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Machine learning reveals orbital interaction in materials

Science and technology of advanced materials, 2017-10, Vol.18 (1), p.756-765

2017

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Learning structure-property relationship in crystalline materials: A study of lanthanide–transition metal alloys

The Journal of chemical physics, 2018-05, Vol.148 (20), p.204106-204106

2018

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A regression-based model evaluation of the Curie temperature of transition-metal rare-earth compounds

Journal of physics. Conference series, 2019-10, Vol.1290 (1), p.12009

2019

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Application of materials informatics on crystalline materials for two-body terms approximation

Computational materials science, 2019-08, Vol.166, p.155-161

2019

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Explainable machine learning for materials discovery: predicting the potentially formable Nd–Fe–B crystal structures and extracting the structure–stability relationship

IUCrJ, 2020-11, Vol.7 (6), p.1036-1047

2020

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Non-equilibrium critical point in Be-doped low-temperature-grown GaAs

Journal of applied physics, 2013-02, Vol.113 (5)

2013

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Learning Materials Properties from Orbital Interactions

Journal of physics. Conference series, 2019-10, Vol.1290 (1), p.12012

2019

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Committee machine that votes for similarity between materials

IUCrJ, 2018-11, Vol.5 (Pt 6), p.830-840

2018

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Cooperative transition of electronic states of antisite As defects in Be-doped low-temperature-grown GaAs layers

Journal of applied physics, 2011-12, Vol.110 (12), p.123716-123716-7

2011

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Ensemble learning reveals dissimilarity between rare-earth transition-metal binary alloys with respect to the Curie temperature

JPhys materials, 2019-07, Vol.2 (3), p.34009

2019

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Data mining for materials design: a computational study of single molecule magnet

The Journal of chemical physics, 2014-01, Vol.140 (4), p.044101-044101

2014

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A study on carbon nanotube titanium dioxide hybrids: experiment and calculation

Advances in natural sciences. Nanoscience and nanotechnology, 2014-12, Vol.5 (4), p.45018-6

2014

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Pairwise interactions for potential energy surfaces and atomic forces using deep neural networks

Computational materials science, 2022-06, Vol.209, p.111379, Article 111379

2022

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Novel mixture model for the representation of potential energy surfaces

The Journal of chemical physics, 2016-10, Vol.145 (15), p.154103-154103

2016

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Learning hidden chemistry with deep neural networks

Computational materials science, 2021-12, Vol.200, p.110784, Article 110784

2021

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A first-principle study of nonlinear large amplitude vibration and global optimization of 3D penta-graphene plates based on the Bees Algorithm

Acta mechanica, 2020-09, Vol.231 (9), p.3799-3823

2020

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Thermoelectric Properties and Carrier Localization in Ultrathin Layer of Nb‐Doped MoS2

physica status solidi (b), 2018-09, Vol.255 (9), p.n/a

2018

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Transition of electron transport process in Be-doped low-temperature-grown GaAs layer

Journal of applied physics, 2013-08, Vol.114 (8)

2013

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First-principles study of hydrogen-enhanced phosphorus diffusion in silicon

Journal of applied physics, 2016-01, Vol.119 (4)

2016

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Origin of cooperative transition of antisite-Arsenic defects in Be-doped low-temperature-grown GaAs layers

Journal of crystal growth, 2013-09, Vol.378, p.329-332

2013

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Corrigendum: Ensemble learning reveals dissimilarity between rare-earth transition metal binary alloys with respect to the Curie temperature (2019 J. Phys. Mater. 2 034009)

JPhys materials, 2020-01, Vol.3 (1), p.19501

2020

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Ab-initio study of intermolecular interaction and structure of liquid cyclopentasilane

Chemical physics, 2012-05, Vol.400, p.59-64

2012

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First principles study of the physisorption of hydrogen molecule on graphene and carbon nanotube surfaces adhered by Pt atom

Computational materials science, 2010-07, Vol.49 (1), p.S15-S20

2010

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First-principles study of the thermally induced polymerization of cyclopentasilane

Computational materials science, 2010-07, Vol.49 (1), p.S21-S24

2010

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Nonlinear post-buckling and vibration of 2D penta-graphene composite plates

Acta mechanica, 2020-02, Vol.231 (2), p.539-559

2020

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Machine learning reveals orbital interaction in materials

Learning structure-property relationship in crystalline materials: A study of lanthanide–transition metal alloys

A regression-based model evaluation of the Curie temperature of transition-metal rare-earth compounds

Application of materials informatics on crystalline materials for two-body terms approximation

Explainable machine learning for materials discovery: predicting the potentially formable Nd–Fe–B crystal structures and extracting the structure–stability relationship

Non-equilibrium critical point in Be-doped low-temperature-grown GaAs

Learning Materials Properties from Orbital Interactions

Committee machine that votes for similarity between materials

Cooperative transition of electronic states of antisite As defects in Be-doped low-temperature-grown GaAs layers

Ensemble learning reveals dissimilarity between rare-earth transition-metal binary alloys with respect to the Curie temperature

Data mining for materials design: a computational study of single molecule magnet

A study on carbon nanotube titanium dioxide hybrids: experiment and calculation

Pairwise interactions for potential energy surfaces and atomic forces using deep neural networks

Novel mixture model for the representation of potential energy surfaces

Learning hidden chemistry with deep neural networks

A first-principle study of nonlinear large amplitude vibration and global optimization of 3D penta-graphene plates based on the Bees Algorithm

Thermoelectric Properties and Carrier Localization in Ultrathin Layer of Nb‐Doped MoS2

Transition of electron transport process in Be-doped low-temperature-grown GaAs layer

First-principles study of hydrogen-enhanced phosphorus diffusion in silicon

Origin of cooperative transition of antisite-Arsenic defects in Be-doped low-temperature-grown GaAs layers

Corrigendum: Ensemble learning reveals dissimilarity between rare-earth transition metal binary alloys with respect to the Curie temperature (2019 J. Phys. Mater. 2 034009)

Ab-initio study of intermolecular interaction and structure of liquid cyclopentasilane

First principles study of the physisorption of hydrogen molecule on graphene and carbon nanotube surfaces adhered by Pt atom

First-principles study of the thermally induced polymerization of cyclopentasilane

Nonlinear post-buckling and vibration of 2D penta-graphene composite plates

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