Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W

Machine Learning Force Fields

(2021) Oliver T. Unke et al.   CHEMICAL REVIEWS

Quantum de-trapping and transport of heavy defects in tungsten

(2020) Kazuto Arakawa et al.   NATURE MATERIALS

Microscopic structure of a heavily irradiated material

(2020) P. M. Derlet et al.   Physical Review Materials

Neural network potential from bispectrum components: A case study on crystalline silicon

(2020) Howard Yanxon et al.   JOURNAL OF CHEMICAL PHYSICS

Extrapolating Unconverged GW Energies up to the Complete Basis Set Limit with Linear Regression

(2020) Fabien Bruneval et al.   Journal of Chemical Theory and Computation

Interatomic potentials for irradiation-induced defects in iron

(2020) Rebecca Alexander et al.   JOURNAL OF NUCLEAR MATERIALS

Machine learning surrogate models for prediction of point defect vibrational entropy

(2020) Clovis Lapointe et al.   Physical Review Materials

Vacancy formation energy and its connection with bonding environment in solid: A high-throughput calculation and machine learning study

(2020) YingXing Cheng et al.   COMPUTATIONAL MATERIALS SCIENCE

Sensitivity and dimensionality of atomic environment representations used for machine learning interatomic potentials

(2020) Berk Onat et al.   JOURNAL OF CHEMICAL PHYSICS

Reinforcing materials modelling by encoding the structures of defects in crystalline solids into distortion scores

(2020) Alexandra M. Goryaeva et al.   Nature Communications

Atomic scale simulations for the diffusion-assisted crossing of dislocation anchored by vacancy clusters

(2020) Marie Landeiro Dos Reis et al.   Physical Review Materials

Collision cascades overlapping with self-interstitial defect clusters in Fe and W

(2019) Jesper Byggmästar et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Symmetry-broken self-interstitial defects in chromium, molybdenum, and tungsten

(2019) Pui-Wai Ma et al.   PHYSICAL REVIEW MATERIALS

Pattern Learning Electronic Density of States

(2019) Byung Chul Yeo et al.   Scientific Reports

Ab initio vibrational free energies including anharmonicity for multicomponent alloys

(2019) Blazej Grabowski et al.   npj Computational Materials

Towards better efficiency of interatomic linear machine learning potentials

(2019) Alexandra M. Goryaeva et al.   COMPUTATIONAL MATERIALS SCIENCE

Boltzmann generators: Sampling equilibrium states of many-body systems with deep learning

(2019) Frank Noé et al.   SCIENCE

Rearrangement of interstitial defects in alpha-Fe under extreme condition

(2019) A. Chartier et al.   ACTA MATERIALIA

Unifying machine learning and quantum chemistry with a deep neural network for molecular wavefunctions

(2019) K. T. Schütt et al.   Nature Communications

De novo exploration and self-guided learning of potential-energy surfaces

(2019) Noam Bernstein et al.   npj Computational Materials

KineCluE: A kinetic cluster expansion code to compute transport coefficients beyond the dilute limit

(2019) Thomas Schuler et al.   COMPUTATIONAL MATERIALS SCIENCE

Dynamical stability of radiation-induced C15 clusters in iron

(2019) J. Byggmästar et al.   JOURNAL OF NUCLEAR MATERIALS

Extending the accuracy of the SNAP interatomic potential form

(2018) Mitchell A. Wood et al.   JOURNAL OF CHEMICAL PHYSICS

Unsupervised Calculation of Free Energy Barriers in Large Crystalline Systems

(2018) Thomas D. Swinburne et al.   PHYSICAL REVIEW LETTERS

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

(2018) Thomas D. Swinburne et al.   PHYSICAL REVIEW MATERIALS

Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron

(2018) Daniele Dragoni et al.   PHYSICAL REVIEW MATERIALS

Machine learning determination of atomic dynamics at grain boundaries

(2018) Tristan A. Sharp et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Machine Learning a General-Purpose Interatomic Potential for Silicon

(2018) Albert P. Bartók et al.   Physical Review X

A machine learning approach to model solute grain boundary segregation

(2018) Liam Huber et al.   npj Computational Materials

Screw dislocation structure and mobility in body centered cubic Fe predicted by a Gaussian Approximation Potential

