Journal ArticleDOI
Neural network predictions of oxygen interactions on a dynamic Pd surface
Jacob R. Boes,John R. Kitchin +1 more
TLDR
Artificial neural networks (NNs) are increasingly common in quantum chemistry applications and can be trained to higher-level ab-initio calculations and are capable of achieving arbitrary results as discussed by the authors.Abstract:
Artificial neural networks (NNs) are increasingly common in quantum chemistry applications. These models can be trained to higher-level ab-initio calculations and are capable of achieving arbitrary...read more
Citations
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Journal ArticleDOI
First Principles Neural Network Potentials for Reactive Simulations of Large Molecular and Condensed Systems.
TL;DR: The methodology of an important class of ML potentials that employs artificial neural networks is considered, which can accelerate computer simulations by several orders of magnitude, while preserving quantum mechanical accuracy.
Journal ArticleDOI
A Critical Review of Machine Learning of Energy Materials
TL;DR: In this article, the authors provide an in-depth, critical review of ML-guided design and discovery of energy materials, a field where a novel material with superior performance (e.g., higher energy density, higher energy conversion efficiency, etc.) can have a transformative impact on the urgent global problem of climate change.
Journal ArticleDOI
Machine learning for heterogeneous catalyst design and discovery
Bryan R. Goldsmith,Jacques A. Esterhuizen,Jin-Xun Liu,Christopher J. Bartel,Christopher Sutton +4 more
TL;DR: In this paper, the authors highlight the ability of ML tools to accelerate catalyst screening by enabling rapid prototyping and revealing active sites and structure-activity relations, which can drive forward rational catalyst design.
Journal ArticleDOI
Four Generations of High-Dimensional Neural Network Potentials.
TL;DR: In this article, the authors present a classification scheme for the family of high-dimensional neural network potentials (HDNNPs) and discuss the applicability and remaining limitations of these potentials along with an outlook at possible future developments.
Journal ArticleDOI
Machine learning for renewable energy materials
TL;DR: Achieving the 2016 Paris agreement goal of limiting global warming below 2 °C and securing a sustainable energy future require materials innovations in renewable energy technologies.
References
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Journal ArticleDOI
Generalized Gradient Approximation Made Simple
TL;DR: A simple derivation of a simple GGA is presented, in which all parameters (other than those in LSD) are fundamental constants, and only general features of the detailed construction underlying the Perdew-Wang 1991 (PW91) GGA are invoked.
Journal ArticleDOI
Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set.
Georg Kresse,Jürgen Furthmüller +1 more
TL;DR: An efficient scheme for calculating the Kohn-Sham ground state of metallic systems using pseudopotentials and a plane-wave basis set is presented and the application of Pulay's DIIS method to the iterative diagonalization of large matrices will be discussed.
Journal ArticleDOI
Projector augmented-wave method
TL;DR: An approach for electronic structure calculations is described that generalizes both the pseudopotential method and the linear augmented-plane-wave (LAPW) method in a natural way and can be used to treat first-row and transition-metal elements with affordable effort and provides access to the full wave function.
Journal ArticleDOI
From ultrasoft pseudopotentials to the projector augmented-wave method
Georg Kresse,Daniel P. Joubert +1 more
TL;DR: In this paper, the formal relationship between US Vanderbilt-type pseudopotentials and Blochl's projector augmented wave (PAW) method is derived and the Hamilton operator, the forces, and the stress tensor are derived for this modified PAW functional.
Journal ArticleDOI
Special points for brillouin-zone integrations
Hendrik J. Monkhorst,J.D. Pack +1 more
TL;DR: In this article, a method for generating sets of special points in the Brillouin zone which provides an efficient means of integrating periodic functions of the wave vector is given, where the integration can be over the entire zone or over specified portions thereof.
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