On the Role of Long-Range Electrostatics in Machine-Learned Interatomic Potentials for Complex Battery Materials

When do short-range atomistic machine-learning models fall short?

(2021) Shuwen Yue et al.   JOURNAL OF CHEMICAL PHYSICS

A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer

(2021) Tsz Wai Ko et al.   Nature Communications

Transferability of machine learning potentials: Protonated water neural network potential applied to the protonated water hexamer

(2021) Christoph Schran et al.   JOURNAL OF CHEMICAL PHYSICS

Gaussian Process Regression for Materials and Molecules

(2021) Volker L. Deringer et al.   CHEMICAL REVIEWS

Nano‐Scale Complexions Facilitate Li Dendrite‐Free Operation in LATP Solid‐State Electrolyte

(2021) Sina Stegmaier et al.   Advanced Energy Materials

Machine Learning for Molecular Simulation

(2020) Frank Noé et al.   Annual Review of Physical Chemistry

FCHL revisited: Faster and more accurate quantum machine learning

(2020) Anders S. Christensen et al.   JOURNAL OF CHEMICAL PHYSICS

Clarifying the relationship between redox activity and electrochemical stability in solid electrolytes

(2020) Tammo K. Schwietert et al.   NATURE MATERIALS

SciPy 1.0: fundamental algorithms for scientific computing in Python

(2020) Pauli Virtanen et al.   NATURE METHODS

Lithium Ion Conduction in Cathode Coating Materials from On-the-Fly Machine Learning

(2020) Chuhong Wang et al.   CHEMISTRY OF MATERIALS

Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide

(2020) April M. Cooper et al.   npj Computational Materials

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

(2020) Jonathan Vandermause et al.   npj Computational Materials

An accurate machine-learning calculator for optimization of Li-ion battery cathodes

(2020) Gregory Houchins et al.   JOURNAL OF CHEMICAL PHYSICS

Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

(2020) Xiaowei Xie et al.   Journal of Chemical Theory and Computation

Dielectric response with short-ranged electrostatics

(2020) Stephen J. Cox   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Exploring chemical compound space with quantum-based machine learning

(2020) O. Anatole von Lilienfeld et al.   Nature Reviews Chemistry

Mapping Materials and Molecules

(2020) Bingqing Cheng et al.   ACCOUNTS OF CHEMICAL RESEARCH

Ab initio thermodynamics of liquid and solid water

(2019) Bingqing Cheng et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges

(2019) Oliver T. Unke et al.   Journal of Chemical Theory and Computation

Multi-ion Conduction in Li3OCl Glass Electrolytes

(2019) Hendrik H. Heenen et al.   Journal of Physical Chemistry Letters

Ab Initio Thermodynamics Insight into the Structural Evolution of Working IrO2 Catalysts in Proton-Exchange Membrane Electrolyzers

(2019) Daniel Opalka et al.   ACS Catalysis

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

First-principles-based multiscale modelling of heterogeneous catalysis

(2019) Albert Bruix et al.   Nature Catalysis

Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground

(2019) Christoph Schran et al.   Journal of Chemical Theory and Computation

Understanding interface stability in solid-state batteries

(2019) Yihan Xiao et al.   Nature Reviews Materials

A mechanism of defect-enhanced phase transformation kinetics in lithium iron phosphate olivine

(2019) Liang Hong et al.   npj Computational Materials

Addressing global uncertainty and sensitivity in first-principles based microkinetic models by an adaptive sparse grid approach

(2018) Sandra Döpking et al.   JOURNAL OF CHEMICAL PHYSICS

Constructing first-principles phase diagrams of amorphous LixSi using machine-learning-assisted sampling with an evolutionary algorithm

(2018) Nongnuch Artrith et al.   JOURNAL OF CHEMICAL PHYSICS

Alchemical and structural distribution based representation for universal quantum machine learning

(2018) Felix A. Faber et al.   JOURNAL OF CHEMICAL PHYSICS

Gaussian approximation potential modeling of lithium intercalation in carbon nanostructures

(2018) So Fujikake et al.   JOURNAL OF CHEMICAL PHYSICS

The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics

(2018) Kun Yao et al.   Chemical Science

Bayesian-Driven First-Principles Calculations for Accelerating Exploration of Fast Ion Conductors for Rechargeable Battery Application

(2018) Randy Jalem et al.   Scientific Reports

The structural and compositional factors that control the Li-ion conductivity in LiPON electrolytes

(2018) Valentina Lacivita et al.   CHEMISTRY OF MATERIALS

Super-Ionic Conduction in Solid-State Li7P3S11-Type Sulfide Electrolytes

(2018) Donghee Chang et al.   CHEMISTRY OF MATERIALS

Transferable Machine-Learning Model of the Electron Density

(2018) Andrea Grisafi et al.   ACS Central Science

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

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

The atomic simulation environment—a Python library for working with atoms

(2017) Ask Hjorth Larsen et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Implications of Occupational Disorder on Ion Mobility in Li4Ti5O12 Battery Materials

(2017) Hendrik H. Heenen et al.   NANO LETTERS

Lithium ion conductivity in Li2S–P2S5 glasses – building units and local structure evolution during the crystallization of superionic conductors Li3PS4, Li7P3S11 and Li4P2S7

(2017) Christian Dietrich et al.   Journal of Materials Chemistry A

In Situ Monitoring of Fast Li-Ion Conductor Li7P3S11 Crystallization Inside a Hot-Press Setup

(2016) Martin R. Busche et al.   CHEMISTRY OF MATERIALS

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

(2016) Alexander V. Shapeev   MULTISCALE MODELING & SIMULATION

Computational understanding of Li-ion batteries

(2016) Alexander Urban et al.   npj Computational Materials

Origin of Outstanding Stability in the Lithium Solid Electrolyte Materials: Insights from Thermodynamic Analyses Based on First-Principles Calculations

(2015) Yizhou Zhu et al.   ACS Applied Materials & Interfaces

Interfacial Challenges in Solid-State Li Ion Batteries

(2015) Alan C. Luntz et al.   Journal of Physical Chemistry Letters

Interatomic potentials for ionic systems with density functional accuracy based on charge densities obtained by a neural network

(2015) S. Alireza Ghasemi et al.   PHYSICAL REVIEW B

On representing chemical environments

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

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

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

Ab initio molecular simulations with numeric atom-centered orbitals

(2009) Volker Blum et al.   COMPUTER PHYSICS COMMUNICATIONS