(2018) Francesco Maresca et al.   npj Computational Materials

Learning molecular energies using localized graph kernels

(2017) Grégoire Ferré et al.   JOURNAL OF CHEMICAL PHYSICS

An empirical potential for simulating vacancy clusters in tungsten

(2017) D R Mason et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Fast and scalable prediction of local energy at grain boundaries: machine-learning based modeling of first-principles calculations

(2017) Tomoyuki Tamura et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

Wavelet Scattering Regression of Quantum Chemical Energies

(2017) Matthew Hirn et al.   MULTISCALE MODELING & SIMULATION

Low temperature diffusivity of self-interstitial defects in tungsten

(2017) Thomas D Swinburne et al.   NEW JOURNAL OF PHYSICS

On the stability and mobility of di-vacancies in tungsten

(2017) K. Heinola et al.   NUCLEAR FUSION

Quantum-chemical insights from deep tensor neural networks

(2017) Kristof T. Schütt et al.   Nature Communications

Machine learning unifies the modeling of materials and molecules

(2017) Albert P. Bartók et al.   Science Advances

Accurate force field for molybdenum by machine learning large materials data

(2017) Chi Chen et al.   PHYSICAL REVIEW MATERIALS

An implementation of artificial neural-network potentials for atomistic materials simulations: Performance for TiO 2

(2016) Nongnuch Artrith et al.   COMPUTATIONAL MATERIALS SCIENCE

Unraveling the temperature dependence of the yield strength in single-crystal tungsten using atomistically-informed crystal plasticity calculations

(2016) David Cereceda et al.   INTERNATIONAL JOURNAL OF PLASTICITY

Perspective: Machine learning potentials for atomistic simulations

(2016) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

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

Plastic anisotropy and dislocation trajectory in BCC metals

(2016) Lucile Dezerald et al.   Nature Communications

Fast, vacancy-free climb of prismatic dislocation loops in bcc metals

(2016) Thomas D. Swinburne et al.   Scientific Reports

Gaussian approximation potentials: A brief tutorial introduction

(2015) Albert P. Bartók et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Permutation-invariant distance between atomic configurations

(2015) Grégoire Ferré et al.   JOURNAL OF CHEMICAL PHYSICS

Kinetic Distance and Kinetic Maps from Molecular Dynamics Simulation

(2015) Frank Noé et al.   Journal of Chemical Theory and Computation

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

(2015) A.P. Thompson et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Learning scheme to predict atomic forces and accelerate materials simulations

(2015) V. Botu et al.   PHYSICAL REVIEW B

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

(2015) Atsuto Seko et al.   PHYSICAL REVIEW B

First-principles calculation of defect free energies: General aspects illustrated in the case of bcc Fe

(2015) D. Murali et al.   PHYSICAL REVIEW B

Modeling of the magnetic free energy of self-diffusion in bcc Fe

(2015) N. Sandberg et al.   PHYSICAL REVIEW B

First-principles prediction of kink-pair activation enthalpy on screw dislocations in bcc transition metals: V, Nb, Ta, Mo, W, and Fe

(2015) L. Dezerald et al.   PHYSICAL REVIEW B

Understanding Anharmonicity in fcc Materials: From its Origin toab initioStrategies beyond the Quasiharmonic Approximation

(2015) A. Glensk et al.   PHYSICAL REVIEW LETTERS

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

(2015) Zhenwei Li et al.   PHYSICAL REVIEW LETTERS

Big Data of Materials Science: Critical Role of the Descriptor

(2015) Luca M. Ghiringhelli et al.   PHYSICAL REVIEW LETTERS

Adaptive machine learning framework to accelerateab initiomolecular dynamics

(2014) Venkatesh Botu et al.   INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY

Free energy calculations from adaptive molecular dynamics simulations with adiabatic reweighting

(2014) Lingling Cao et al.   JOURNAL OF CHEMICAL PHYSICS

Stability of self-interstitial clusters with C15 Laves phase structure in iron

(2014) L. Dézerald et al.   JOURNAL OF NUCLEAR MATERIALS

Sparse representation for a potential energy surface

(2014) Atsuto Seko et al.   PHYSICAL REVIEW B

Accuracy and transferability of Gaussian approximation potential models for tungsten

(2014) Wojciech J. Szlachta et al.   PHYSICAL REVIEW B

First-principles calculations for point defects in solids

(2014) Christoph Freysoldt et al.   REVIEWS OF MODERN PHYSICS

Breakdown of the Arrhenius Law in Describing Vacancy Formation Energies: The Importance of Local Anharmonicity Revealed byAb initioThermodynamics

