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The high-throughput highway to computational materials design

Nature materials, 2013-03, Vol.12 (3), p.191-201

2013

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Machine-learned interatomic potentials for alloys and alloy phase diagrams

npj computational materials, 2021-01, Vol.7 (1), p.1-9, Article 24

2021

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Tensor-Reduced Atomic Density Representations

Physical review letters, 2023-07, Vol.131 (2), p.028001-028001, Article 028001

2023

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Machine-learned multi-system surrogate models for materials prediction

npj computational materials, 2019-04, Vol.5 (1), Article 51

2019

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Comprehensive Search for New Phases and Compounds in Binary Alloy Systems Based on Platinum-Group Metals, Using a Computational First-Principles Approach

Physical review. X, 2013-12, Vol.3 (4), p.041035, Article 041035

2013

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Uncovering Compounds by Synergy of Cluster Expansion and High-Throughput Methods

Journal of the American Chemical Society, 2010-04, Vol.132 (13), p.4830-4833

2010

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Discovering the building blocks of atomic systems using machine learning: application to grain boundaries

npj computational materials, 2017-08, Vol.3 (1), p.1-7, Article 29

2017

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Evolutionary approach for determining first-principles hamiltonians

Nature materials, 2005-05, Vol.4 (5), p.391-394

2005

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Ordered Structures in Rhenium Binary Alloys from First-Principles Calculations

Journal of the American Chemical Society, 2011-01, Vol.133 (1), p.158-163

2011

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First principles thermodynamical modeling of the binodal and spinodal curves in lead chalcogenides

Physical chemistry chemical physics : PCCP, 2016-02, Vol.18 (6), p.5005-5011

2016

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Where are nature's missing structures?

Nature materials, 2007-12, Vol.6 (12), p.941-945

Hart, Gus L. W

2007

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Robustness of the cluster expansion: Assessing the roles of relaxation and numerical error

Physical review. B, 2017-07, Vol.96 (1), Article 014107

2017

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Machine learning predictions of high-Curie-temperature materials

Applied physics letters, 2023-07, Vol.123 (4)

2023

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Effectiveness of smearing and tetrahedron methods: best practices in DFT codes

Modelling and simulation in materials science and engineering, 2021-09, Vol.29 (6), p.65014

2021

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A Set of Moment Tensor Potentials for Zirconium with Increasing Complexity

Journal of chemical theory and computation, 2023-10, Vol.19 (19), p.6848-6856

2023

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Cluster expansion made easy with Bayesian compressive sensing

Physical review. B, Condensed matter and materials physics, 2013-10, Vol.88 (15), Article 155105

2013

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Computational materials science Out of the scalar sand box

Nature materials, 2008-06, Vol.7 (6), p.426-427

Hart, Gus L. W

2008

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Using genetic algorithms to map first-principles results to model hamiltonians : Application to the generalized ising model for alloys

Physical review. B, Condensed matter and materials physics, 2005-10, Vol.72 (16), p.165113.1-165113.13, Article 165113

2005

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Stable ordered structures of binary technetium alloys from first principles

Physical review. B, Condensed matter and materials physics, 2012-01, Vol.85 (1), p.012201-012201, Article 012201

2012

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Compressive sensing as a paradigm for building physics models

Physical review. B, Condensed matter and materials physics, 2013-01, Vol.87 (3)

2013

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Predictions of the Pt8Ti Phase in Unexpected Systems

Journal of the American Chemical Society, 2010-05, Vol.132 (19), p.6851-6854

2010

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A robust algorithm for k-point grid generation and symmetry reduction

Journal of physics communications, 2019-06, Vol.3 (6), p.65009

2019

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Generating derivative structures from multilattices: Algorithm and application to hcp alloys

Physical review. B, Condensed matter and materials physics, 2009-07, Vol.80 (1), Article 014120

2009

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Ordering tendencies in the binary alloys of Rh, Pd, Ir, and Pt: Density functional calculations

Physical review. B, Condensed matter and materials physics, 2006-10, Vol.74 (14), Article 144206

2006

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Boron alloying in GaN

Applied physics letters, 2004-02, Vol.84 (5), p.705-707

2004

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The high-throughput highway to computational materials design

Machine-learned interatomic potentials for alloys and alloy phase diagrams

Tensor-Reduced Atomic Density Representations

Machine-learned multi-system surrogate models for materials prediction

Comprehensive Search for New Phases and Compounds in Binary Alloy Systems Based on Platinum-Group Metals, Using a Computational First-Principles Approach

Uncovering Compounds by Synergy of Cluster Expansion and High-Throughput Methods

Discovering the building blocks of atomic systems using machine learning: application to grain boundaries

Evolutionary approach for determining first-principles hamiltonians

Ordered Structures in Rhenium Binary Alloys from First-Principles Calculations

First principles thermodynamical modeling of the binodal and spinodal curves in lead chalcogenides

Where are nature's missing structures?

Robustness of the cluster expansion: Assessing the roles of relaxation and numerical error

Machine learning predictions of high-Curie-temperature materials

Effectiveness of smearing and tetrahedron methods: best practices in DFT codes

A Set of Moment Tensor Potentials for Zirconium with Increasing Complexity

Cluster expansion made easy with Bayesian compressive sensing

Computational materials science Out of the scalar sand box

Using genetic algorithms to map first-principles results to model hamiltonians : Application to the generalized ising model for alloys

Stable ordered structures of binary technetium alloys from first principles

Compressive sensing as a paradigm for building physics models

Predictions of the Pt8Ti Phase in Unexpected Systems

A robust algorithm for k-point grid generation and symmetry reduction

Generating derivative structures from multilattices: Algorithm and application to hcp alloys

Ordering tendencies in the binary alloys of Rh, Pd, Ir, and Pt: Density functional calculations

Boron alloying in GaN

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