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RESEARCH PAPER · Precision Chemistry · 2026

Materials Databases: Foundations of Modern Digital Materials

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Materials Databases: Foundations of Modern Digital MaterialsOriginalA workflow-centric review of artificial intelligence in solid-state hydrogen storage: toward trustworthy AI for materials design0Discovering new materials knowledge from “old data”6Finding the hidden catalytic knowledge from literature data4i BonD: bond energy database embracing the era of artificial intelligence0Machine learning-driven high-throughput screening of electrocatalysts and electrolytes for electrochemical surfaces and interfaces5Perspective: Why Materials AI Needs More Failure Reporting — A Position on Negative Results as Community Infrastructure0DigMethpy: an AI-empowered digital catalysis platform for methane pyrolysis molten catalyst design3Empowering Polymeric Materials Discovery by Artificial Intelligence2AI agents for MOFs and COFs discovery0Data- and AI-Driven Catalysis Science: From Descriptors to Digital Catalysis for Next-Generation Catalysts0Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery0Interfacial Intelligence for Polymer Brushes: Toward Physics-Grounded Design0

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  1. A workflow-centric review of artificial intelligence in solid-state hydrogen storage: toward trustworthy AI for materials design

    Journal of Materials Chemistry A · 2026-01-01

    Jianghao Cai, Junming Huang, Kang Ma, Yutian Zhuang, Junwei Zhao, Kai Ma, Shuai Dong, Wenfeng Fu, Zhengyang Gao, Weijie Yang

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  2. Discovering new materials knowledge from “old data”

    Chemical Communications · 2026-01-01

    Yuhang Wang, Qian Wang, Qian Wang, Eric Jianfeng Cheng, Hao Li

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  3. Finding the hidden catalytic knowledge from literature data

    EES Catalysis · 2026-01-01

    Yuhang Wang, Yong Wang, Hao Li

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  4. i BonD: bond energy database embracing the era of artificial intelligence

    Digital Discovery · 2026-01-01

    Shen Wang, Qi Yang, Sanzhong Luo, Jin‐Pei Cheng

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  5. Machine learning-driven high-throughput screening of electrocatalysts and electrolytes for electrochemical surfaces and interfaces

    Chemical Communications · 2026-01-01

    Shun Zou, Lipan Luo, Guanyu Wang, Haochen Shen, Haoyun Bai, Guobin Wen, Bohua Ren, Shuangyin Wang

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  6. Perspective: Why Materials AI Needs More Failure Reporting — A Position on Negative Results as Community Infrastructure

    Journal of Computational and Data-Driven Materials Engineering · 2026-01-01

    Anna Novak, Tomáš Hrubý

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  7. DigMethpy: an AI-empowered digital catalysis platform for methane pyrolysis molten catalyst design

    AI Agent · 2026-05-13

    Zihao Cheng, X.L. Huang, Hangwei Liu, Junmei Du, Piao Ma, Hang Yin, Di Zhang, Hao Li, Yuanzheng Chen

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  8. Empowering Polymeric Materials Discovery by Artificial Intelligence

    JACS Au · 2026-08-14

    Chenyao Ma, Linda Zhang, Yuheng Chen, Wei Du, Shangwen Fang, Zihao Jiang, Chuanyu Liu, Xinyu Ma, Rui Su, Gang Wang, Muyao Yu, Dong Zhong, Jie Zhu, Weibo Gong, Huan Gu, Limin Li, Chen Shen, Rui Wu, Zhenghao Wu, Kan Xu, Min Zhou, Donglin He, Xiayun Huang, Shan Jiang, Pengfei Ou, Jiayu Peng, Yuwei Zhang, Jie Zhao, Di Zhang, Piao Ma, Zhenghao Li, Hao Li

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  9. AI agents for MOFs and COFs discovery

    AI Agent · 2026-08-17

    Jiayu Yu, Zihao Jiang, Donglin He

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  10. Data- and AI-Driven Catalysis Science: From Descriptors to Digital Catalysis for Next-Generation Catalysts

    Green Energy & Environment · 2026-09-01

    Linlin Sun, Xiaoshuo Liu, Ding Qianghua, Linda Zhang, Di Zhang, Piao Ma, Zhaoxin Wan, Jiayu Peng, Wenqiang Yang, Ang Cao, Weijie Yang, Hui Li

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  11. Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

    Advanced Functional Materials · 2026-09-03

    Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li

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  12. Interfacial Intelligence for Polymer Brushes: Toward Physics-Grounded Design

    JACS Au · 2026-09-28

    Jie Zhu, Xinran Zhao, Dong Wu, Sarah L. Perry, Hui Li, Zhengdong Cheng, Zhihong Nie

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