DFT Accurate Interatomic Potential for Molten NaCl from Machine Learning

Tovey, Samuel; Narayanan Krishnamoorthy, Anand; Sivaraman, Ganesh; Guo, Jicheng; Benmore, Chris; Heuer, Andreas; Holm, Christian

doi:10.1021/acs.jpcc.0c08870

DFT Accurate Interatomic Potential for Molten NaCl from Machine Learning

Journal Article · Thu Nov 12 00:00:00 EST 2020 · Journal of Physical Chemistry. C

DOI:https://doi.org/10.1021/acs.jpcc.0c08870· OSTI ID:1774556

^[1]; ^[2]; Sivaraman, Ganesh ^[3]; ^[3]; ^[3]; Heuer, Andreas ^[4]; ^[1]

University of Stuttgart (Germany)
Helmholtz-Institute Münster: Ionics in Energy Storage (IEK-12), Münster (Germany)
Argonne National Lab. (ANL), Argonne, IL (United States)
Helmholtz-Institute Münster: Ionics in Energy Storage (IEK-12), Münster (Germany); University of Münster (Germany)

Molten alkali chloride salts are a critical component in concentrated solar power and nuclear applications. Despite their ubiquity, the extreme chemical reactivity of molten alkali chlorides at high temperatures has presented a significant challenge in characterizing atomic structures and dynamic properties experimentally. In this work, we we investigate molten NaCl by performing high temperature molecular dynamics simulations using a Gaussian Approximation Potential (GAP) trained on Density Functional Theory (DFT) datasets. Our GAP model, trained with a meager 1000 atomic configurations, arrives at near ab initio accuracy with a mean absolute error of 1.5 meV/atom thus enabling fast analysis of high temperature salt properties on large length (5000 ion pairs) and time (> 1ns) scales currently inaccessible to ab initio simulations. Calculated structure factors and diffusion constants from our GAP model simulations show excellent agreement with experiments. Our results indicate that GAP models are able to capture the many-body interactions required to accurately model ionic-systems.

View Accepted Manuscript (DOE)

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: Deutsche Forschungsgemeinschaft (DFG); USDOE Office of Science (SC)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 1774556

Journal Information:: Journal of Physical Chemistry. C, Journal Name: Journal of Physical Chemistry. C Journal Issue: 47 Vol. 124; ISSN 1932-7447

Publisher:: American Chemical SocietyCopyright Statement

Country of Publication:: United States

Language:: English

References (66)

