funded by EPSRC through a Service Level Agreement. Notes in blue are in-year updates on progress to the tasks included in the 2016/17 plans. Text highlighted in yellow shows changes to the draft 2017/18 plans that we submitted in January 2017. Contents CCP5 – Computer Simulation of Condensed Phases .......................................................................... 4 CCP5 – 2016 / 17 Plans (1 April 2016 – 31 March 2017) ...................................................... 4 CCP5 – Summary Report (1 April 2016 – 31 March 2017) .................................................... 7 CCP5 –2017 / 18 Plans (1 April 2017 – 31 March 2018) ....................................................... 8 CCP9 – Electronic Structure of Solids .................................................................................................. 9 CCP9 – 2016 / 17 Plans (1 April 2016 – 31 March 2017) ...................................................... 9 CCP9 – Summary Report (1 April 2016 – 31 March 2017) .................................................. 11 CCP9 – 2017 / 18 Plans (1 April 2017 – 31 March 2018) .................................................... 12 CCP-mag – Computational Multiscale -
Introduction to DFT and the Plane-Wave Pseudopotential Method
Introduction to DFT and the plane-wave pseudopotential method Keith Refson STFC Rutherford Appleton Laboratory Chilton, Didcot, OXON OX11 0QX 23 Apr 2014 Parallel Materials Modelling Packages @ EPCC 1 / 55 Introduction Synopsis Motivation Some ab initio codes Quantum-mechanical approaches Density Functional Theory Electronic Structure of Condensed Phases Total-energy calculations Introduction Basis sets Plane-waves and Pseudopotentials How to solve the equations Parallel Materials Modelling Packages @ EPCC 2 / 55 Synopsis Introduction A guided tour inside the “black box” of ab-initio simulation. Synopsis • Motivation • The rise of quantum-mechanical simulations. Some ab initio codes Wavefunction-based theory • Density-functional theory (DFT) Quantum-mechanical • approaches Quantum theory in periodic boundaries • Plane-wave and other basis sets Density Functional • Theory SCF solvers • Molecular Dynamics Electronic Structure of Condensed Phases Recommended Reading and Further Study Total-energy calculations • Basis sets Jorge Kohanoff Electronic Structure Calculations for Solids and Molecules, Plane-waves and Theory and Computational Methods, Cambridge, ISBN-13: 9780521815918 Pseudopotentials • Dominik Marx, J¨urg Hutter Ab Initio Molecular Dynamics: Basic Theory and How to solve the Advanced Methods Cambridge University Press, ISBN: 0521898633 equations • Richard M. Martin Electronic Structure: Basic Theory and Practical Methods: Basic Theory and Practical Density Functional Approaches Vol 1 Cambridge University Press, ISBN: 0521782856 -
What's New in Biovia Materials Studio 2020
WHAT’S NEW IN BIOVIA MATERIALS STUDIO 2020 Datasheet BIOVIA Materials Studio 2020 is the latest release of BIOVIA’s predictive science tools for chemistry and materials science research. Materials Studio empowers researchers to understand the relationships between a material’s mo- lecular or crystal structure and its properties in order to make more informed decisions about materials research and development. More often than not materials performance is influenced by phenomena at multiple scales. Scientists using Materials Studio 2020 have an extensive suite of world class solvers and parameter sets operating from atoms to microscale for simulating more materials and more properties than ever before. Furthermore, the predicted properties can now be used in multi-physics modeling and in systems modeling software such as SIMULIA Abaqus and CATIA Dymola to predict macroscopic behaviors. In this way multiscale simulations can be used to solve some of the toughest pro- blems in materials design and product optimization. BETTER MATERIALS - BETTER BATTERIES Safe, fast charging batteries with high energy density and long life are urgently needed for a host of applications - not least for the electrification of all modes of transportation as an alternative to fossil fuel energy sources. Battery design relies on a complex interplay between thermal, mechanical and chemical processes from the smallest scales of the material (electronic structure) through to the geometry of the battery cell and pack design. Improvements to the component materials used in batteries and capacitors are fundamental to providing the advances in performance needed. Materials Studio provides new functionality to enable the simula- tion of key materials parameters for both liquid electrolytes and electrode components. -
Arxiv:1508.02735V1 [Cond-Mat.Mtrl-Sci] 11 Aug 2015
A critical look at methods for calculating charge transfer couplings fast and accurately Pablo Ramos, Marc Mankarious, and Michele Pavanello∗ Department of Chemistry, Rutgers University, Newark, NJ 07102, USA E-mail: [email protected] Abstract We present here a short and subjective review of methods for calculating charge trans- fer couplings. Although we mostly focus on Density Functional Theory, we discuss a small subset of semiempirical methods as well as the adiabatic-to-diabatic transformation methods typically coupled with wavefunction-based electronic structure calculations. In this work, we will present the reader with a critical assessment of the regimes that can be modelled by the various methods – their strengths and weaknesses. In order to give a feeling about the practical aspects of the calculations, we also provide the reader with a practical protocol for running coupling calculations with the recently developed FDE-ET method. arXiv:1508.02735v1 [cond-mat.mtrl-sci] 11 Aug 2015 ∗To whom correspondence should be addressed 1 Contents 1 Introduction 3 2 DFT Based Methods 5 2.1 The Frozen Density Embedding formalism . 5 2.1.1 FDE-ET method . 9 2.1.2 Distance dependence of the electronic coupling . 12 2.1.3 Hole transfer in DNA oligomers . 14 2.2 Constrained Density Functional Theory Applied to Electron Transfer Simulations . 16 2.3 Fragment Orbital DFT . 18 2.3.1 Hole transfer rates on DNA hairpins . 20 2.3.2 The Curious Case of Sulfite Oxidase . 20 2.4 Ultrafast computations of the electronic couplings: The AOM method . 22 2.5 Note on orthogonality . -
