Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

Swinburne, Thomas David; Perez, Danny

doi:10.1103/PhysRevMaterials.2.053802

Title: Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

Abstract

Here, a massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.

Authors:

^[1];

^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Publication Date:: Mon May 21 00:00:00 EDT 2018

Research Org.:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

OSTI Identifier:: 1458961

Report Number(s):: LA-UR-18-21562
Journal ID: ISSN 2475-9953; PRMHAR; TRN: US1901538

Grant/Contract Number:: AC52-06NA25396

Resource Type:: Accepted Manuscript

Journal Name:: Physical Review Materials

Additional Journal Information:: Journal Volume: 2; Journal Issue: 5; Journal ID: ISSN 2475-9953

Publisher:: American Physical Society (APS)

Country of Publication:: United States

Language:: English

Subject:: 36 MATERIALS SCIENCE; Material Science

Citation Formats


                    Swinburne, Thomas David, and Perez, Danny. Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification.  United States: N. p., 2018. 
Web.  doi:10.1103/PhysRevMaterials.2.053802.

Copy to clipboard


                    Swinburne, Thomas David, & Perez, Danny. Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification.  United States.  https://doi.org/10.1103/PhysRevMaterials.2.053802

Copy to clipboard


                    Swinburne, Thomas David, and Perez, Danny. Mon .  
"Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification".  United States.  https://doi.org/10.1103/PhysRevMaterials.2.053802.  https://www.osti.gov/servlets/purl/1458961.

Copy to clipboard


                    
@article{osti_1458961,

  title        = {Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification},

  author       = {Swinburne, Thomas David and Perez, Danny},

  abstractNote = {Here, a massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.},

  doi          = {10.1103/PhysRevMaterials.2.053802},

  journal      = {Physical Review Materials},

  number       = 5,

  volume       = 2,

  place        = {United States},

  year         = {Mon May 21 00:00:00 EDT 2018},

  month        = {Mon May 21 00:00:00 EDT 2018}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1103/PhysRevMaterials.2.053802

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 30 works

Citation information provided by
Web of Science

Figures / Tables:

FIG. 1: TAMMBER workflow. TAD MD produces interstate transition trajectories which are analyzed by Bayesian rate estimators and static calculation. An absorbing Markov chain gives then gives the expected residence time and optimally allocates resources and the degree of temperature acceleration. The cycle is then repeated until the target residencemore »

All figures and tables (7 total)

Save / Share:

Export Metadata

Save to My Library

Works referenced in this record:

Atomistic Simulations of Activated Processes in Materials
journal, July 2017

Henkelman, G.
Annual Review of Materials Research, Vol. 47, Issue 1
DOI: 10.1146/annurev-matsci-071312-121616

Discrete path sampling
journal, October 2002

Wales, David J.
Molecular Physics, Vol. 100, Issue 20
DOI: 10.1080/00268970210162691

Temperature-accelerated dynamics for simulation of infrequent events
journal, June 2000

So/rensen, Mads R.; Voter, Arthur F.
The Journal of Chemical Physics, Vol. 112, Issue 21
DOI: 10.1063/1.481576

Unsupervised Calculation of Free Energy Barriers in Large Crystalline Systems
journal, March 2018

Swinburne, Thomas D.; Marinica, Mihai-Cosmin
Physical Review Letters, Vol. 120, Issue 13
DOI: 10.1103/PhysRevLett.120.135503

The Modern Temperature-Accelerated Dynamics Approach
journal, June 2016

Zamora, Richard J.; Uberuaga, Blas P.; Perez, Danny
Annual Review of Chemical and Biomolecular Engineering, Vol. 7, Issue 1
DOI: 10.1146/annurev-chembioeng-080615-033608

A new algorithm for Monte Carlo simulation of Ising spin systems
journal, January 1975

Bortz, A. B.; Kalos, M. H.; Lebowitz, J. L.
Journal of Computational Physics, Vol. 17, Issue 1
DOI: 10.1016/0021-9991(75)90060-1

Kinetic activation-relaxation technique
journal, October 2011

Béland, Laurent Karim; Brommer, Peter; El-Mellouhi, Fedwa
Physical Review E, Vol. 84, Issue 4
DOI: 10.1103/PhysRevE.84.046704

Dynamical integration of a Markovian web: A first passage time approach
journal, August 2007

Boulougouris, Georgios C.; Theodorou, Doros N.
The Journal of Chemical Physics, Vol. 127, Issue 8
DOI: 10.1063/1.2753153