cp2k: atomistic simulations of condensed matter systems Hutter, Jürg; Iannuzzi, Marcella; Schiffmann, Florian Wiley Interdisciplinary Reviews: Computational Molecular Science, Vol. 4, Issue 1 https://doi.org/10.1002/wcms.1159	journal	June 2013
Fast Parallel Algorithms for Short-Range Molecular Dynamics Plimpton, Steve Journal of Computational Physics, Vol. 117, Issue 1 https://doi.org/10.1006/jcph.1995.1039	journal	March 1995
Zur Gittertheorie der Ionenkristalle Born, Max; Mayer, Joseph E. Zeitschrift f�r Physik, Vol. 75, Issue 1-2 https://doi.org/10.1007/BF01340511	journal	January 1932
The density of liquid NaCl and KCl and an estimate of their critical constants together with those of the other alkali halides Kirshenbaum, A. D.; Cahill, J. A.; McGonigal, P. J. Journal of Inorganic and Nuclear Chemistry, Vol. 24, Issue 10 https://doi.org/10.1016/0022-1902(62)80205-X	journal	December 1962
Ionic sizes and born repulsive parameters in the NaCl-type alkali halides—I Fumi, F. G.; Tosi, M. P. Journal of Physics and Chemistry of Solids, Vol. 25, Issue 1 https://doi.org/10.1016/0022-3697(64)90159-3	journal	January 1964
Ionic sizes and born repulsive parameters in the NaCl-type alkali halides—II Tosi, M. P.; Fumi, F. G. Journal of Physics and Chemistry of Solids, Vol. 25, Issue 1 https://doi.org/10.1016/0022-3697(64)90160-X	journal	January 1964
Redox electrochemistry and formal standard redox potentials of the Eu(III)/Eu(II) redox couple in an equimolar mixture of molten NaClKCl Kuznetsov, S. A.; Gaune-Escard, M. Electrochimica Acta, Vol. 46, Issue 8 https://doi.org/10.1016/S0013-4686(00)00708-8	journal	January 2001
Quickstep: Fast and accurate density functional calculations using a mixed Gaussian and plane waves approach VandeVondele, Joost; Krack, Matthias; Mohamed, Fawzi Computer Physics Communications, Vol. 167, Issue 2 https://doi.org/10.1016/j.cpc.2004.12.014	journal	April 2005
Electrolysis of solid metal sulfide to metal and sulfur in molten NaCl–KCl Wang, Tao; Gao, Haiping; Jin, Xianbo Electrochemistry Communications, Vol. 13, Issue 12 https://doi.org/10.1016/j.elecom.2011.10.005	journal	December 2011
Phase-Transferable Force Field for Alkali Halides Walz, Marie-Madeleine; Ghahremanpour, Mohammad M.; van Maaren, Paul J. Journal of Chemical Theory and Computation, Vol. 14, Issue 11 https://doi.org/10.1021/acs.jctc.8b00507	journal	October 2018
Performance and Cost Assessment of Machine Learning Interatomic Potentials Zuo, Yunxing; Chen, Chi; Li, Xiangguo The Journal of Physical Chemistry A, Vol. 124, Issue 4 https://doi.org/10.1021/acs.jpca.9b08723	journal	October 2019
Modeling the Phase-Change Memory Material, Ge ₂ Sb ₂ Te ₅ , with a Machine-Learned Interatomic Potential Mocanu, Felix C.; Konstantinou, Konstantinos; Lee, Tae Hoon The Journal of Physical Chemistry B, Vol. 122, Issue 38 https://doi.org/10.1021/acs.jpcb.8b06476	journal	September 2018
Fluid Structure of Molten LiCl–Li Solutions Guo, Jicheng; Merwin, Augustus; Benmore, Chris J. The Journal of Physical Chemistry B, Vol. 123, Issue 47 https://doi.org/10.1021/acs.jpcb.9b07479	journal	October 2019
Realistic Atomistic Structure of Amorphous Silicon from Machine-Learning-Driven Molecular Dynamics Deringer, Volker L.; Bernstein, Noam; Bartók, Albert P. The Journal of Physical Chemistry Letters, Vol. 9, Issue 11 https://doi.org/10.1021/acs.jpclett.8b00902	journal	May 2018
Elucidating Ionic Correlations Beyond Simple Charge Alternation in Molten MgCl ₂ –KCl Mixtures Wu, Fei; Roy, Santanu; Ivanov, Alexander S. The Journal of Physical Chemistry Letters, Vol. 10, Issue 24 https://doi.org/10.1021/acs.jpclett.9b02845	journal	November 2019
