Efficient Global Structure Optimization with a Machine-Learned Surrogate Model

Bayesian inference of atomistic structure in functional materials

(2019) Milica Todorović et al.   npj Computational Materials

DFTB-Assisted Global Structure Optimization of 13- and 55-Atom Late Transition Metal Clusters

(2019) Maxime Van den Bossche   JOURNAL OF PHYSICAL CHEMISTRY A

Active learning of uniformly accurate interatomic potentials for materials simulation

(2019) Linfeng Zhang et al.   PHYSICAL REVIEW MATERIALS

Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning Model

(2019) José A. Garrido Torres et al.   PHYSICAL REVIEW LETTERS

Surface‐supported cluster catalysis: Ensembles of metastable states run the show

(2019) Borna Zandkarimi et al.   Wiley Interdisciplinary Reviews-Computational Molecular Science

Data-driven learning and prediction of inorganic crystal structures

(2018) Volker L. Deringer et al.   FARADAY DISCUSSIONS

Accelerating CALYPSO structure prediction by data-driven learning of a potential energy surface

(2018) Qunchao Tong et al.   FARADAY DISCUSSIONS

Gaussian process regression for geometry optimization

(2018) Alexander Denzel et al.   JOURNAL OF CHEMICAL PHYSICS

SchNet – A deep learning architecture for molecules and materials

(2018) K. T. Schütt et al.   JOURNAL OF CHEMICAL PHYSICS

Less is more: Sampling chemical space with active learning

(2018) Justin S. Smith et al.   JOURNAL OF CHEMICAL PHYSICS

Local Fluxionality of Surface-Deposited Cluster Catalysts: The Case of Pt7 on Al2O3

(2018) Huanchen Zhai et al.   Journal of Physical Chemistry Letters

Data-Driven Learning of Total and Local Energies in Elemental Boron

(2018) Volker L. Deringer et al.   PHYSICAL REVIEW LETTERS

On-the-Fly Machine Learning of Atomic Potential in Density Functional Theory Structure Optimization

(2018) T. L. Jacobsen et al.   PHYSICAL REVIEW LETTERS

Data-driven learning and prediction of inorganic crystal structures

(2018) Volker L. Deringer et al.   FARADAY DISCUSSIONS

Accelerating CALYPSO structure prediction by data-driven learning of a potential energy surface

(2018) Qunchao Tong et al.   FARADAY DISCUSSIONS

Crystal structure prediction accelerated by Bayesian optimization

(2018) Tomoki Yamashita et al.   PHYSICAL REVIEW MATERIALS

Accelerating high-throughput searches for new alloys with active learning of interatomic potentials

(2018) Konstantin Gubaev et al.   COMPUTATIONAL MATERIALS SCIENCE

Nudged elastic band calculations accelerated with Gaussian process regression

(2017) Olli-Pekka Koistinen et al.   JOURNAL OF CHEMICAL PHYSICS

Addressing uncertainty in atomistic machine learning

(2017) Andrew A. Peterson et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Structure of the SnO2(110)−(4×1) Surface

(2017) Lindsay R. Merte et al.   PHYSICAL REVIEW LETTERS

ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

(2017) J. S. Smith et al.   Chemical Science

Machine learning of accurate energy-conserving molecular force fields

(2017) Stefan Chmiela et al.   Science Advances

Interatomic potential construction with self-learning and adaptive database

(2017) Kazutoshi Miwa et al.   PHYSICAL REVIEW MATERIALS

Acceleration of saddle-point searches with machine learning

(2016) Andrew A. Peterson   JOURNAL OF CHEMICAL PHYSICS

An automated nudged elastic band method

(2016) Esben L. Kolsbjerg et al.   JOURNAL OF CHEMICAL PHYSICS

Ensemble-Average Representation of Pt Clusters in Conditions of Catalysis Accessed through GPU Accelerated Deep Neural Network Fitting Global Optimization

(2016) Huanchen Zhai et al.   Journal of Chemical Theory and Computation

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

Oxygen orders differently under graphene: new superstructures on Ir(111)

(2016) A. J. Martínez-Galera et al.   Nanoscale

AFFCK: Adaptive Force-Field-Assisted ab Initio Coalescence Kick Method for Global Minimum Search

(2015) Huanchen Zhai et al.   Journal of Chemical Theory and Computation

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

(2015) Zhenwei Li et al.   PHYSICAL REVIEW LETTERS

A genetic algorithm for first principles global structure optimization of supported nano structures

(2014) Lasse B. Vilhelmsen et al.   JOURNAL OF CHEMICAL PHYSICS

Grains and grain boundaries in highly crystalline monolayer molybdenum disulphide

(2013) Arend M. van der Zande et al.   NATURE MATERIALS

Oxygen Switching of the Epitaxial Graphene–Metal Interaction

(2012) Rosanna Larciprete et al.   ACS Nano

Oxygen Intercalation under Graphene on Ir(111): Energetics, Kinetics, and the Role of Graphene Edges

(2012) Elin Grånäs et al.   ACS Nano

Superconductive sodalite-like clathrate calcium hydride at high pressures

(2012) H. Wang et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Crystal fingerprint space – a novel paradigm for studying crystal-structure sets

(2010) Mario Valle et al.   ACTA CRYSTALLOGRAPHICA SECTION A

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

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

Nanoalloys:  From Theory to Applications of Alloy Clusters and Nanoparticles

(2008) Riccardo Ferrando et al.   CHEMICAL REVIEWS

Ab initio calculation of carbon clusters. II. Relative stabilities of fullerene and nonfullerene C24

(2008) Wei An et al.   JOURNAL OF CHEMICAL PHYSICS