Monte Carlo Sampling of a Markov Web
journal, March 2005

Boulougouris, Georgios C.; Frenkel, Daan
Journal of Chemical Theory and Computation, Vol. 1, Issue 3
DOI: 10.1021/ct049900m

The nature of high-energy radiation damage in iron
journal, February 2013

Zarkadoula, E.; Daraszewicz, S. L.; Duffy, D. M.
Journal of Physics: Condensed Matter, Vol. 25, Issue 12
DOI: 10.1088/0953-8984/25/12/125402

Adaptive temperature-accelerated dynamics
journal, February 2011

Shim, Yunsic; Amar, Jacques G.
The Journal of Chemical Physics, Vol. 134, Issue 5
DOI: 10.1063/1.3541823

Structural Relaxation Made Simple
journal, October 2006

Bitzek, Erik; Koskinen, Pekka; Gähler, Franz
Physical Review Letters, Vol. 97, Issue 17
DOI: 10.1103/PhysRevLett.97.170201

Stability of self-interstitial clusters with C15 Laves phase structure in iron
journal, June 2014

Dézerald, L.; Marinica, M. -C.; Ventelon, Lisa
Journal of Nuclear Materials, Vol. 449, Issue 1-3
DOI: 10.1016/j.jnucmat.2014.02.012

Practical graph isomorphism, II
journal, January 2014

McKay, Brendan D.; Piperno, Adolfo
Journal of Symbolic Computation, Vol. 60
DOI: 10.1016/j.jsc.2013.09.003

Hyperdynamics: Accelerated Molecular Dynamics of Infrequent Events
journal, May 1997

Voter, Arthur F.
Physical Review Letters, Vol. 78, Issue 20
DOI: 10.1103/PhysRevLett.78.3908

Formation of prismatic loops from C15 Laves phase interstitial clusters in body-centered cubic iron
journal, March 2015

Zhang, Yongfeng; Bai, Xian-Ming; Tonks, Michael R.
Scripta Materialia, Vol. 98
DOI: 10.1016/j.scriptamat.2014.10.033

Fast Parallel Algorithms for Short-Range Molecular Dynamics
journal, March 1995

Plimpton, Steve
Journal of Computational Physics, Vol. 117, Issue 1
DOI: 10.1006/jcph.1995.1039

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
journal, July 2013

Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy
APL Materials, Vol. 1, Issue 1
DOI: 10.1063/1.4812323

Long-Time Dynamics through Parallel Trajectory Splicing
journal, December 2015

Perez, Danny; Cubuk, Ekin D.; Waterland, Amos
Journal of Chemical Theory and Computation, Vol. 12, Issue 1
DOI: 10.1021/acs.jctc.5b00916

Tutorial on maximum likelihood estimation
journal, February 2003

Myung, In Jae
Journal of Mathematical Psychology, Vol. 47, Issue 1, p. 90-100
DOI: 10.1016/S0022-2496(02)00028-7

Reaction-rate theory: fifty years after Kramers
journal, April 1990

Hänggi, Peter; Talkner, Peter; Borkovec, Michal
Reviews of Modern Physics, Vol. 62, Issue 2
DOI: 10.1103/RevModPhys.62.251

Multiscale modelling of defect kinetics in irradiated iron
journal, December 2004

Fu, Chu-Chun; Torre, Jacques Dalla; Willaime, François
Nature Materials, Vol. 4, Issue 1
DOI: 10.1038/nmat1286

Big Data of Materials Science: Critical Role of the Descriptor
journal, March 2015

Ghiringhelli, Luca M.; Vybiral, Jan; Levchenko, Sergey V.
Physical Review Letters, Vol. 114, Issue 10
DOI: 10.1103/PhysRevLett.114.105503

Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics
journal, September 2015

Chatterjee, Abhijit; Bhattacharya, Swati
The Journal of Chemical Physics, Vol. 143, Issue 11
DOI: 10.1063/1.4930976

Benchmarks for Characterization of Minima, Transition States, and Pathways in Atomic, Molecular, and Condensed Matter Systems
journal, November 2014

Chill, Samuel T.; Stevenson, Jacob; Ruehle, Victor
Journal of Chemical Theory and Computation, Vol. 10, Issue 12
DOI: 10.1021/ct5008718

Scalable kernel polynomial method for calculating transition rates
journal, June 2013

