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Insightful classification of crystal structures using deep learning

Nature communications, 2018-07, Vol.9 (1), p.2775-10, Article 2775

2018

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Big data of materials science: critical role of the descriptor

Physical review letters, 2015-03, Vol.114 (10), p.105503-105503, Article 105503

2015

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Identifying domains of applicability of machine learning models for materials science

Nature communications, 2020-09, Vol.11 (1), p.4428-4428, Article 4428

2020

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New tolerance factor to predict the stability of perovskite oxides and halides

Science advances, 2019-02, Vol.5 (2), p.eaav0693-eaav0693

2019

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Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides

Nature communications, 2022-01, Vol.13 (1), p.419-419, Article 419

2022

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Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning

Nature communications, 2021-10, Vol.12 (1), p.6234-6234, Article 6234

2021

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The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding

npj computational materials, 2022-12, Vol.8 (1), p.1-7, Article 250

2022

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Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats

npj computational materials, 2017-11, Vol.3 (1), p.1-9, Article 46

2017

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Surface-induced crystallization in supercooled tetrahedral liquids

Nature materials, 2009-09, Vol.8 (9), p.726-730

2009

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Automatic identification of crystal structures and interfaces via artificial-intelligence-based electron microscopy

npj computational materials, 2023-10, Vol.9 (1), p.179-11, Article 179

2023

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Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence

npj computational materials, 2023-06, Vol.9 (1), p.112-12, Article 112

2023

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Phenylalanine near Inorganic Surfaces: Conformational Statistics vs Specific Chemistry

Journal of the American Chemical Society, 2008-02, Vol.130 (8), p.2634-2638

2008

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Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery

Topics in catalysis, 2022, Vol.65 (1-4), p.196-206

2022

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Simultaneous learning of several materials properties from incomplete databases with multi-task SISSO

JPhys materials, 2019-04, Vol.2 (2), p.24002

2019

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GAtor: A First-Principles Genetic Algorithm for Molecular Crystal Structure Prediction

Journal of chemical theory and computation, 2018-04, Vol.14 (4), p.2246-2264

2018

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Finding predictive models for singlet fission by machine learning

npj computational materials, 2022-04, Vol.8 (1), p.1-10, Article 70

2022

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TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions

Data mining and knowledge discovery, 2022-09, Vol.36 (5), p.1815-1864

2022

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Free gold clusters: beyond the static, monostructure description

Faraday discussions, 2011, Vol.152, p.153-167

2011

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Data-driven equation for drug–membrane permeability across drugs and membranes

The Journal of chemical physics, 2021-06, Vol.154 (24), p.244114-244114

2021

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Correction to: Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery

Topics in catalysis, 2022, Vol.65 (1-4), p.207-207

2022

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Numerical quality control for DFT-based materials databases

npj computational materials, 2022-04, Vol.8 (1), p.1-8, Article 69

2022

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Ab Initio Approach for Thermodynamic Surface Phases with Full Consideration of Anharmonic Effects: The Example of Hydrogen at Si(100)

Physical review letters, 2022-06, Vol.128 (24), p.246101-246101, Article 246101

2022

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Stability and metastability of clusters in a reactive atmosphere: theoretical evidence for unexpected stoichiometries of MgMOx

Physical review letters, 2013-09, Vol.111 (13), p.135501-135501

2013

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Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery

Data mining and knowledge discovery, 2017-09, Vol.31 (5), p.1391-1418

2017

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Publisher’s Note: “Data-driven equation for drug–membrane permeability across drugs and membranes” [J. Chem. Phys. 154, 244114 (2021)]

The Journal of chemical physics, 2021-07, Vol.155 (3), p.039901-039901

2021

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Insightful classification of crystal structures using deep learning

Big data of materials science: critical role of the descriptor

Identifying domains of applicability of machine learning models for materials science

New tolerance factor to predict the stability of perovskite oxides and halides

Artificial-intelligence-driven discovery of catalyst genes with application to CO2 activation on semiconductor oxides

Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning

The NOMAD Artificial-Intelligence Toolkit: turning materials-science data into knowledge and understanding

Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats

Surface-induced crystallization in supercooled tetrahedral liquids

Automatic identification of crystal structures and interfaces via artificial-intelligence-based electron microscopy

Accelerating materials-space exploration for thermal insulators by mapping materials properties via artificial intelligence

Phenylalanine near Inorganic Surfaces: Conformational Statistics vs Specific Chemistry

Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery

Simultaneous learning of several materials properties from incomplete databases with multi-task SISSO

GAtor: A First-Principles Genetic Algorithm for Molecular Crystal Structure Prediction

Finding predictive models for singlet fission by machine learning

TCMI: a non-parametric mutual-dependence estimator for multivariate continuous distributions

Free gold clusters: beyond the static, monostructure description

Data-driven equation for drug–membrane permeability across drugs and membranes

Correction to: Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery

Numerical quality control for DFT-based materials databases

Ab Initio Approach for Thermodynamic Surface Phases with Full Consideration of Anharmonic Effects: The Example of Hydrogen at Si(100)

Stability and metastability of clusters in a reactive atmosphere: theoretical evidence for unexpected stoichiometries of MgMOx

Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery

Publisher’s Note: “Data-driven equation for drug–membrane permeability across drugs and membranes” [J. Chem. Phys. 154, 244114 (2021)]

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