4.8 Article

Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Multidisciplinary Sciences

Learning local equivariant representations for large-scale atomistic dynamics

Albert Musaelian et al.

Summary: This study introduces Allegro, a local equivariant deep neural network interatomic potential architecture that achieves excellent accuracy and scalability in quantum chemistry and molecular simulations.

NATURE COMMUNICATIONS (2023)

Article Multidisciplinary Sciences

E(3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials

Simon Batzner et al.

Summary: This paper introduces an E(3)-equivariant deep learning method for accelerating molecular dynamics simulations. The method shows state-of-the-art accuracy and remarkable sample efficiency in faithfully describing the dynamics of complex systems. The Neural Equivariant Interatomic Potentials (NequIP) approach employs E(3)-equivariant convolutions to interact with geometric tensors, resulting in a more information-rich and faithful representation of atomic environments. NequIP outperforms existing models with significantly fewer training data, challenging the commonly held belief about the necessity of massive training sets for deep neural networks.

NATURE COMMUNICATIONS (2022)

Article Computer Science, Interdisciplinary Applications

A universal graph deep learning interatomic potential for the periodic table

Chi Chen et al.

Summary: This study presents a universal interatomic potential (IAP) model for materials based on graph neural networks, which has broad applications in structural relaxation, dynamic simulations, and property prediction. The study also identifies a large number of synthesizable materials with stability and exceptional properties.

NATURE COMPUTATIONAL SCIENCE (2022)

Article Materials Science, Multidisciplinary

Effects of thermal, elastic, and surface properties on the stability of SiC polytypes

Senja Ramakers et al.

Summary: This paper investigates the thermodynamic stability of different SiC polytypes and identifies that the differences in surface energy are likely the driving force for nucleation, while the differences in bulk thermodynamic stability slightly favor certain polytypes.

PHYSICAL REVIEW B (2022)

Article Materials Science, Ceramics

Phase transitions and elastic anisotropies of SiC polymorphs under high pressure

Zheng Ran et al.

Summary: This study investigated the structures, equations of state, phase transitions, mechanical stability, and elastic anisotropies of five SiC polymorphs under pressure through first-principles calculations. A new phase transition criterion was developed, and the negative Poisson's ratio of zinc blende SiC was verified.

CERAMICS INTERNATIONAL (2021)

Article Chemistry, Physical

Bayesian force fields from active learning for simulation of inter-dimensional transformation of stanene

Yu Xie et al.

Summary: A method is presented to significantly accelerate Gaussian process models for interatomic force fields by mapping forces and uncertainties onto low-dimensional features. This allows for automated active learning of models combining near-quantum accuracy, built-in uncertainty, and comparable evaluation cost to classical analytical models, capable of simulating millions of atoms. Large-scale molecular dynamics simulations of the stability of the stanene monolayer reveal an unusual phase transformation mechanism of 2D stanene.

NPJ COMPUTATIONAL MATERIALS (2021)

Article Physics, Applied

The study of the optical phonon frequency of 3C-SiC by molecular dynamics simulations with deep neural network potential

Wei Chen et al.

Summary: In this work, molecular dynamics simulations with deep neural network potential trained with datasets from ab initio calculations were used to determine the dielectric spectra of crystal. The results showed good agreement with experimental measurements, demonstrating the ability to carry out MD simulations for large systems to obtain dielectric properties with the accuracy of ab initio calculations.

JOURNAL OF APPLIED PHYSICS (2021)

Article Chemistry, Multidisciplinary

A transferable active-learning strategy for reactive molecular force fields

Tom A. Young et al.

Summary: This study presents a method of using machine learning to construct fast, accurate, and reactive interatomic potentials for predictive molecular simulations. By leveraging hierarchical and active learning, accurate Gaussian Approximation Potential (GAP) models can be developed autonomously for diverse chemical systems.

CHEMICAL SCIENCE (2021)

Article Chemistry, Physical

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

Jonathan Vandermause et al.

NPJ COMPUTATIONAL MATERIALS (2020)

Proceedings Paper Physics, Condensed Matter

First Principle Study of Structural, Electronic and Vibrational Properties of 3C-SiC

Tavneet Kaur et al.

DAE SOLID STATE PHYSICS SYMPOSIUM 2019 (2020)

Article Computer Science, Artificial Intelligence

In operando active learning of interatomic interaction during large-scale simulations

M. Hodapp et al.

MACHINE LEARNING-SCIENCE AND TECHNOLOGY (2020)

Article Chemistry, Physical

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

Chi Chen et al.