Liquid Metal Batteries: Past, Present, and Future Kim, Hojong; Boysen, Dane A.; Newhouse, Jocelyn M. Chemical Reviews, Vol. 113, Issue 3 https://doi.org/10.1021/cr300205k	journal	November 2012
Diffusion of Unlike Ions into Liquid Sodium Chloride Bockris, J. O'M.; Yoshikawa, S.; Richards, S. R. The Journal of Physical Chemistry, Vol. 68, Issue 7 https://doi.org/10.1021/j100789a028	journal	July 1964
Self-Diffusion and Structure in Molten Group II Chlorides ¹ Bockris, J. O'M.; Richards, S. R.; Nanis, L. The Journal of Physical Chemistry, Vol. 69, Issue 5 https://doi.org/10.1021/j100889a031	journal	May 1965
Electrical Conductance and Density of Molten Salt Systems: KCl–LiCl, KCl–NaCl and KCl–KI Van Artsdalen, E. R.; Yaffe, I. S. The Journal of Physical Chemistry, Vol. 59, Issue 2 https://doi.org/10.1021/j150524a007	journal	February 1955
Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids Jorgensen, William L.; Maxwell, David S.; Tirado-Rives, Julian Journal of the American Chemical Society, Vol. 118, Issue 45 https://doi.org/10.1021/ja9621760	journal	January 1996
Towards exact molecular dynamics simulations with machine-learned force fields Chmiela, Stefan; Sauceda, Huziel E.; Müller, Klaus-Robert Nature Communications, Vol. 9, Issue 1 https://doi.org/10.1038/s41467-018-06169-2	journal	September 2018
Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide Sivaraman, Ganesh; Krishnamoorthy, Anand Narayanan; Baur, Matthias npj Computational Materials, Vol. 6, Issue 1 https://doi.org/10.1038/s41524-020-00367-7	journal	July 2020
Machine learning for molecular and materials science Butler, Keith T.; Davies, Daniel W.; Cartwright, Hugh Nature, Vol. 559, Issue 7715 https://doi.org/10.1038/s41586-018-0337-2	journal	July 2018
Molten alkali halides – temperature dependence of structure, dynamics and thermodynamics Walz, Marie-Madeleine; van der Spoel, David Physical Chemistry Chemical Physics, Vol. 21, Issue 34 https://doi.org/10.1039/C9CP03603B	journal	January 2019
Temperature effects on the ionic conductivity in concentrated alkaline electrolyte solutions Shao, Yunqi; Hellström, Matti; Yllö, Are Physical Chemistry Chemical Physics, Vol. 22, Issue 19 https://doi.org/10.1039/C9CP06479F	journal	January 2020
Studies of the local structures of molten metal halides Rollet, Anne-Laure; Salanne, Mathieu Annual Reports Section "C" (Physical Chemistry), Vol. 107 https://doi.org/10.1039/c1pc90003j	journal	January 2011
Self-diffusion in molten alkali halides Bockris, J. O'M.; Hooper, G. W. Discussions of the Faraday Society, Vol. 32 https://doi.org/10.1039/df9613200218	journal	January 1961
X-ray diffraction analysis of molten NaCl near its melting point Ohno, Hideo; Furukawa, Kazuo Journal of the Chemical Society, Faraday Transactions 1: Physical Chemistry in Condensed Phases, Vol. 77, Issue 8 https://doi.org/10.1039/f19817701981	journal	January 1981
Étude des sels fondus par diffraction des rayons X aux températures élevées (Suite) II. Structure à l'état liquide des chlorures LiCl, NaCl, KCl, BaCl2 et du fluorure CaF2. Considérations générales sur la structure des halogénures fondus Zarzycki, Jerzy Journal de Physique Appliquée, Vol. 19, Issue S4 https://doi.org/10.1051/jphysap:0195800190401300	journal	January 1958
Dispersion and Polarizability and the van der Waals Potential in the Alkali Halides Mayer, Joseph E. The Journal of Chemical Physics, Vol. 1, Issue 4 https://doi.org/10.1063/1.1749283	journal	April 1933
Interatomic Distances in Crystals of the Alkali Halides Huggins, Maurice L.; Mayer, Joseph E. The Journal of Chemical Physics, Vol. 1, Issue 9 https://doi.org/10.1063/1.1749344	journal	September 1933
Density-functional-based molecular-dynamics simulations of molten salts Hazebroucq, Sandrine; Picard, Gérard S.; Adamo, Carlo The Journal of Chemical Physics, Vol. 123, Issue 13 https://doi.org/10.1063/1.2038888	journal	October 2005