(2014) A. Glensk et al.   Physical Review X

Interatomic potentials for modelling radiation defects and dislocations in tungsten

(2013) M-C Marinica et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

Prediction of the kink-pair formation enthalpy on screw dislocations inα-iron by a line tension model parametrized on empirical potentials and first-principles calculations

(2013) Laurent Proville et al.   PHYSICAL REVIEW B

On representing chemical environments

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

Direct Observation of Interstitial Dislocation Loop Coarsening inα-Iron

(2013) S. Moll et al.   PHYSICAL REVIEW LETTERS

First-principles study on the mobility of screw dislocations in bcc iron

(2012) M. Itakura et al.   ACTA MATERIALIA

Solute–point defect interactions in bcc systems: Focus on first principles modelling in W and RPV steels

(2012) C.S. Becquart et al.   CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE

Quantum effect on thermally activated glide of dislocations

(2012) Laurent Proville et al.   NATURE MATERIALS

Irradiation-Induced Formation of Nanocrystallites withC15Laves Phase Structure in bcc Iron

(2012) M.-C. Marinica et al.   PHYSICAL REVIEW LETTERS

Dislocation-core symmetry and slip planes in tungsten alloys: Ab initio calculations and microcantilever bending experiments

(2011) Hong Li et al.   ACTA MATERIALIA

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

(2011) Jörg Behler   JOURNAL OF CHEMICAL PHYSICS

Ab initio investigation of radiation defects in tungsten: Structure of self-interstitials and specificity of di-vacancies compared to other bcc transition metals

(2011) Lisa Ventelon et al.   JOURNAL OF NUCLEAR MATERIALS

Phase stability, point defects, and elastic properties of W-V and W-Ta alloys

(2011) M. Muzyk et al.   PHYSICAL REVIEW B

Energy landscape of small clusters of self-interstitial dumbbells in iron

(2011) M.-C. Marinica et al.   PHYSICAL REVIEW B

Microstructural evolution of irradiated tungsten: Ab initio parameterisation of an OKMC model

(2010) C.S. Becquart et al.   JOURNAL OF NUCLEAR MATERIALS

Comparison of empirical interatomic potentials for iron applied to radiation damage studies

(2010) L. Malerba et al.   JOURNAL OF NUCLEAR MATERIALS

Free Energy Calculations: An Efficient Adaptive Biasing Potential Method

(2010) Bradley M. Dickson et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Formation energies of point defects at finite temperatures

(2010) B. Grabowski et al.   PHYSICA STATUS SOLIDI B-BASIC SOLID STATE PHYSICS

Charge-optimized many-body potential for the hafnium/hafnium oxide system

(2010) Tzu-Ray Shan et al.   PHYSICAL REVIEW B

Effect of Rhenium on the Dislocation Core Structure in Tungsten

(2010) Lorenz Romaner et al.   PHYSICAL REVIEW LETTERS

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

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

Vibrational contributions to the stability of point defects in bcc iron: A first-principles study

(2009) G. Lucas et al.   NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS

CUR matrix decompositions for improved data analysis

(2009) Michael W. Mahoney et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Kernel methods in machine learning

(2008) Thomas Hofmann et al.   ANNALS OF STATISTICS

The non-Arrhenius migration of interstitial defects in bcc transition metals

(2008) Sergei L. Dudarev   COMPTES RENDUS PHYSIQUE

The AM05 density functional applied to solids

(2008) Ann E. Mattsson et al.   JOURNAL OF CHEMICAL PHYSICS

Adaptive biasing force method for scalar and vector free energy calculations

(2008) Eric Darve et al.   JOURNAL OF CHEMICAL PHYSICS

Formation of stable sessile interstitial complexes in reactions between glissile dislocation loops in bcc Fe

(2008) Dmitry Terentyev et al.   JOURNAL OF NUCLEAR MATERIALS

Long-time convergence of an adaptive biasing force method

(2008) Tony Lelièvre et al.   NONLINEARITY

Effect of theα−γPhase Transition on the Stability of Dislocation Loops in bcc Iron

(2008) S. L. Dudarev et al.   PHYSICAL REVIEW LETTERS

Peierls Potential for Crowdions in the bcc Transition Metals

(2008) S. P. Fitzgerald et al.   PHYSICAL REVIEW LETTERS