Huang, Chen; Voter, Arthur F.; Perez, Danny
Physical Review B, Vol. 87, Issue 21
DOI: 10.1103/PhysRevB.87.214106

Comparison of empirical interatomic potentials for iron applied to radiation damage studies
journal, November 2010

Malerba, L.; Marinica, M. C.; Anento, N.
Journal of Nuclear Materials, Vol. 406, Issue 1
DOI: 10.1016/j.jnucmat.2010.05.017

A climbing image nudged elastic band method for finding saddle points and minimum energy paths
journal, December 2000

Henkelman, Graeme; Uberuaga, Blas P.; Jónsson, Hannes
The Journal of Chemical Physics, Vol. 113, Issue 22, p. 9901-9904
DOI: 10.1063/1.1329672

Monte Carlo Algorithms with Absorbing Markov Chains: Fast Local Algorithms for Slow Dynamics
journal, January 1995

Novotny, M. A.
Physical Review Letters, Vol. 74, Issue 1
DOI: 10.1103/PhysRevLett.74.1

Irradiation-Induced Formation of Nanocrystallites with $C 15$ Laves Phase Structure in bcc Iron
journal, January 2012

Marinica, M. -C.; Willaime, F.; Crocombette, J. -P.
Physical Review Letters, Vol. 108, Issue 2
DOI: 10.1103/PhysRevLett.108.025501

Molecular dynamics saddle search adaptive kinetic Monte Carlo
journal, June 2014

Chill, Samuel T.; Henkelman, Graeme
The Journal of Chemical Physics, Vol. 140, Issue 21
DOI: 10.1063/1.4880721

An invariant form for the prior probability in estimation problems
journal, September 1946

Jeffreys, Harold
Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, Vol. 186, Issue 1007, p. 453-461
DOI: 10.1098/rspa.1946.0056

Everything you wanted to know about Markov State Models but were afraid to ask
journal, September 2010

Pande, Vijay S.; Beauchamp, Kyle; Bowman, Gregory R.
Methods, Vol. 52, Issue 1
DOI: 10.1016/j.ymeth.2010.06.002

Parallel replica method for dynamics of infrequent events
journal, June 1998

Voter, Arthur F.
Physical Review B, Vol. 57, Issue 22
DOI: 10.1103/PhysRevB.57.R13985

A new class of enhanced kinetic sampling methods for building Markov state models
journal, October 2017

Bhoutekar, Arti; Ghosh, Susmita; Bhattacharya, Swati
The Journal of Chemical Physics, Vol. 147, Issue 15
DOI: 10.1063/1.4984932

Big Data of Materials Science - Critical Role of the Descriptor
text, January 2014

Ghiringhelli, Luca M.; Vybiral, Jan; Levchenko, Sergey V.
arXiv
DOI: 10.48550/arxiv.1411.7437

Works referencing / citing this record:

Atomistic-object kinetic Monte Carlo simulations of irradiation damage in tungsten
journal, May 2019

Mason, D. R.; Sand, A. E.; Dudarev, S. L.
Modelling and Simulation in Materials Science and Engineering, Vol. 27, Issue 5
DOI: 10.1088/1361-651x/ab1a1e

Atomistic-Object Kinetic Monte Carlo simulations of irradiation damage in tungsten
text, January 2019

Mason, Daniel R.; Sand, Andrea E.; Dudarev, Sergei L.
arXiv
DOI: 10.48550/arxiv.1904.04089

Figures / Tables found in this record:

Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.

Similar Records in DOE PAGES and OSTI.GOV collections:

Extreme-Scale Bayesian Inference for Uncertainty Quantification of Complex Simulations

Technical Report Biros, George

Uncertainty quantification (UQ)—that is, quantifying uncertainties in complex mathematical models and their large-scale computational implementations—is widely viewed as one of the outstanding challenges facing the field of CS&E over the coming decade. The EUREKA project set to address the most difficult class of UQ problems: those for which both the underlying PDE model as well as the uncertain parameters are of extreme scale. In the project we worked on these extreme-scale challenges in the following four areas: 1. Scalable parallel algorithms for sampling and characterizing the posterior distribution that exploit the structure of the underlying PDEs and parameter-to-observable map. Thesemore »« less
https://doi.org/10.2172/1416727

Full Text Available
Sparsifying priors for Bayesian uncertainty quantification in model discovery

Journal Article Hirsh, Seth M. ; Barajas-Solano, David A. ; Kutz, J. Nathan - Royal Society Open Science