First principles molecular dynamics of molten NaCl Galamba, N.; Costa Cabral, B. J. The Journal of Chemical Physics, Vol. 126, Issue 12 https://doi.org/10.1063/1.2711187	journal	March 2007
Gaussian basis sets for accurate calculations on molecular systems in gas and condensed phases VandeVondele, Joost; Hutter, Jürg The Journal of Chemical Physics, Vol. 127, Issue 11 https://doi.org/10.1063/1.2770708	journal	September 2007
Calculations of the thermal conductivities of ionic materials by simulation with polarizable interaction potentials Ohtori, Norikazu; Salanne, Mathieu; Madden, Paul A. The Journal of Chemical Physics, Vol. 130, Issue 10 https://doi.org/10.1063/1.3086856	journal	March 2009
The origin of the conductivity maximum in molten salts. I. Bismuth chloride Clay, Adam T.; Kuntz, Colin M.; Johnson, Keith E. The Journal of Chemical Physics, Vol. 136, Issue 12 https://doi.org/10.1063/1.3694830	journal	March 2012
A unified formulation of the constant temperature molecular dynamics methods Nosé, Shuichi The Journal of Chemical Physics, Vol. 81, Issue 1 https://doi.org/10.1063/1.447334	journal	July 1984
Molten Salts Data: Diffusion Coefficients in Single and Multi‐Component Salt Systems Janz, G. J.; Bansal, N. P. Journal of Physical and Chemical Reference Data, Vol. 11, Issue 3 https://doi.org/10.1063/1.555665	journal	July 1982
Small-angle scattering and the structure of ambient liquid water Clark, G. N. I.; Hura, G. L.; Teixeira, J. Proceedings of the National Academy of Sciences, Vol. 107, Issue 32 https://doi.org/10.1073/pnas.1006599107	journal	July 2010
Interionic potentials in alkali halides and their use in simulations of the molten salts Sangster, M. J. L.; Dixon, M. Advances in Physics, Vol. 25, Issue 3 https://doi.org/10.1080/00018737600101392	journal	May 1976
Polarization effects in ionic solids and melts Salanne, Mathieu; Madden, Paul A. Molecular Physics, Vol. 109, Issue 19 https://doi.org/10.1080/00268976.2011.617523	journal	October 2011
Transport coefficients and the Stokes–Einstein relation in molten alkali halides with polarisable ion model Ishii, Yoshiki; Kasai, Satoshi; Salanne, Mathieu Molecular Physics, Vol. 113, Issue 17-18 https://doi.org/10.1080/00268976.2015.1046527	journal	May 2015
A theory of the electrical properties of liquid metals: III. the resistivity of binary alloys Faber, T. E.; Ziman, J. M. Philosophical Magazine, Vol. 11, Issue 109 https://doi.org/10.1080/14786436508211931	journal	January 1965
Comments on the structure of molten salts Biggin, S.; Enderby, J. E. Journal of Physics C: Solid State Physics, Vol. 15, Issue 11 https://doi.org/10.1088/0022-3719/15/11/001	journal	April 1982
The structure of molten sodium chloride Edwards, F. G.; Enderby, J. E.; Howe, R. A. Journal of Physics C: Solid State Physics, Vol. 8, Issue 21 https://doi.org/10.1088/0022-3719/8/21/018	journal	November 1975
The Molecular Dynamics Calculation of Transport Coefficients Gillan, M. J. Physica Scripta, Vol. T39 https://doi.org/10.1088/0031-8949/1991/T39/057	journal	January 1991
Structure and dynamics of molten salts Revere, M.; Tosi, M. P. Reports on Progress in Physics, Vol. 49, Issue 9 https://doi.org/10.1088/0034-4885/49/9/002	journal	September 1986
Neutron and x-ray diffraction studies of liquids and glasses Fischer, Henry E.; Barnes, Adrian C.; Salmon, Philip S. Reports on Progress in Physics, Vol. 69, Issue 1 https://doi.org/10.1088/0034-4885/69/1/R05	journal	November 2005
The structure of molten LiCl McGreevy, R. L.; Howe, M. A. Journal of Physics: Condensed Matter, Vol. 1, Issue 49 https://doi.org/10.1088/0953-8984/1/49/014	journal	December 1989
