Universal Machine Learning Interatomic Potentials: Surveying Solid Electrolytes

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

(2020) Jonathan Vandermause et al.   npj Computational Materials

Rapid and Economic Synthesis of Li7PS6 Solid Electrolyte from Liquid Approach

(2019) Dominika A. Ziolkowska et al.   ACS Applied Materials & Interfaces

Phase Transitions of Hybrid Perovskites Simulated by Machine-Learning Force Fields Trained on the Fly with Bayesian Inference

(2019) Ryosuke Jinnouchi et al.   PHYSICAL REVIEW LETTERS

An electrostatic spectral neighbor analysis potential for lithium nitride

(2019) Zhi Deng et al.   npj Computational Materials

Fundamentals of inorganic solid-state electrolytes for batteries

(2019) Theodosios Famprikis et al.   NATURE MATERIALS

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

(2019) K. T. Schütt et al.   Nature Communications

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

(2018) Linfeng Zhang et al.   PHYSICAL REVIEW LETTERS

Statistical variances of diffusional properties from ab initio molecular dynamics simulations

(2018) Xingfeng He et al.   npj Computational Materials

Towards exact molecular dynamics simulations with machine-learned force fields

(2018) Stefan Chmiela et al.   Nature Communications

Study of Li atom diffusion in amorphous Li3PO4 with neural network potential

(2017) Wenwen Li et al.   JOURNAL OF CHEMICAL PHYSICS

Origin of fast ion diffusion in super-ionic conductors

(2017) Xingfeng He et al.   Nature Communications

Machine learning of accurate energy-conserving molecular force fields

(2017) Stefan Chmiela et al.   Science Advances

Insights into the Performance Limits of the Li7P3S11 Superionic Conductor: A Combined First-Principles and Experimental Study

(2016) Iek-Heng Chu et al.   ACS Applied Materials & Interfaces

Ab initio and kinetic Monte Carlo study of lithium diffusion in LiSi, Li 12 Si 7 , Li 13 Si 5 and Li 15 Si 4

(2016) Janghyuk Moon et al.   JOURNAL OF POWER SOURCES

Computational studies of solid-state alkali conduction in rechargeable alkali-ion batteries

(2016) Zhi Deng et al.   NPG Asia Materials

Rational Composition Optimization of the Lithium-Rich Li3OCl1–xBrx Anti-Perovskite Superionic Conductors

(2015) Zhi Deng et al.   CHEMISTRY OF MATERIALS

Fast Li Ion Dynamics in the Solid Electrolyte Li7P3S11as Probed by6,7Li NMR Spin-Lattice Relaxation

(2015) Dominik Wohlmuth et al.   CHEMPHYSCHEM

Structural and Mechanistic Insights into Fast Lithium-Ion Conduction in Li4SiO4–Li3PO4 Solid Electrolytes

(2015) Yue Deng et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

First-principles interatomic potentials for ten elemental metals via compressed sensing

(2015) Atsuto Seko et al.   PHYSICAL REVIEW B

Molecular Dynamics with On-the-Fly Machine Learning of Quantum-Mechanical Forces

(2015) Zhenwei Li et al.   PHYSICAL REVIEW LETTERS

Solid-State Electrolytes: Revealing the Mechanisms of Li-Ion Conduction in Tetragonal and Cubic LLZO by First-Principles Calculations

(2014) Katharina Meier et al.   Journal of Physical Chemistry C

Concerted Migration Mechanism in the Li Ion Dynamics of Garnet-Type Li7La3Zr2O12

(2013) Randy Jalem et al.   CHEMISTRY OF MATERIALS

A sulphide lithium super ion conductor is superior to liquid ion conductors for use in rechargeable batteries

(2013) Yoshikatsu Seino et al.   Energy & Environmental Science

Anomalous High Ionic Conductivity of Nanoporous β-Li3PS4

(2013) Zengcai Liu et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

On representing chemical environments

(2013) Albert P. Bartók et al.   PHYSICAL REVIEW B

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

(2013) Anubhav Jain et al.   APL Materials

One-dimensional stringlike cooperative migration of lithium ions in an ultrafast ionic conductor

(2012) M. Xu et al.   APPLIED PHYSICS LETTERS

Phase stability, electrochemical stability and ionic conductivity of the Li10±1MP2X12(M = Ge, Si, Sn, Al or P, and X = O, S or Se) family of superionic conductors

(2012) Shyue Ping Ong et al.   Energy & Environmental Science

First Principles Study of the Li10GeP2S12 Lithium Super Ionic Conductor Material

(2011) Yifei Mo et al.   CHEMISTRY OF MATERIALS

A lithium superionic conductor

(2011) Noriaki Kamaya et al.   NATURE MATERIALS

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

(2010) Albert P. Bartók et al.   PHYSICAL REVIEW LETTERS