skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: 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:
 [1];  [1];  [1];  [1]
  1. 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. doi: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. doi: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 = {2016},
month = {6}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 4 works
Citation information provided by
Web of Science

Save / Share:

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
  • DOI: 10.1002/adfm.201900778

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
  • DOI: 10.1002/adfm.201900778