Analysis of high-energy x-ray diffraction data at high pressure: the case of vitreous As ₂ O ₃ at 32 GPa Mei, Q.; Benmore, C. J.; Soignard, E. Journal of Physics: Condensed Matter, Vol. 19, Issue 41 https://doi.org/10.1088/0953-8984/19/41/415103	journal	September 2007
Polarization effects in ionic systems from first principles Wilson, M.; Madden, P. A. Journal of Physics: Condensed Matter, Vol. 5, Issue 17 https://doi.org/10.1088/0953-8984/5/17/004	journal	April 1993
The solvation and ion condensation properties for sulfonated polyelectrolytes in different solvents—a computational study Smiatek, J.; Wohlfarth, A.; Holm, C. New Journal of Physics, Vol. 16, Issue 2 https://doi.org/10.1088/1367-2630/16/2/025001	journal	February 2014
Inhomogeneous Electron Gas Hohenberg, P.; Kohn, W. Physical Review, Vol. 136, Issue 3B, p. B864-B871 https://doi.org/10.1103/PhysRev.136.B864	journal	November 1964
Self-Consistent Equations Including Exchange and Correlation Effects Kohn, W.; Sham, L. J. Physical Review, Vol. 140, Issue 4A, p. A1133-A1138 https://doi.org/10.1103/PhysRev.140.A1133	journal	November 1965
Canonical dynamics: Equilibrium phase-space distributions Hoover, William G. Physical Review A, Vol. 31, Issue 3 https://doi.org/10.1103/PhysRevA.31.1695	journal	March 1985
Separable dual-space Gaussian pseudopotentials Goedecker, S.; Teter, M.; Hutter, J. Physical Review B, Vol. 54, Issue 3 https://doi.org/10.1103/PhysRevB.54.1703	journal	July 1996
On representing chemical environments Bartók, Albert P.; Kondor, Risi; Csányi, Gábor Physical Review B, Vol. 87, Issue 18 https://doi.org/10.1103/PhysRevB.87.184115	journal	May 2013
Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons Bartók, Albert P.; Payne, Mike C.; Kondor, Risi Physical Review Letters, Vol. 104, Issue 13 https://doi.org/10.1103/PhysRevLett.104.136403	journal	April 2010
Generalized Gradient Approximation Made Simple Perdew, John P.; Burke, Kieron; Ernzerhof, Matthias Physical Review Letters, Vol. 77, Issue 18, p. 3865-3868 https://doi.org/10.1103/PhysRevLett.77.3865	journal	October 1996
Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron Dragoni, Daniele; Daff, Thomas D.; Csányi, Gábor Physical Review Materials, Vol. 2, Issue 1 https://doi.org/10.1103/PhysRevMaterials.2.013808	journal	January 2018
Machine Learning a General-Purpose Interatomic Potential for Silicon Bartók, Albert P.; Kermode, James; Bernstein, Noam Physical Review X, Vol. 8, Issue 4 https://doi.org/10.1103/PhysRevX.8.041048	journal	December 2018
A comparison of various commonly used correlation functions for describing total scattering Keen, David A. Journal of Applied Crystallography, Vol. 34, Issue 2 https://doi.org/10.1107/S0021889800019993	journal	April 2001
Review—Metallic Lithium and the Reduction of Actinide Oxides Merwin, Augustus; Williamson, Mark A.; Willit, James L. Journal of The Electrochemical Society, Vol. 164, Issue 8 https://doi.org/10.1149/2.0251708jes	journal	January 2017
Electrochemical Reduction of TiO 2 in Molten LiCl–Li 2 O Hur, Jin-Mok; Lee, Su-Chul; Jeong, Sang-Mun Chemistry Letters, Vol. 36, Issue 8 https://doi.org/10.1246/cl.2007.1028	journal	August 2007
Concentrating Solar Power Gen3 Demonstration Roadmap Mehos, Mark; Turchi, Craig; Vidal, Judith https://doi.org/10.2172/1338899	report	January 2017
Pyroprocessing Flowsheets for Recycling used Nuclear fuel Williamson, M. A.; Willit, J. L. Nuclear Engineering and Technology, Vol. 43, Issue 4 https://doi.org/10.5516/NET.2011.43.4.329	journal	August 2011

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DFT Accurate Interatomic Potential for Molten NaCl from Machine Learning

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