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A Universal Framework for Featurization of Atomistic Systems

Journal Article · · Journal of Physical Chemistry Letters
 [1];  [2]
  1. School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States; OSTI
  2. School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
Not provided.
Research Organization:
Georgia Institute of Technology, Atlanta, GA (United States); Brown Univ., Providence, RI (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0019410; SC0019441
OSTI ID:
1978120
Journal Information:
Journal of Physical Chemistry Letters, Journal Name: Journal of Physical Chemistry Letters Journal Issue: 34 Vol. 13; ISSN 1948-7185
Publisher:
American Chemical Society
Country of Publication:
United States
Language:
English

References (56)

Exploring chemical compound space with quantum-based machine learning journal June 2020
SIMPLE-NN: An efficient package for training and executing neural-network interatomic potentials journal September 2019
Perspective: Machine learning potentials for atomistic simulations journal November 2016
Machine learning in materials informatics: recent applications and prospects journal December 2017
CHARMM: The biomolecular simulation program journal July 2009
Scalable and Memory-Efficient Kernel Ridge Regression conference May 2020
Amp: A modular approach to machine learning in atomistic simulations journal October 2016
High-dimensional neural network potentials for metal surfaces: A prototype study for copper journal January 2012
Structure prediction drives materials discovery journal April 2019
Ab initio molecular dynamics: Concepts, recent developments, and future trends journal May 2005
Adaptive machine learning framework to accelerate ab initio molecular dynamics journal December 2014
Perspective on density functional theory journal April 2012
Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties conference November 2020
Quantum chemistry structures and properties of 134 kilo molecules journal August 2014
Maxwell-Cartesian spherical harmonics in multipole potentials and atomic orbitals journal February 2002
SingleNN: Modified Behler–Parrinello Neural Network with Shared Weights for Atomistic Simulations with Transferability journal July 2020
Critical Assessment of the Performance of Density Functional Methods for Several Atomic and Molecular Properties journal January 2007
The ReaxFF reactive force-field: development, applications and future directions journal March 2016
Towards exact molecular dynamics simulations with machine-learned force fields journal September 2018
The OPLS [optimized potentials for liquid simulations] potential functions for proteins, energy minimizations for crystals of cyclic peptides and crambin journal March 1988
Representing potential energy surfaces by high-dimensional neural network potentials journal April 2014
The Amber biomolecular simulation programs journal January 2005
Molecular dynamics simulations of biomolecules journal September 2002
Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground journal November 2019
PhysNet: A Neural Network for Predicting Energies, Forces, Dipole Moments, and Partial Charges journal April 2019
Open Catalyst 2020 (OC20) Dataset and Community Challenges journal May 2021
Optimizing many-body atomic descriptors for enhanced computational performance of machine learning based interatomic potentials journal July 2019
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning journal January 2012
Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics journal April 2018
Neural network potentials for metals and oxides - First applications to copper clusters at zinc oxide journal November 2012
Role of Molecular Dynamics and Related Methods in Drug Discovery journal February 2016
Gaussian Moments as Physically Inspired Molecular Descriptors for Accurate and Scalable Machine Learning Potentials journal July 2020
High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide journal April 2011
Optimized norm-conserving Vanderbilt pseudopotentials journal August 2013
Hierarchical modeling of molecular energies using a deep neural network journal June 2018
Machine learning unifies the modeling of materials and molecules journal December 2017
Improved adsorption energetics within density-functional theory using revised Perdew-Burke-Ernzerhof functionals journal March 1999
Design and analysis of machine learning exchange-correlation functionals via rotationally invariant convolutional descriptors journal June 2019
Angular Momentum: An Illustrated Guide to Rotational Symmetries for Physical Systems journal July 1995
ReaxFF:  A Reactive Force Field for Hydrocarbons journal October 2001
Ab Initio Molecular Dynamics Simulations of Methylammonium Lead Iodide Perovskite Degradation by Water journal June 2015
Charge Optimized Many Body (COMB) potentials for simulation of nuclear fuel and clad journal June 2018
Ab Initio Molecular Dynamics book January 2009
Potential Energy Surfaces Fitted by Artificial Neural Networks journal March 2010
Enabling robust offline active learning for machine learning potentials using simple physics-based priors journal January 2021
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties journal April 2018
Random-phase approximation and its applications in computational chemistry and materials science journal June 2012
Perspective: Fifty years of density-functional theory in chemical physics journal May 2014
Physics-Inspired Structural Representations for Molecules and Materials journal July 2021
Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals journal April 2017
Efficient and accurate machine-learning interpolation of atomic energies in compositions with many species journal July 2017
Angular Momentum in Quantum Mechanics book January 1957
Review of force fields and intermolecular potentials used in atomistic computational materials research journal September 2018
Alchemical and structural distribution based representation for universal quantum machine learning journal June 2018
ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost journal January 2017
Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces journal April 2007

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