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Title: Active learning for robust, high-complexity reactive atomistic simulations

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]
  1. Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, USA
  2. Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, USA, Department of Chemical Engineering, University of California, Davis, California 95616, USA
Publication Date:
Sponsoring Org.:
USDOE
OSTI Identifier:
1670808
Resource Type:
Journal Article: Publisher's Accepted Manuscript
Journal Name:
Journal of Chemical Physics
Additional Journal Information:
Journal Name: Journal of Chemical Physics Journal Volume: 153 Journal Issue: 13; Journal ID: ISSN 0021-9606
Publisher:
American Institute of Physics
Country of Publication:
United States
Language:
English

Citation Formats

Lindsey, Rebecca K., Fried, Laurence E., Goldman, Nir, and Bastea, Sorin. Active learning for robust, high-complexity reactive atomistic simulations. United States: N. p., 2020. Web. doi:10.1063/5.0021965.
Lindsey, Rebecca K., Fried, Laurence E., Goldman, Nir, & Bastea, Sorin. Active learning for robust, high-complexity reactive atomistic simulations. United States. doi:10.1063/5.0021965.
Lindsey, Rebecca K., Fried, Laurence E., Goldman, Nir, and Bastea, Sorin. Wed . "Active learning for robust, high-complexity reactive atomistic simulations". United States. doi:10.1063/5.0021965.
@article{osti_1670808,
title = {Active learning for robust, high-complexity reactive atomistic simulations},
author = {Lindsey, Rebecca K. and Fried, Laurence E. and Goldman, Nir and Bastea, Sorin},
abstractNote = {},
doi = {10.1063/5.0021965},
journal = {Journal of Chemical Physics},
issn = {0021-9606},
number = 13,
volume = 153,
place = {United States},
year = {2020},
month = {10}
}

Journal Article:
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Works referenced in this record:

A Mathematical Theory of Communication
journal, July 1948


Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
journal, January 2012


Measurement of carbon condensates using small-angle x-ray scattering during detonation of the high explosive hexanitrostilbene
journal, June 2015

  • Bagge-Hansen, M.; Lauderbach, L.; Hodgin, R.
  • Journal of Applied Physics, Vol. 117, Issue 24
  • DOI: 10.1063/1.4922866

Canonical dynamics: Equilibrium phase-space distributions
journal, March 1985


Diamonds in detonation soot
journal, June 1988

  • Greiner, N. Roy; Phillips, D. S.; Johnson, J. D.
  • Nature, Vol. 333, Issue 6172
  • DOI: 10.1038/333440a0

Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set
journal, July 1996


Bayesian Ensemble Approach to Error Estimation of Interatomic Potentials
journal, October 2004


Least angle regression
journal, April 2004


QCTFF: On the construction of a novel protein force field: PERSPECTIVE
journal, March 2015

  • Popelier, Paul L. A.
  • International Journal of Quantum Chemistry, Vol. 115, Issue 16
  • DOI: 10.1002/qua.24900

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials
journal, January 2016

  • Shapeev, Alexander V.
  • Multiscale Modeling & Simulation, Vol. 14, Issue 3
  • DOI: 10.1137/15m1054183

Permutationally invariant potential energy surfaces in high dimensionality
journal, October 2009

  • Braams, Bastiaan J.; Bowman, Joel M.
  • International Reviews in Physical Chemistry, Vol. 28, Issue 4
  • DOI: 10.1080/01442350903234923

Projector augmented-wave method
journal, December 1994


Generalized Gradient Approximation Made Simple
journal, October 1996

  • Perdew, John P.; Burke, Kieron; Ernzerhof, Matthias
  • Physical Review Letters, Vol. 77, Issue 18, p. 3865-3868
  • DOI: 10.1103/physrevlett.77.3865

Potential Energy Surfaces Fitted by Artificial Neural Networks
journal, March 2010

  • Handley, Chris M.; Popelier, Paul L. A.
  • The Journal of Physical Chemistry A, Vol. 114, Issue 10
  • DOI: 10.1021/jp9105585

Using Force Matching To Determine Reactive Force Fields for Water under Extreme Thermodynamic Conditions
journal, December 2016

  • Koziol, Lucas; Fried, Laurence E.; Goldman, Nir
  • Journal of Chemical Theory and Computation, Vol. 13, Issue 1
  • DOI: 10.1021/acs.jctc.6b00707

Less is more: Sampling chemical space with active learning
journal, June 2018

  • Smith, Justin S.; Nebgen, Ben; Lubbers, Nicholas
  • The Journal of Chemical Physics, Vol. 148, Issue 24
  • DOI: 10.1063/1.5023802

Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials
journal, March 2015


Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set
journal, October 1996


Many-body reactive force field development for carbon condensation in C/O systems under extreme conditions
journal, August 2020

  • Lindsey, Rebecca K.; Goldman, Nir; Fried, Laurence E.
  • The Journal of Chemical Physics, Vol. 153, Issue 5
  • DOI: 10.1063/5.0012840

Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations
journal, January 2011

  • Behler, Jörg
  • Physical Chemistry Chemical Physics, Vol. 13, Issue 40
  • DOI: 10.1039/c1cp21668f

Adaptive machine learning framework to accelerate ab initio molecular dynamics
journal, December 2014

  • Botu, Venkatesh; Ramprasad, Rampi
  • International Journal of Quantum Chemistry, Vol. 115, Issue 16
  • DOI: 10.1002/qua.24836

Semiempirical GGA-type density functional constructed with a long-range dispersion correction
journal, January 2006

  • Grimme, Stefan
  • Journal of Computational Chemistry, Vol. 27, Issue 15, p. 1787-1799
  • DOI: 10.1002/jcc.20495

Modeling solid-state chemistry: Interatomic potentials for multicomponent systems
journal, March 1989


Application of the ChIMES Force Field to Nonreactive Molecular Systems: Water at Ambient Conditions
journal, November 2018

  • Lindsey, Rebecca K.; Fried, Laurence E.; Goldman, Nir
  • Journal of Chemical Theory and Computation, Vol. 15, Issue 1
  • DOI: 10.1021/acs.jctc.8b00831

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
journal, April 2010


Ultrafast shock synthesis of nanocarbon from a liquid precursor
journal, January 2020

  • Armstrong, Michael R.; Lindsey, Rebecca K.; Goldman, Nir
  • Nature Communications, Vol. 11, Issue 1
  • DOI: 10.1038/s41467-019-14034-z

Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium
journal, May 1994


Regularization Paths for Generalized Linear Models via Coordinate Descent
journal, January 2010

  • Friedman, Jerome; Hastie, Trevor; Tibshirani, Robert
  • Journal of Statistical Software, Vol. 33, Issue 1
  • DOI: 10.18637/jss.v033.i01

The utility of higher order derivatives in constructing molecular potential energy surfaces by interpolation
journal, December 1995

  • Jordan, Meredith J. T.; Thompson, Keiran C.; Collins, Michael A.
  • The Journal of Chemical Physics, Vol. 103, Issue 22
  • DOI: 10.1063/1.469982

The properties and applications of nanodiamonds
journal, December 2011

  • Mochalin, Vadym N.; Shenderova, Olga; Ho, Dean
  • Nature Nanotechnology, Vol. 7, Issue 1
  • DOI: 10.1038/nnano.2011.209

Active learning of uniformly accurate interatomic potentials for materials simulation
journal, February 2019


Ab initiomolecular dynamics for liquid metals
journal, January 1993


A unified formulation of the constant temperature molecular dynamics methods
journal, July 1984

  • Nosé, Shuichi
  • The Journal of Chemical Physics, Vol. 81, Issue 1
  • DOI: 10.1063/1.447334

First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems
journal, August 2017


ChIMES: A Force Matched Potential with Explicit Three-Body Interactions for Molten Carbon
journal, November 2017

  • Lindsey, Rebecca K.; Fried, Laurence E.; Goldman, Nir
  • Journal of Chemical Theory and Computation, Vol. 13, Issue 12
  • DOI: 10.1021/acs.jctc.7b00867

Active Learning the Potential Energy Landscape for Water Clusters from Sparse Training Data
journal, January 2020

  • Loeffler, Troy D.; Patra, Tarak K.; Chan, Henry
  • The Journal of Physical Chemistry C, Vol. 124, Issue 8
  • DOI: 10.1021/acs.jpcc.0c00047

Generalized Gradient Approximation Made Simple [Phys. Rev. Lett. 77, 3865 (1996)]
journal, February 1997


From ultrasoft pseudopotentials to the projector augmented-wave method
journal, January 1999


Support vector machine regression (LS-SVM)—an alternative to artificial neural networks (ANNs) for the analysis of quantum chemistry data?
journal, January 2011

  • Balabin, Roman M.; Lomakina, Ekaterina I.
  • Physical Chemistry Chemical Physics, Vol. 13, Issue 24
  • DOI: 10.1039/c1cp00051a

Active learning of linearly parametrized interatomic potentials
journal, December 2017


Regression Shrinkage and Selection Via the Lasso
journal, January 1996