Interoperability Between Electronic Structure Codes with the Quippy Toolkit
Interoperability between electronic structure codes with the quippy toolkit James Kermode Department of Physics King’s College London 6 September 2012 Outline Overview of libAtoms and QUIP Scripting interfaces Overview of quippy capabilities Live demo! Summary and Conclusions Outline Overview of libAtoms and QUIP Scripting interfaces Overview of quippy capabilities Live demo! Summary and Conclusions I The QUIP (QUantum mechanics and Interatomic Potentials) package, built on top of libAtoms, implements a wide variety of interatomic potentials and tight binding quantum mechanics, and is also able to call external packages. I Various hybrid combinations are also supported in the style of QM/MM, including ‘Learn on the Fly’ scheme (LOTF).2 3 I quippy is a Python interface to libAtoms and QUIP. The libAtoms, QUIP and quippy packages 1 I The libAtoms package is a software library written in Fortran 95 for the purposes of carrying out molecular dynamics simulations. 1http://www.libatoms.org 2Csányi et al., PRL (2004) 3http://www.jrkermode.co.uk/quippy I Various hybrid combinations are also supported in the style of QM/MM, including ‘Learn on the Fly’ scheme (LOTF).2 3 I quippy is a Python interface to libAtoms and QUIP. The libAtoms, QUIP and quippy packages 1 I The libAtoms package is a software library written in Fortran 95 for the purposes of carrying out molecular dynamics simulations. I The QUIP (QUantum mechanics and Interatomic Potentials) package, built on top of libAtoms, implements a wide variety of interatomic potentials and tight binding quantum mechanics, and is also able to call external packages. 1http://www.libatoms.org 2Csányi et al., PRL (2004) 3http://www.jrkermode.co.uk/quippy 3 I quippy is a Python interface to libAtoms and QUIP. -
Surface Functionalization of H-Terminated Diamond with NH and NH2 on the (1, 0, 0), (1, 1, 0) and (1, 1, 1) Surface Planes Using Density Functional Theory
Uppsala University Bachelor project, 15hp Surface functionalization of H-terminated diamond with NH and NH2 on the (1; 0; 0), (1; 1; 0) and (1; 1; 1) surface planes using Density Functional Theory Sara Kjellberg Supervised by Prof. Karin Larsson October 5, 2017 Abstract The adsorption energy of aminated diamond surfaces on the (1; 1; 1), (1; 1; 0) and (1; 0; 0) diamond surfaces have been calculated with density functional theory (DFT). The resulting values show that bridging is favoured before on-top nitrogen at low coverage for all the low index planes. The trend is even more pronounced as the coverage increases, most likely due to sterical hindrance. As expected, the imidogen (NH) and amidogen (NH2) groups are bonded to the surface planes in the order (1; 0; 0) > (1; 1; 1) > (1; 1; 0) as decrease in energy is the highest on the (1; 0; 0) plane and lowest on the (1 010) plane. The effect of sterical hindrance is largest at the (1; 1; 0) surface while the (1; 0; 0) surface is almost unaffected by neighbouring functional groups. Also, double bonded on-top imidogen (NH) is the least stable group at the (1; 0; 0) surface at low coverage while it is almost as stable as bridging NH when having a full mono-layer. Moreover, on-top imidogen (NH) was highly distorted and forced a change in surface geometry 1 Contents 1 Goal 3 2 Introduction 3 2.1 Background . .3 3 Theory 4 3.1 Surfaces of diamond . .4 3.1.1 General surface theory . -
Trends in Atomistic Simulation Software Usage [1.3]
A LiveCoMS Perpetual Review Trends in atomistic simulation software usage [1.3] Leopold Talirz1,2,3*, Luca M. Ghiringhelli4, Berend Smit1,3 1Laboratory of Molecular Simulation (LSMO), Institut des Sciences et Ingenierie Chimiques, Valais, École Polytechnique Fédérale de Lausanne, CH-1951 Sion, Switzerland; 2Theory and Simulation of Materials (THEOS), Faculté des Sciences et Techniques de l’Ingénieur, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 3National Centre for Computational Design and Discovery of Novel Materials (MARVEL), École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland; 4The NOMAD Laboratory at the Fritz Haber Institute of the Max Planck Society and Humboldt University, Berlin, Germany This LiveCoMS document is Abstract Driven by the unprecedented computational power available to scientific research, the maintained online on GitHub at https: use of computers in solid-state physics, chemistry and materials science has been on a continuous //github.com/ltalirz/ rise. This review focuses on the software used for the simulation of matter at the atomic scale. We livecoms-atomistic-software; provide a comprehensive overview of major codes in the field, and analyze how citations to these to provide feedback, suggestions, or help codes in the academic literature have evolved since 2010. An interactive version of the underlying improve it, please visit the data set is available at https://atomistic.software. GitHub repository and participate via the issue tracker. This version dated August *For correspondence: 30, 2021 [email protected] (LT) 1 Introduction Gaussian [2], were already released in the 1970s, followed Scientists today have unprecedented access to computa- by force-field codes, such as GROMOS [3], and periodic tional power.