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Editor-in-Chief: Tong-Yi Zhang
Submission to first decision: 44 days
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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

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Lithium-ion battery health prognosis via electrochemical impedance spectroscopy using CNN-BiLSTM model

Zhihang Liu, ... Yunwei ZhangYunwei Zhang
Open Access Research Article DOI: 10.20517/jmi.2024.09 26 Jun 2024
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Thermal stability prediction of copolymerized polyimides via an interpretable transfer learning model

Yu Zhang, ... Peng DingPeng Ding
Open Access Research Article DOI: 10.20517/jmi.2024.13 16 Jun 2024
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Data-driven strategy for bandgap database construction of perovskites and the potential segregation study

Bobin Wu, ... Haitao Zhao
Open Access Research Article DOI: 10.20517/jmi.2024.10 27 May 2024
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Theoretical design of dendrite-free zinc anode through intrinsic descriptors from symbolic regression

Mengde Kang, ... Cheng Lian
Open Access Research Article DOI: 10.20517/jmi.2023.42 26 May 2024
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Searching new cocrystal structures of CL-20 and HMX via evolutionary algorithm and machine learning potential

Zhong-Hao Ye, ... Xiao-Chun Wang
Open Access Research Article DOI: 10.20517/jmi.2023.37 21 May 2024
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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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A review on high-throughput development of high-entropy alloys by combinatorial methods

Shahryar Mooraj, Wen ChenWen Chen
Open Access Review DOI: 10.20517/jmi.2022.41 16 Mar 2023
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Process parameter optimization of metal additive manufacturing: a review and outlook

Hou Yi Chia, ... Wentao YanWentao Yan
Open Access Review DOI: 10.20517/jmi.2022.18 8 Oct 2022
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Themed Collections
machine learning
Topic: Data-driven Modeling and Design of Quantum Functional Materials
Topic: Computational Thermodynamics, Computational Kinetics and Machine Learning in Advanced Materials
Topic: Machine Learning Approach for Design, Development and Application of High Entropy Materials
Volume 4, Issue 2 (in progress)
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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

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 | 11 May 2022
Views: | Downloads:
Download PDF
A review on high-throughput development of high-entropy alloys by combinatorial methods
Shahryar Mooraj, Wen ChenWen Chen
Open Access | Review | 16 Mar 2023
Views: | Downloads:
Download PDF
Process parameter optimization of metal additive manufacturing: a review and outlook
Hou Yi Chia, ... Wentao YanWentao Yan
Open Access | Review | 8 Oct 2022
Views: | Downloads:
Download PDF
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Journal of Materials Informatics
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