Representing the potential-energy surface of protonated water clusters by high-dimensional neural network potentials

Next generation interatomic potentials for condensed systems

(2014) Christopher Michael Handley et al.   EUROPEAN PHYSICAL JOURNAL B

Reactive Many-Body Expansion for a Protonated Water Cluster

(2013) Peter Pinski et al.   Journal of Chemical Theory and Computation

A Density-Functional Theory-Based Neural Network Potential for Water Clusters Including van der Waals Corrections

(2013) Tobias Morawietz et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Machine-learning approach for one- and two-body corrections to density functional theory: Applications to molecular and condensed water

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

A Full-Dimensional Neural Network Potential-Energy Surface for Water Clusters up to the Hexamer

(2013) Tobias Morawietz et al.   ZEITSCHRIFT FUR PHYSIKALISCHE CHEMIE-INTERNATIONAL JOURNAL OF RESEARCH IN PHYSICAL CHEMISTRY & CHEMICAL PHYSICS

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

Construction of high-dimensional neural network potentials using environment-dependent atom pairs

(2012) K. V. Jovan Jose 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

High-dimensional neural network potentials for metal surfaces: A prototype study for copper

(2012) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Neural network interatomic potential for the phase change material GeTe

(2012) Gabriele C. Sosso et al.   PHYSICAL REVIEW B

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

Liquid Water: From Symmetry Distortions to Diffusive Motion

(2011) Noam Agmon   ACCOUNTS OF CHEMICAL RESEARCH

The Curious Case of the Hydrated Proton

(2011) Chris Knight et al.   ACCOUNTS OF CHEMICAL RESEARCH

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

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

Proton transfer reactions and dynamics in protonated water clusters

(2011) Charoensak Lao-ngam 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

Simulating water with rigid non-polarizable models: a general perspective

(2011) Carlos Vega et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

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

(2011) Nongnuch Artrith et al.   PHYSICAL REVIEW B

Towards an ab initio flexible potential for water, and post-harmonic quantum vibrational analysis of water clusters

(2010) Yimin Wang et al.   CHEMICAL PHYSICS LETTERS

Aqueous Basic Solutions: Hydroxide Solvation, Structural Diffusion, and Comparison to the Hydrated Proton

(2010) Dominik Marx et al.   CHEMICAL REVIEWS

Potential Energy Surfaces Fitted by Artificial Neural Networks

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

Ab initioquality neural-network potential for sodium

(2010) Hagai Eshet et al.   PHYSICAL REVIEW B

Graphite-diamond phase coexistence study employing a neural-network mapping of theab initiopotential energy surface

(2010) Rustam Z. Khaliullin 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

TiReX: Replica-exchange molecular dynamics using Tinker

(2009) Evgeni S. Penev et al.   COMPUTER PHYSICS COMMUNICATIONS

Ab initio molecular simulations with numeric atom-centered orbitals

(2009) Volker Blum et al.   COMPUTER PHYSICS COMMUNICATIONS

Dynamically Polarizable Water Potential Based on Multipole Moments Trained by Machine Learning

(2009) Chris M. Handley et al.   Journal of Chemical Theory and Computation

Classification of OH Bonds and Infrared Spectra of the Topology-Distinct Protonated Water Clusters H3O+(H2O)n−1(n≤ 7)

(2009) Maihemutijiang Jieli et al.   JOURNAL OF PHYSICAL CHEMISTRY A

Optimal construction of a fast and accurate polarisable water potential based on multipole moments trained by machine learning

(2009) Chris M. Handley et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

A Modified MSEVB Force Field for Protonated Water Clusters†

(2008) R. Kumar et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Metadynamics Simulations of the High-Pressure Phases of Silicon Employing a High-Dimensional Neural Network Potential

(2008) Jörg Behler et al.   PHYSICAL REVIEW LETTERS