☆ 4.8 Review

Gaussian Process Regression for Materials and Molecules

CHEMICAL REVIEWS (2021)

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Amp: A modular approach to machine learning in atomistic simulations

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Molecular simulation of the thermophysical properties and phase behaviour of impure CO2 relevant to CCS

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Acceleration of saddle-point searches with machine learning

Andrew A. Peterson

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Novel mixture model for the representation of potential energy surfaces

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Perspective: Machine learning potentials for atomistic simulations

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Ab Initio Quality NMR Parameters in Solid-State Materials Using a High-Dimensional Neural-Network Representation

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Efficient non-parametric fitting of potential energy surfaces for polyatomic molecules with Gaussian processes

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New Perspectives on the Charging Mechanisms of Supercapacitors

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MOMENT TENSOR POTENTIALS: A CLASS OF SYSTEMATICALLY IMPROVABLE INTERATOMIC POTENTIALS

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Single-Layered Hittorf's Phosphorus: A Wide-Bandgap High Mobility 2D Material

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How van der Waals interactions determine the unique properties of water

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Reproducibility in density functional theory calculations of solids

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

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Structural, electronic and kinetic properties of the phase-change material Ge2Sb2Te5 in the liquid state

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Molecular simulation of the thermophysical properties and phase behaviour of impure CO2 relevant to CCS

Alexander J. Cresswell et al.

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Molecular dynamics study on β-phase vanadium monohydride with machine learning potential

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Crystallization processes in the phase change material Ge2Sb2Te5: Unbiased density functional/molecular dynamics simulations

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Many Molecular Properties from One Kernel in Chemical Space

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QCTFF: On the construction of a novel protein force field

Paul L. A. Popelier

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Gaussian approximation potentials: A brief tutorial introduction

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Ab initio molecular dynamics simulation of liquid water by quantum Monte Carlo

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Big Data Meets Quantum Chemistry Approximations: The Δ-Machine Learning Approach

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Transferable Atomic Multipole Machine Learning Models for Small Organic Molecules

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Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials

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Machine Learning for Quantum Mechanical Properties of Atoms in Molecules

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Machine Learning Predictions of Molecular Properties: Accurate Many-Body Potentials and Nonlocality in Chemical Space

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Density-functional theory guided advances in phase-change materials and memories

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Learning scheme to predict atomic forces and accelerate materials simulations

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

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

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Lattice dynamics and vibrational spectra of the orthorhombic, tetragonal, and cubic phases of methylammonium lead iodide

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

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Density functional theory: Its origins, rise to prominence, and future

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The Centrality of Chemistry

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Adaptive machine learning framework to accelerate ab initio molecular dynamics

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Phosphorene: An Unexplored 2D Semiconductor with a High Hole Mobility

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The Extended Stability Range of Phosphorus Allotropes

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Free Energy Surface Reconstruction from Umbrella Samples Using Gaussian Process Regression

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Development of a First-Principles Water Potential with Flexible Monomers. III. Liquid Phase Properties

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Development of a First Principles Water Potential with Flexible Monomers. II: Trimer Potential Energy Surface, Third Virial Coefficient, and Small Clusters

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Sparse representation for a potential energy surface

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Accuracy and transferability of Gaussian approximation potential models for tungsten

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Quantum chemistry structures and properties of 134 kilo molecules

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β-Rhombohedral Boron: At the Crossroads of the Chemistry of Boron and the Physics of Frustration

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Parametrization and Benchmark of DFTB3 for Organic Molecules

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Development of a First Principles Water Potential with Flexible Monomers: Dimer Potential Energy Surface, VRT Spectrum, and Second Virial Coefficient

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Fast and accurate generation of ab initio quality atomic charges using nonparametric statistical regression

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

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Bulk Liquid Water at Ambient Temperature and Pressure from MP2 Theory

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Fast Crystallization of the Phase Change Compound GeTe by Large-Scale Molecular Dynamics Simulations

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Assessment of interatomic potentials for atomistic analysis of static and dynamic properties of screw dislocations in W

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

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

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Nonlinear Light Scattering and Spectroscopy of Particles and Droplets in Liquids

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ANNUAL REVIEW OF PHYSICAL CHEMISTRY, VOL 63 (2012)

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First-Principles Calculation of NMR Parameters Using the Gauge Including Projector Augmented Wave Method: A Chemist's Point of View

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

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Perspective on density functional theory

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Amorphous structures of Ge/Sb/Te alloys: Density functional simulations

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Thermal transport in phase-change materials from atomistic simulations

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

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Neural network interatomic potential for the phase change material GeTe

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Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

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Efficient First-Principles Calculation of the Quantum Kinetic Energy and Momentum Distribution of Nuclei

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Accurate and Efficient Method for Many-Body van der Waals Interactions

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The inefficiency of re-weighted sampling and the curse of system size in high-order path integration

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SHIFTX2: significantly improved protein chemical shift prediction

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Nucleation mechanism for the direct graphite-to-diamond phase transition

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

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

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MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2010)

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Graphite-diamond phase coexistence study employing a neural-network mapping of the ab initio potential energy surface

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Hypothetical low-energy chiral framework structure of group 14 elements

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Crystal structure prediction via particle-swarm optimization

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

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Boron: Elementary Challenge for Experimenters and Theoreticians

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ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2009)

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Permutationally invariant potential energy surfaces in high dimensionality

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Progress and challenges in the automated construction of Markov state models for full protein systems

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A converse approach to the calculation of NMR shielding tensors

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CUR matrix decompositions for improved data analysis

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Microscopic origin of the fast crystallization ability of Ge-Sb-Te phase-change memory materials

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Phase-change materials for rewriteable data storage

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Generalized neural-network representation of high-dimensional potential-energy surfaces

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USPEX - Evolutionary crystal structure prediction

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A random-sampling high dimensional model representation neural network for building potential energy surfaces

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From graphene to graphite:: Electronic structure around the K point

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Multiparadigm modeling of dynamical crack propagation in silicon using a reactive force field

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Comparison of model potentials for molecular-dynamics simulations of silica -: art. no. 124711

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Thin film deposition of tetrahedral amorphous carbon: a molecular dynamics study

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DIAMOND AND RELATED MATERIALS (2005)

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Multiscale hybrid simulation methods for material systems

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Ab initio potential energy and dipole moment surfaces for H5O+2 -: art. no. 044308

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Fibrous red phosphorus

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Representing high-dimensional potential-energy surfaces for reactions at surfaces by neural networks

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Phosphorus nanorods - Two allotropic modifications of a long-known element

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PROSHIFT: Protein chemical shift prediction using artificial neural networks

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Diamond-like amorphous carbon

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MATERIALS SCIENCE & ENGINEERING R-REPORTS (2002)

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Simulating materials failure by using up to one billion atoms and the world's fastest computer: Work-hardening

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2002)

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Composition, structure, and stability of RuO2(110) as a function of oxygen pressure -: art. no. 035406

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On a connection between kernel PCA and metric multidimensional scaling

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MACHINE LEARNING (2002)

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All-electron magnetic response with pseudopotentials: NMR chemical shifts

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Generalizing the environment-dependent interaction potential for carbon

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Highly optimized empirical potential model of silicon

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MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2000)

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High-quality continuous random networks

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Ab initio study of screw dislocations in Mo and Ta:: A new picture of plasticity in bcc transition metals

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