We propose a probabilistic model discovery method for identifying ordinary differential equations governing the dynamics of observed multivariate data. Our method is based on the sparse identification of nonlinear dynamics (SINDy) framework, where models are expressed as sparse linear combinations of pre-specified candidate functions. Promoting parsimony through sparsity leads to interpretable models that generalize to unknown data. Instead of targeting point estimates of the SINDy coefficients, we estimate these coefficients via sparse Bayesian inference. The resulting method, uncertainty quantification SINDy (UQ-SINDy), quantifies not only the uncertainty in the values of the SINDy coefficients due to observation errors and limited data,more »« less
https://doi.org/10.1098/rsos.211823

Full Text Available
Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys

Journal Article Tran, Anh ; Tranchida, Julien ; Wildey, Tim ; ... - Journal of Chemical Physics

We present a scale-bridging approach based on a multi-fidelity (MF) machine-learning (ML) framework leveraging Gaussian processes (GP) to fuse atomistic computational model predictions across multiple levels of fidelity. Through the posterior variance of the MFGP, our framework naturally enables uncertainty quantification, providing estimates of confidence in the predictions. We used density functional theory as high-fidelity prediction, while a ML interatomic potential is used as low-fidelity prediction. Practical materials’ design efficiency is demonstrated by reproducing the ternary composition dependence of a quantity of interest (bulk modulus) across the full aluminum–niobium–titanium ternary random alloy composition space. The MFGP is then coupled tomore »« less
https://doi.org/10.1063/5.0015672

Full Text Available
Π4U: A high performance computing framework for Bayesian uncertainty quantification of complex models

Journal Article Hadjidoukas, P. E. ; Angelikopoulos, P. ; Papadimitriou, C. ; ... - Journal of Computational Physics

We present Π4U,{sup 1} an extensible framework, for non-intrusive Bayesian Uncertainty Quantification and Propagation (UQ+P) of complex and computationally demanding physical models, that can exploit massively parallel computer architectures. The framework incorporates Laplace asymptotic approximations as well as stochastic algorithms, along with distributed numerical differentiation and task-based parallelism for heterogeneous clusters. Sampling is based on the Transitional Markov Chain Monte Carlo (TMCMC) algorithm and its variants. The optimization tasks associated with the asymptotic approximations are treated via the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). A modified subset simulation method is used for posterior reliability measurements of rare events. The frameworkmore »« less
https://doi.org/10.1016/J.JCP.2014.12.006
Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Journal Article Dhulipala, Somayajulu Lakshmi Narasimha ; Toptan, Aysenur ; Che, Yifeng ; ... - Journal of Nuclear Materials

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements,more »« less
https://doi.org/10.1016/j.jnucmat.2023.154790

Similar Records

Title: Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

Abstract

Citation Formats

Figures / Tables:

Atomistic Simulations of Activated Processes in Materials journal, July 2017

Discrete path sampling journal, October 2002

Temperature-accelerated dynamics for simulation of infrequent events journal, June 2000

Unsupervised Calculation of Free Energy Barriers in Large Crystalline Systems journal, March 2018

The Modern Temperature-Accelerated Dynamics Approach journal, June 2016

A new algorithm for Monte Carlo simulation of Ising spin systems journal, January 1975

Kinetic activation-relaxation technique journal, October 2011

Dynamical integration of a Markovian web: A first passage time approach journal, August 2007

Monte Carlo Sampling of a Markov Web journal, March 2005

The nature of high-energy radiation damage in iron journal, February 2013

Adaptive temperature-accelerated dynamics journal, February 2011

Structural Relaxation Made Simple journal, October 2006

Stability of self-interstitial clusters with C15 Laves phase structure in iron journal, June 2014

Practical graph isomorphism, II journal, January 2014

Hyperdynamics: Accelerated Molecular Dynamics of Infrequent Events journal, May 1997

Formation of prismatic loops from C15 Laves phase interstitial clusters in body-centered cubic iron journal, March 2015

Fast Parallel Algorithms for Short-Range Molecular Dynamics journal, March 1995

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation journal, July 2013

Long-Time Dynamics through Parallel Trajectory Splicing journal, December 2015

Tutorial on maximum likelihood estimation journal, February 2003

Reaction-rate theory: fifty years after Kramers journal, April 1990

Multiscale modelling of defect kinetics in irradiated iron journal, December 2004

Big Data of Materials Science: Critical Role of the Descriptor journal, March 2015

Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics journal, September 2015

Benchmarks for Characterization of Minima, Transition States, and Pathways in Atomic, Molecular, and Condensed Matter Systems journal, November 2014

Scalable kernel polynomial method for calculating transition rates journal, June 2013

Comparison of empirical interatomic potentials for iron applied to radiation damage studies journal, November 2010

A climbing image nudged elastic band method for finding saddle points and minimum energy paths journal, December 2000

Monte Carlo Algorithms with Absorbing Markov Chains: Fast Local Algorithms for Slow Dynamics journal, January 1995

Irradiation-Induced Formation of Nanocrystallites with C 15 Laves Phase Structure in bcc Iron journal, January 2012

Molecular dynamics saddle search adaptive kinetic Monte Carlo journal, June 2014

An invariant form for the prior probability in estimation problems journal, September 1946

Everything you wanted to know about Markov State Models but were afraid to ask journal, September 2010

Parallel replica method for dynamics of infrequent events journal, June 1998

A new class of enhanced kinetic sampling methods for building Markov state models journal, October 2017

Big Data of Materials Science - Critical Role of the Descriptor text, January 2014

Atomistic-object kinetic Monte Carlo simulations of irradiation damage in tungsten journal, May 2019

Atomistic-Object Kinetic Monte Carlo simulations of irradiation damage in tungsten text, January 2019

Atomistic Simulations of Activated Processes in Materials
journal, July 2017

Discrete path sampling
journal, October 2002

Temperature-accelerated dynamics for simulation of infrequent events
journal, June 2000

Unsupervised Calculation of Free Energy Barriers in Large Crystalline Systems
journal, March 2018

The Modern Temperature-Accelerated Dynamics Approach
journal, June 2016

A new algorithm for Monte Carlo simulation of Ising spin systems
journal, January 1975

Kinetic activation-relaxation technique
journal, October 2011

Dynamical integration of a Markovian web: A first passage time approach
journal, August 2007

Monte Carlo Sampling of a Markov Web
journal, March 2005

The nature of high-energy radiation damage in iron
journal, February 2013

Adaptive temperature-accelerated dynamics
journal, February 2011

Structural Relaxation Made Simple
journal, October 2006

Stability of self-interstitial clusters with C15 Laves phase structure in iron
journal, June 2014

Practical graph isomorphism, II
journal, January 2014

Hyperdynamics: Accelerated Molecular Dynamics of Infrequent Events
journal, May 1997

Formation of prismatic loops from C15 Laves phase interstitial clusters in body-centered cubic iron
journal, March 2015

Fast Parallel Algorithms for Short-Range Molecular Dynamics
journal, March 1995

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
journal, July 2013

Long-Time Dynamics through Parallel Trajectory Splicing
journal, December 2015

Tutorial on maximum likelihood estimation
journal, February 2003

Reaction-rate theory: fifty years after Kramers
journal, April 1990

Multiscale modelling of defect kinetics in irradiated iron
journal, December 2004

Big Data of Materials Science: Critical Role of the Descriptor
journal, March 2015

Uncertainty in a Markov state model with missing states and rates: Application to a room temperature kinetic model obtained using high temperature molecular dynamics
journal, September 2015

Benchmarks for Characterization of Minima, Transition States, and Pathways in Atomic, Molecular, and Condensed Matter Systems
journal, November 2014

Scalable kernel polynomial method for calculating transition rates
journal, June 2013

Comparison of empirical interatomic potentials for iron applied to radiation damage studies
journal, November 2010

A climbing image nudged elastic band method for finding saddle points and minimum energy paths
journal, December 2000

Monte Carlo Algorithms with Absorbing Markov Chains: Fast Local Algorithms for Slow Dynamics
journal, January 1995

Irradiation-Induced Formation of Nanocrystallites with $C 15$ Laves Phase Structure in bcc Iron
journal, January 2012

Molecular dynamics saddle search adaptive kinetic Monte Carlo
journal, June 2014

An invariant form for the prior probability in estimation problems
journal, September 1946

Everything you wanted to know about Markov State Models but were afraid to ask
journal, September 2010

Parallel replica method for dynamics of infrequent events
journal, June 1998

A new class of enhanced kinetic sampling methods for building Markov state models
journal, October 2017

Big Data of Materials Science - Critical Role of the Descriptor
text, January 2014

Atomistic-object kinetic Monte Carlo simulations of irradiation damage in tungsten
journal, May 2019

Atomistic-Object Kinetic Monte Carlo simulations of irradiation damage in tungsten
text, January 2019