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Zener pinning through coherent precipitate: A phase-field study

Computational materials science, 2018-11, Vol.154, p.84-90

2018

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Learning in continuous action space for developing high dimensional potential energy models

Nature communications, 2022-01, Vol.13 (1), p.368-368, Article 368

2022

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Tuning the piezoelectric and mechanical properties of the AlN system via alloying with YN and BN

Journal of applied physics, 2017-09, Vol.122 (10)

2017

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Reconfigurable perovskite nickelate electronics for artificial intelligence

Science (American Association for the Advancement of Science), 2022-02, Vol.375 (6580), p.533-539

2022

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Grain boundary driven Plateau–Rayleigh instability in multilayer nanocrystalline thin film: A phase-field study

Materials & design, 2017-04, Vol.119, p.425-436

2017

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Machine learning the metastable phase diagram of covalently bonded carbon

Nature communications, 2022-06, Vol.13 (1), p.3251-3251, Article 3251

2022

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Perovskite neural trees

Nature communications, 2020-05, Vol.11 (1), p.2245-9, Article 2245

2020

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A database of low-energy atomically precise nanoclusters

Scientific data, 2023-05, Vol.10 (1), p.308-308, Article 308

2023

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Erratum: “Learning the stable and metastable phase diagram to accelerate the discovery of metastable phases of boron” [APL Mach. Learn. 2, 016103 (2024)]

APL machine learning, 2024-03, Vol.2 (1), p.019901-019901-1

2024

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Learning the stable and metastable phase diagram to accelerate the discovery of metastable phases of boron

APL machine learning, 2024-03, Vol.2 (1), p.016103-016103-8

2024

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Accelerated prediction of atomically precise cluster structures using on-the-fly machine learning

npj computational materials, 2022-08, Vol.8 (1), p.1-10, Article 173

2022

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CEGANN: Crystal Edge Graph Attention Neural Network for multiscale classification of materials environment

npj computational materials, 2023-02, Vol.9 (1), p.23-12, Article 23

2023

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Large piezoelectric response of van der Waals layered solids

Journal of materials chemistry. C, Materials for optical and electronic devices, 2018, Vol.6 (41), p.11035-11044

2018

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A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery

npj computational materials, 2023-09, Vol.9 (1), p.177-16, Article 177

2023

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Multi-reward reinforcement learning based development of inter-atomic potential models for silica

npj computational materials, 2023-07, Vol.9 (1), p.125-13, Article 125

2023

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High-Entropy 2D Carbide MXenes: TiVNbMoC3 and TiVCrMoC3

ACS nano, 2021-08, Vol.15 (8), p.12815-12825

2021

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Understanding and control of Zener pinning via phase field and ensemble learning

Computational materials science, 2023-10, Vol.229, p.112384, Article 112384

2023

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Thermal regimes of Li‐ion conductivity in β‐eucryptite

Journal of the American Ceramic Society, 2018-01, Vol.101 (1), p.347-355

2018

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Evaluating generalized feature importance via performance assessment of machine learning models for predicting elastic properties of materials

Computational materials science, 2024-03, Vol.236 (C), p.112847, Article 112847

2024

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Elastemp — A workflow to compute the quasi-harmonic temperature dependent elastic constants of materials

Computational materials science, 2023-06, Vol.226, p.112223, Article 112223

2023

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Machine Learning a Simple Interpretable Short-Range Potential for Silica

Journal of chemical theory and computation, 2024-10, Vol.20 (19), p.8665-8674

2024

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Ab Initio-Based Bond Order Potential for Arsenene Polymorphs Developed via Hierarchical Reinforcement Learning

The journal of physical chemistry. A, Molecules, spectroscopy, kinetics, environment, & general theory, 2024-07, Vol.128 (28), p.5752-5761

2024

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Complex Oxides for Brain‐Inspired Computing: A Review

Advanced materials (Weinheim), 2023-09, Vol.35 (37), p.e2203352-e2203352

2023

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Machine-learning of piezoelectric coefficients for wurtzite crystals

Materials and manufacturing processes, 2023-12, Vol.38 (16), p.2081-2092

2023

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Thermal regimes of Li-ion conductivity in [beta]-eucryptite

Journal of the American Ceramic Society, 2018-01, Vol.101 (1), p.347

2018

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Zener pinning through coherent precipitate: A phase-field study

Learning in continuous action space for developing high dimensional potential energy models

Tuning the piezoelectric and mechanical properties of the AlN system via alloying with YN and BN

Reconfigurable perovskite nickelate electronics for artificial intelligence

Grain boundary driven Plateau–Rayleigh instability in multilayer nanocrystalline thin film: A phase-field study

Machine learning the metastable phase diagram of covalently bonded carbon

Perovskite neural trees

A database of low-energy atomically precise nanoclusters

Erratum: “Learning the stable and metastable phase diagram to accelerate the discovery of metastable phases of boron” [APL Mach. Learn. 2, 016103 (2024)]

Learning the stable and metastable phase diagram to accelerate the discovery of metastable phases of boron

Accelerated prediction of atomically precise cluster structures using on-the-fly machine learning

CEGANN: Crystal Edge Graph Attention Neural Network for multiscale classification of materials environment

Large piezoelectric response of van der Waals layered solids

A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery

Multi-reward reinforcement learning based development of inter-atomic potential models for silica

High-Entropy 2D Carbide MXenes: TiVNbMoC3 and TiVCrMoC3

Understanding and control of Zener pinning via phase field and ensemble learning

Thermal regimes of Li‐ion conductivity in β‐eucryptite

Evaluating generalized feature importance via performance assessment of machine learning models for predicting elastic properties of materials

Elastemp — A workflow to compute the quasi-harmonic temperature dependent elastic constants of materials

Machine Learning a Simple Interpretable Short-Range Potential for Silica

Ab Initio-Based Bond Order Potential for Arsenene Polymorphs Developed via Hierarchical Reinforcement Learning

Complex Oxides for Brain‐Inspired Computing: A Review

Machine-learning of piezoelectric coefficients for wurtzite crystals

Thermal regimes of Li-ion conductivity in [beta]-eucryptite

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