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Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron
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journal
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January 2018 |
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New empirical approach for the structure and energy of covalent systems
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journal
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April 1988 |
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An entropy-maximization approach to automated training set generation for interatomic potentials
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journal
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September 2020 |
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Atomic cluster expansion of scalar, vectorial, and tensorial properties including magnetism and charge transfer
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journal
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July 2020 |
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The MLIP package: Moment Tensor Potentials with MPI and Active Learning
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journal
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November 2020 |
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SchNet – A deep learning architecture for molecules and materials
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journal
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June 2018 |
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Moment tensor potentials as a promising tool to study diffusion processes
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journal
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June 2019 |
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Extending the accuracy of the SNAP interatomic potential form
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journal
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June 2018 |
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Training data selection for accuracy and transferability of interatomic potentials
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journal
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September 2022 |
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On representing chemical environments
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journal
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May 2013 |
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On-the-fly machine learning force field generation: Application to melting points
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journal
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July 2019 |
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Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials
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journal
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January 2016 |
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Machine Learning a General-Purpose Interatomic Potential for Silicon
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journal
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December 2018 |
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An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO2
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journal
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March 2016 |
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Atomic cluster expansion for accurate and transferable interatomic potentials
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journal
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January 2019 |
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Representing potential energy surfaces by high-dimensional neural network potentials
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journal
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April 2014 |
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Accuracy and transferability of Gaussian approximation potential models for tungsten
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journal
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September 2014 |
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A simple empirical N -body potential for transition metals
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journal
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July 1984 |
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E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials
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journal
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May 2022 |
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Environment-dependent interatomic potential for bulk silicon
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journal
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October 1997 |
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Performant implementation of the atomic cluster expansion (PACE) and application to copper and silicon
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journal
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June 2021 |
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Permutationally invariant potential energy surfaces in high dimensionality
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journal
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October 2009 |
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Proper orthogonal descriptors for efficient and accurate interatomic potentials
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journal
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May 2023 |
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Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide
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journal
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July 2020 |
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Efficient parametrization of the atomic cluster expansion
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journal
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January 2022 |
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ReaxFF: A Reactive Force Field for Hydrocarbons
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journal
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October 2001 |
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Atom-centered symmetry functions for constructing high-dimensional neural network potentials
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journal
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February 2011 |
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Machine learning based interatomic potential for amorphous carbon
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journal
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March 2017 |
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Neural network models of potential energy surfaces
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journal
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September 1995 |
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Gaussian approximation potential modeling of lithium intercalation in carbon nanostructures
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journal
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June 2018 |
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Incompleteness of Atomic Structure Representations
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journal
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October 2020 |
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DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics
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journal
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July 2018 |
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Performance and Cost Assessment of Machine Learning Interatomic Potentials
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journal
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October 2019 |
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Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
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journal
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April 2010 |
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Data-Driven Learning of Total and Local Energies in Elemental Boron
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journal
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April 2018 |
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Computer simulation of local order in condensed phases of silicon
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journal
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April 1985 |
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Embedded-atom method: Derivation and application to impurities, surfaces, and other defects in metals
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journal
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June 1984 |
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Machine learning unifies the modeling of materials and molecules
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journal
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December 2017 |
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Regularised atomic body-ordered permutation-invariant polynomials for the construction of interatomic potentials
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journal
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February 2020 |
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Gaussian Process Regression for Materials and Molecules
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journal
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August 2021 |
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Modified embedded-atom potentials for cubic materials and impurities
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journal
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August 1992 |
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Four Generations of High-Dimensional Neural Network Potentials
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journal
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March 2021 |
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Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions
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journal
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June 2018 |
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Physics-Inspired Structural Representations for Molecules and Materials
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journal
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July 2021 |
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How robust are modern graph neural network potentials in long and hot molecular dynamics simulations?
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journal
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November 2022 |
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Active learning of linearly parametrized interatomic potentials
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journal
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December 2017 |
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Machine learning potentials for complex aqueous systems made simple
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journal
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September 2021 |
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LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
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journal
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February 2022 |
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A second-generation reactive empirical bond order (REBO) potential energy expression for hydrocarbons
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journal
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January 2002 |
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Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials
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journal
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March 2015 |
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Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces
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journal
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April 2007 |