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Title: Functional uncertainty quantification for isobaric molecular dynamics simulations and defect formation energies

Abstract

Functional uncertainty quantification (FunUQ) was recently proposed to quantify uncertainties in models and simulations that originate from input functions, as opposed to parameters. This paper extends here FunUQ to quantify uncertainties originating from interatomic potentials in isothermal-isobaric molecular dynamics (MD) simulations and to the calculation of defect formation energies. We derive and verify a computationally inexpensive expression to compute functional derivatives in MD based on perturbation theory. We show that this functional derivative of the quantities of interest (average internal energy, volume, and defect energies in our case) with respect to the interatomic potential can be used to predict those quantities for a different interatomic potential, without re-running the simulation. The codes and scripts to perform FunUQ in MD are freely available for download. In addition, to facilitate reproducibility and to enable use of best practices for the approach, we created Jupyter notebooks to perform FunUQ analysis on MD simulations and made them available for online simulation in nanoHUB. The tool uses cloud computing resources and users can view, edit, and run end-to-end workflows from a standard web-browser without the need to download or install any software.

Authors:
ORCiD logo [1];  [2]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States). Materials Science Division
  2. Purdue Univ., West Lafayette, IN (United States). School of Materials Engineering. Birck Nanotechnology Center
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Purdue Univ., West Lafayette, IN (United States)
Sponsoring Org.:
USDOE; National Science Foundation (NSF)
OSTI Identifier:
1525723
Report Number(s):
LLNL-JRNL-760093
Journal ID: ISSN 0965-0393; 947997
Grant/Contract Number:  
AC52-07NA27344; CBET 1404823
Resource Type:
Accepted Manuscript
Journal Name:
Modelling and Simulation in Materials Science and Engineering
Additional Journal Information:
Journal Volume: 27; Journal Issue: 4; Journal ID: ISSN 0965-0393
Publisher:
IOP Publishing
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE

Citation Formats

Reeve, Samuel Temple, and Strachan, Alejandro. Functional uncertainty quantification for isobaric molecular dynamics simulations and defect formation energies. United States: N. p., 2019. Web. doi:10.1088/1361-651x/ab16fa.
Reeve, Samuel Temple, & Strachan, Alejandro. Functional uncertainty quantification for isobaric molecular dynamics simulations and defect formation energies. United States. doi:10.1088/1361-651x/ab16fa.
Reeve, Samuel Temple, and Strachan, Alejandro. Mon . "Functional uncertainty quantification for isobaric molecular dynamics simulations and defect formation energies". United States. doi:10.1088/1361-651x/ab16fa.
@article{osti_1525723,
title = {Functional uncertainty quantification for isobaric molecular dynamics simulations and defect formation energies},
author = {Reeve, Samuel Temple and Strachan, Alejandro},
abstractNote = {Functional uncertainty quantification (FunUQ) was recently proposed to quantify uncertainties in models and simulations that originate from input functions, as opposed to parameters. This paper extends here FunUQ to quantify uncertainties originating from interatomic potentials in isothermal-isobaric molecular dynamics (MD) simulations and to the calculation of defect formation energies. We derive and verify a computationally inexpensive expression to compute functional derivatives in MD based on perturbation theory. We show that this functional derivative of the quantities of interest (average internal energy, volume, and defect energies in our case) with respect to the interatomic potential can be used to predict those quantities for a different interatomic potential, without re-running the simulation. The codes and scripts to perform FunUQ in MD are freely available for download. In addition, to facilitate reproducibility and to enable use of best practices for the approach, we created Jupyter notebooks to perform FunUQ analysis on MD simulations and made them available for online simulation in nanoHUB. The tool uses cloud computing resources and users can view, edit, and run end-to-end workflows from a standard web-browser without the need to download or install any software.},
doi = {10.1088/1361-651x/ab16fa},
journal = {Modelling and Simulation in Materials Science and Engineering},
number = 4,
volume = 27,
place = {United States},
year = {2019},
month = {4}
}

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