
Editor-in-Chief: Prof. Zongyou Yin, Australian National University, Australia.
AI for Materials is a gold open-access, peer-reviewed journal that aims to bridge the dynamic fields of artificial intelligence (AI) and advanced materials research. The journal’s mission is to provide a dedicated, high-impact platform for researchers, engineers, and practitioners to publish pioneering studies that leverage AI-driven methodologies to enhance the discovery, design, development, and application of materials across different scales. More
Collaborative AI Enhances Image Understanding in Materials Science
Ruoyan Avery Yin, Zhichu Ren, Zongyou Yin, Zhen Zhang, So Yeon Kim, Chia-Wei Hsu, Ju Li
2026, 1(1): 6. doi: 10.53941/aimat.2026.100006
Driving Catalytic Innovation: The Development and Application of Machine Learning Force Fields
Xiaoyi Hu, Guanjie Wang, Cuilian Wen, Baisheng Sa
2026, 1(1): 5. doi: 10.53941/aimat.2026.100005
Let Materials Science Data Learn to Reason
Tongao Yao, Aoni Xu, Pengfei Ou, Weijie Yang
2026, 1(1): 4. doi: 10.53941/aimat.2026.100004
Supervised Machine Learning Assisted Development of Hybrid Solvation Model for Simulating Graphene-Water Interface
Jordan Clive Barker, William Wen, Yun Wang
2026, 1(1): 3. doi: 10.53941/aimat.2026.100003
Data Speaks: LLM-Enabled Evidence Auditing Resets the “Migration Barrier” Playbook for Solid-State Electrolytes
Limin Li, Kan Xu, Rui Su, Huan Gu, Piao Ma
2026, 1(1): 2. doi: 10.53941/aimat.2026.100002
Zongyou Yin
2026, 1(1): 1. doi: 10.53941/aimat.2026.100001