CHEMISTRY OF MATERIALS (2019)

Article Materials Science, Multidisciplinary

In situ observation of a phase transition in silicon carbide under shock compression using pulsed x-ray diffraction

S. J. Tracy et al.

PHYSICAL REVIEW B (2019)

Article Computer Science, Artificial Intelligence

A fast neural network approach for direct covariant forces prediction in complex multi-element extended systems

Jonathan P. Mailoa et al.

NATURE MACHINE INTELLIGENCE (2019)

Article Physics, Multidisciplinary

Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics

Linfeng Zhang et al.

PHYSICAL REVIEW LETTERS (2018)

Article Chemistry, Physical

Si/C/H ReaxFF Reactive Potential for Silicon Surfaces Grafted with Organic Molecules

Federico A. Soria et al.

JOURNAL OF PHYSICAL CHEMISTRY C (2018)

Article Geochemistry & Geophysics

Equation of State of SiC at Extreme Conditions: New Insight Into the Interior of Carbon-Rich Exoplanets

F. Miozzi et al.

JOURNAL OF GEOPHYSICAL RESEARCH-PLANETS (2018)

Article Materials Science, Multidisciplinary

Efficient nonparametric n-body force fields from machine learning

Aldo Glielmo et al.

PHYSICAL REVIEW B (2018)

Article Materials Science, Multidisciplinary

Active learning of linearly parametrized interatomic potentials

Evgeny V. Podryabinkin et al.

COMPUTATIONAL MATERIALS SCIENCE (2017)

Article Materials Science, Multidisciplinary

Phonon thermal transport in 2H, 4H and 6H silicon carbide from first principles

Nakib Haider Protik et al.

MATERIALS TODAY PHYSICS (2017)

Article Materials Science, Multidisciplinary

Zinc-blende to rocksalt transition in SiC in a laser-heated diamond-anvil cell

Kierstin Daviau et al.

PHYSICAL REVIEW B (2017)

Article Materials Science, Multidisciplinary

Robust structural identification via polyhedral template matching

Peter Mahler Larsen et al.

MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2016)

Article Mathematics, Interdisciplinary Applications

MOMENT TENSOR POTENTIALS: A CLASS OF SYSTEMATICALLY IMPROVABLE INTERATOMIC POTENTIALS

Alexander V. Shapeev

MULTISCALE MODELING & SIMULATION (2016)

Article Materials Science, Multidisciplinary

First principle investigation of phase transition and thermodynamic properties of SiC

W. H. Lee et al.

COMPUTATIONAL MATERIALS SCIENCE (2015)

Article Computer Science, Interdisciplinary Applications

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

A. P. Thompson et al.

JOURNAL OF COMPUTATIONAL PHYSICS (2015)

Article Materials Science, Multidisciplinary

Distributions of phonon lifetimes in Brillouin zones

Atsushi Togo et al.

PHYSICAL REVIEW B (2015)

Article Physics, Multidisciplinary

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

Zhenwei Li et al.

PHYSICAL REVIEW LETTERS (2015)

Article Nanoscience & Nanotechnology

First principles phonon calculations in materials science

Atsushi Togo et al.

SCRIPTA MATERIALIA (2015)

Article Astronomy & Astrophysics

A POSSIBLE CARBON-RICH INTERIOR IN SUPER-EARTH 55 Cancri e

Nikku Madhusudhan et al.

ASTROPHYSICAL JOURNAL LETTERS (2012)

Article Materials Science, Multidisciplinary

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

Alexander Stukowski

MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2010)

Article Physics, Multidisciplinary

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

Albert P. Bartok et al.

PHYSICAL REVIEW LETTERS (2010)

Article Physics, Condensed Matter

Ab initio molecular dynamics simulation of a pressure induced zinc blende to rocksalt phase transition in SiC

H. Y. Xiao et al.

JOURNAL OF PHYSICS-CONDENSED MATTER (2009)

Article Physics, Condensed Matter

First-principles study of pressure-induced phase transition in silicon carbide

Yu-Ping Lu et al.

PHYSICA B-CONDENSED MATTER (2008)

Article Physics, Multidisciplinary

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

Joerg Behler et al.

PHYSICAL REVIEW LETTERS (2007)

Article Physics, Applied

Hugoniot and strength behavior of silicon carbide

TJ Vogler et al.

JOURNAL OF APPLIED PHYSICS (2006)

Article Materials Science, Multidisciplinary

Analytical potential for atomistic simulations of silicon, carbon, and silicon carbide

P Erhart et al.

PHYSICAL REVIEW B (2005)

Article Physics, Condensed Matter

Pressure-induced phase transition of SiC

M Durandurdu

JOURNAL OF PHYSICS-CONDENSED MATTER (2004)

Article Physics, Multidisciplinary

Molecular dynamics simulation of structural transformation in silicon carbide under pressure

F Shimojo et al.

PHYSICAL REVIEW LETTERS (2000)