Journal of Materials Informatics

Local environment interaction-based machine learning framework for predicting molecular adsorption energy

Molecular adsorption, feature engineering, neural networks

Clustering molecular energy landscapes by adaptive network embedding

Network embedding, metadynamics, transition path theory, energy landscapes

Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm

Neural network potential, genetic algorithm, age-fitness, Pareto optimization, crystal structure prediction

High hydrogen evolution activities of dual-metal atoms incorporated N-doped graphenes achieved by coordination regulation

Hydrogen evolution reaction, density functional calculations, N-doped graphene, dual-atom catalyst, coordination regulation

Domain knowledge-guided interpretive machine learning: formula discovery for the oxidation behavior of ferritic-martensitic steels in supercritical water

Accelerated development of hard high-entropy alloys with data-driven high-throughput experiments

Articles

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Local environment interaction-based machine learning framework for predicting molecular adsorption energy

Yifan Li, ... Lei Shen

Open Access Research Article DOI: 10.20517/jmi.2023.41 29 Mar 2024

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Clustering molecular energy landscapes by adaptive network embedding

Paula Mercurio, Di Liu

Open Access Research Article DOI: 10.20517/jmi.2023.40 26 Mar 2024

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Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm

Sadman Sadeed Omee, ... Jianjun Hu

Open Access Research Article DOI: 10.20517/jmi.2023.33 1 Mar 2024

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High hydrogen evolution activities of dual-metal atoms incorporated N-doped graphenes achieved by coordination regulation

Cunjin Zhang, ... Peng Jin

Open Access Research Article DOI: 10.20517/jmi.2023.34 2 Jan 2024

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Computational design of spatially confined triatomic catalysts for nitrogen reduction reaction

Wei Pei

, ... Jijun Zhao

Open Access Research Article DOI: 10.20517/jmi.2023.35 20 Dec 2023

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Most Cited Papers In Last Two Years

Domain knowledge-guided interpretive machine learning: formula discovery for the oxidation behavior of ferritic-martensitic steels in supercritical water

Bin Cao, ... Tong-Yi Zhang

Open Access Research Article DOI: 10.20517/jmi.2022.04 11 May 2022

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Process parameter optimization of metal additive manufacturing: a review and outlook

Hou Yi Chia, ... Wentao Yan

Open Access Review DOI: 10.20517/jmi.2022.18 8 Oct 2022

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High-entropy alloy catalysts: high-throughput and machine learning-driven design

Lixin Chen, ... Yu Zou

Open Access Review DOI: 10.20517/jmi.2022.23 21 Nov 2022

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Webinars

Ongoing Special Issues

Topic: Breakthroughs in Carbon Nanomaterials Design and Applications Using Machine Learning

Prof. Dr. -Ing. Timon Rabczuk

Submission Deadline: 31 Aug 2024

Published articles: 0

Topic: Machine Learning Techniques in Additive Manufacturing: Design, Processes and Production Control

Prof. Dazhong Wu

Submission Deadline: 31 Aug 2024

Published articles: 0

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316

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machine learning

Topics Collection

Topic: Computational Thermodynamics, Computational Kinetics and Machine Learning in Advanced Materials

Topic: Machine Learning Approach for Design, Development and Application of High Entropy Materials

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Editor-in-Chief: Yuping Wu

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News

Announcement of the 2023 “Best Paper Awards”

Six Editorial Board Members of Journal of Materials Informatics Featured in the Clarivate 2023 “Highly Cited Researchers”

Local environment interaction-based machine learning framework for predicting molecular adsorption energy

Molecular adsorption, feature engineering, neural networks

Clustering molecular energy landscapes by adaptive network embedding

Network embedding, metadynamics, transition path theory, energy landscapes

Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm

Neural network potential, genetic algorithm, age-fitness, Pareto optimization, crystal structure prediction

High hydrogen evolution activities of dual-metal atoms incorporated N-doped graphenes achieved by coordination regulation

Hydrogen evolution reaction, density functional calculations, N-doped graphene, dual-atom catalyst, coordination regulation

Domain knowledge-guided interpretive machine learning: formula discovery for the oxidation behavior of ferritic-martensitic steels in supercritical water

Accelerated development of hard high-entropy alloys with data-driven high-throughput experiments

Webinars

Ongoing Special Issues

Topic: Breakthroughs in Carbon Nanomaterials Design and Applications Using Machine Learning

Prof. Dr. -Ing. Timon Rabczuk

Submission Deadline: 31 Aug 2024

Published articles: 0

Topic: Machine Learning Techniques in Additive Manufacturing: Design, Processes and Production Control

Prof. Dazhong Wu

Submission Deadline: 31 Aug 2024

Published articles: 0

Related Journals

Energy Materials

Editor-in-Chief: Yuping Wu

Intelligence & Robotics

Editor-in-Chief: Simon X. Yang

News

Announcement of the 2023 “Best Paper Awards”

Six Editorial Board Members of Journal of Materials Informatics Featured in the Clarivate 2023 “Highly Cited Researchers”

Data

316

Authors

256

Reviewers

Articles

On Board Editors

2021

Published Since

Special Issues

99,864

Article Views

39,320

Article Downloads

Journal of Materials Informatics

Domain knowledge-guided interpretive machine learning: formula discovery for the oxidation behavior of ferritic-martensitic steels in supercritical water

Accelerated development of hard high-entropy alloys with data-driven high-throughput experiments

Articles

Local environment interaction-based machine learning framework for predicting molecular adsorption energy

Clustering molecular energy landscapes by adaptive network embedding

Crystal structure prediction using neural network potential and age-fitness Pareto genetic algorithm

High hydrogen evolution activities of dual-metal atoms incorporated N-doped graphenes achieved by coordination regulation

Computational design of spatially confined triatomic catalysts for nitrogen reduction reaction

Domain knowledge-guided interpretive machine learning: formula discovery for the oxidation behavior of ferritic-martensitic steels in supercritical water

Process parameter optimization of metal additive manufacturing: a review and outlook

High-entropy alloy catalysts: high-throughput and machine learning-driven design

Topic: Breakthroughs in Carbon Nanomaterials Design and Applications Using Machine Learning

Topic: Machine Learning Techniques in Additive Manufacturing: Design, Processes and Production Control

Energy Materials

Intelligence & Robotics

Domain knowledge-guided interpretive machine learning: formula discovery for the oxidation behavior of ferritic-martensitic steels in supercritical water

Accelerated development of hard high-entropy alloys with data-driven high-throughput experiments

Topic: Breakthroughs in Carbon Nanomaterials Design and Applications Using Machine Learning

Topic: Machine Learning Techniques in Additive Manufacturing: Design, Processes and Production Control

Energy Materials

Intelligence & Robotics

Announcement of the 2023 “Best Paper Awards”

Six Editorial Board Members of Journal of Materials Informatics Featured in the Clarivate 2023 “Highly Cited Researchers”

Committee on Publication Ethics

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Committee on Publication Ethics

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