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

Machine Learning for Molecular Simulation

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

Global optimization of copper clusters at the ZnO(101¯0) surface using a DFT-based neural network potential and genetic algorithms

(2020) Martín Leandro Paleico 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

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

An electrostatic spectral neighbor analysis potential for lithium nitride

(2019) Zhi Deng et al.   npj Computational Materials

Machine Learning Interatomic Potentials as Emerging Tools for Materials Science

(2019) Volker L. Deringer et al.   ADVANCED MATERIALS

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt 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

Discovering a Transferable Charge Assignment Model Using Machine Learning

(2018) Andrew E. Sifain et al.   Journal of Physical Chemistry Letters

Inducing wetting morphologies and increased reactivities of small Au clusters on doped oxide supports

(2018) Nisha Mammen et al.   JOURNAL OF CHEMICAL PHYSICS

A neural-network potential through charge equilibration for WS2: From clusters to sheets

(2017) Roohollah Hafizi et al.   JOURNAL OF CHEMICAL PHYSICS

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

(2017) J. S. Smith et al.   Chemical Science

Bypassing the Kohn-Sham equations with machine learning

(2017) Felix Brockherde et al.   Nature Communications

Perspective: Machine learning potentials for atomistic simulations

(2016) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

Geometries, Binding Energies, Ionization Potentials, and Electron Affinities of Metal Clusters: Mgn0, ± 1, n = 1–7

(2016) Kaining Duanmu et al.   Journal of Physical Chemistry C

Machine Learning Force Fields: Construction, Validation, and Outlook

(2016) V. Botu et al.   Journal of Physical Chemistry C

Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials

(2016) Alexander V. Shapeev   MULTISCALE MODELING & SIMULATION

Elucidating the Nature of the Active Phase in Copper/Ceria Catalysts for CO Oxidation

(2016) Joseph S. Elias et al.   ACS Catalysis

Constructing high-dimensional neural network potentials: A tutorial review

(2015) Jörg Behler   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Transferable Atomic Multipole Machine Learning Models for Small Organic Molecules

(2015) Tristan Bereau et al.   Journal of Chemical Theory and Computation

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

A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges

(2012) Tobias Morawietz et al.   JOURNAL OF CHEMICAL PHYSICS

Neural network potentials for metals and oxides - First applications to copper clusters at zinc oxide

(2012) Nongnuch Artrith et al.   PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS

Tailoring the Shape of Metal Ad-Particles by Doping the Oxide Support

(2011) Xiang Shao et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Density functional studies of LiN and LiN+ (N = 2-30) clusters: Structure, binding and charge distribution

(2011) Neetu Goel et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

VESTA 3for three-dimensional visualization of crystal, volumetric and morphology data

(2011) Koichi Momma et al.   JOURNAL OF APPLIED CRYSTALLOGRAPHY

The effect of ionization on the global minima of small and medium sized silicon and magnesium clusters

(2011) Sandip De et al.   JOURNAL OF CHEMICAL PHYSICS

Atom-centered symmetry functions for constructing high-dimensional neural network potentials

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

Development of a Transferable Variable Charge Potential for the Study of Energy Conversion Materials FeF2 and FeF3

(2011) Ying Ma et al.   Journal of Physical Chemistry C

Tuning the Morphology of Gold Clusters by Substrate Doping

(2011) Nisha Mammen et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

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

(2011) Roman M. Balabin et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

(2011) Jörg Behler   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide

(2011) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Potential Energy Surfaces Fitted by Artificial Neural Networks

(2010) Chris M. Handley et al.   JOURNAL OF PHYSICAL CHEMISTRY A

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

Visualization and analysis of atomistic simulation data with OVITO–the Open Visualization Tool

(2009) Alexander Stukowski   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING