The modern temperature-accelerated dynamics approach
Abstract
Accelerated molecular dynamics (AMD) is a class of MD-based methods used to simulate atomistic systems in which the metastable state-to-state evolution is slow compared with thermal vibrations. Temperature-accelerated dynamics (TAD) is a particularly efficient AMD procedure in which the predicted evolution is hastened by elevating the temperature of the system and then recovering the correct state-to-state dynamics at the temperature of interest. TAD has been used to study various materials applications, often revealing surprising behavior beyond the reach of direct MD. This success has inspired several algorithmic performance enhancements, as well as the analysis of its mathematical framework. Recently, these enhancements have leveraged parallel programming techniques to enhance both the spatial and temporal scaling of the traditional approach. Here, we review the ongoing evolution of the modern TAD method and introduce the latest development: speculatively parallel TAD.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1329594
- Report Number(s):
- LA-UR-15-27574
Journal ID: ISSN 1947-5438
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Annual Review of Chemical and Biomolecular Engineering
- Additional Journal Information:
- Journal Volume: 7; Journal Issue: 1; Journal ID: ISSN 1947-5438
- Publisher:
- Annual Reviews
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE; material science; accelerated molecular dynamics; temperature-accelerated dynamics; molecular dynamics; infrequent events; rare events
Citation Formats
Zamora, Richard J., Uberuaga, Blas P., Perez, Danny, and Voter, Arthur F. The modern temperature-accelerated dynamics approach. United States: N. p., 2016.
Web. doi:10.1146/annurev-chembioeng-080615-033608.
Zamora, Richard J., Uberuaga, Blas P., Perez, Danny, & Voter, Arthur F. The modern temperature-accelerated dynamics approach. United States. https://doi.org/10.1146/annurev-chembioeng-080615-033608
Zamora, Richard J., Uberuaga, Blas P., Perez, Danny, and Voter, Arthur F. Wed .
"The modern temperature-accelerated dynamics approach". United States. https://doi.org/10.1146/annurev-chembioeng-080615-033608. https://www.osti.gov/servlets/purl/1329594.
@article{osti_1329594,
title = {The modern temperature-accelerated dynamics approach},
author = {Zamora, Richard J. and Uberuaga, Blas P. and Perez, Danny and Voter, Arthur F.},
abstractNote = {Accelerated molecular dynamics (AMD) is a class of MD-based methods used to simulate atomistic systems in which the metastable state-to-state evolution is slow compared with thermal vibrations. Temperature-accelerated dynamics (TAD) is a particularly efficient AMD procedure in which the predicted evolution is hastened by elevating the temperature of the system and then recovering the correct state-to-state dynamics at the temperature of interest. TAD has been used to study various materials applications, often revealing surprising behavior beyond the reach of direct MD. This success has inspired several algorithmic performance enhancements, as well as the analysis of its mathematical framework. Recently, these enhancements have leveraged parallel programming techniques to enhance both the spatial and temporal scaling of the traditional approach. Here, we review the ongoing evolution of the modern TAD method and introduce the latest development: speculatively parallel TAD.},
doi = {10.1146/annurev-chembioeng-080615-033608},
journal = {Annual Review of Chemical and Biomolecular Engineering},
number = 1,
volume = 7,
place = {United States},
year = {Wed Jun 01 00:00:00 EDT 2016},
month = {Wed Jun 01 00:00:00 EDT 2016}
}
Web of Science
Works referencing / citing this record:
Modeling Diffusion in Functional Materials: From Density Functional Theory to Artificial Intelligence
journal, July 2019
- Elbaz, Yuval; Furman, David; Caspary Toroker, Maytal
- Advanced Functional Materials
Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification
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Long-time molecular dynamics simulations on massively parallel platforms: A comparison of parallel replica dynamics and parallel trajectory splicing
journal, December 2017
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- Journal of Materials Research, Vol. 33, Issue 7
Speculation and replication in temperature accelerated dynamics
journal, February 2018
- Zamora, Richard J.; Perez, Danny; Voter, Arthur F.
- Journal of Materials Research, Vol. 33, Issue 7