Preconditioners for Large-Scale Atomistic Simulations
Lead Research Organisation:
Science and Technology Facilities Council
Department Name: Computational Sci and Eng - RAL
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
People |
ORCID iD |
Nicholas Ian Mark Gould (Principal Investigator) |
Publications
Chen H
(2017)
QM/MM Methods for Crystalline Defects. Part 2: Consistent Energy and Force-Mixing
in Multiscale Modeling & Simulation
Chen H
(2016)
QM/MM Methods for Crystalline Defects. Part 1: Locality of the Tight Binding Model
in Multiscale Modeling & Simulation
Gould N
(2016)
A dimer-type saddle search algorithm with preconditioning and linesearch
in Mathematics of Computation
Makri S
(2019)
A preconditioning scheme for minimum energy path finding methods.
in The Journal of chemical physics
Packwood D
(2016)
Dataset to support article:'A universal preconditioner for simulating condensed phase materials'
in The Journal of chemical physics
Packwood D
(2016)
A universal preconditioner for simulating condensed phase materials.
in The Journal of chemical physics
Description | We have developed a general method for approximating complicated atomistic structures with the aim of speeding up computations by replacing the "real" problem by a sufficiently good "approximation". |
Exploitation Route | The methods we have developed have been implemented in open source software, and there are "hooks" into many application programs. Thus users of these will be all be able to benefit from our ideas. |
Sectors | Chemicals Education Electronics Energy Environment Manufacturing including Industrial Biotechology |
URL | http://www.numerical.rl.ac.uk/people/nimg/ |
Description | Our findings have lead to improve understanding of methods for finding transition states and simulating condensed phase materials. Please see the impact description provided for EP/J022055/1. In particular, a primary outcome of the research has been new algorithms that were incorporated into the atomistic materials simulation code (ASE), and this has enabled collaborators to reduce the time taken for materials simulations from several weeks to a few days. |
First Year Of Impact | 2014 |
Sector | Other |
Impact Types | Economic |
Title | Atomic Simulation Environment (ASE) |
Description | The Atomic Simulation Environment (ASE) is a set of tools and Python modules for setting up, manipulating, running, visualizing and analyzing atomistic simulations |
Type Of Technology | Software |
Year Produced | 2016 |
Open Source License? | Yes |
Impact | Interfaces are provided to a variety of external atomistic codes, such as VASP, CASTEP, CP2K and LAMMPS |
URL | https://gitlab.com/jameskermode/ase |
Title | OPTITOM |
Description | Fortran software for the minimization of various potential energy models for large-scale atomistic simulation. The software is at beta status at the moment; users and developers of QUIP have access, and have reported significant improvements in performance relative to the embedded QUIP optimization algorithm |
Type Of Technology | Software |
Year Produced | 2013 |
Open Source License? | Yes |
Impact | Please refer to physicist users of QUIP. |