AI4Materials: Transforming the landscape of materials science and enigneering

作者：Xue Jiang, Dezhen Xue, Yang Bai, William Yi Wang, Jianjun Liu, Mingli Yang, Yanjing Su · 发表于：Review of Materials Research · 年份：2025 · DOI：10.1016/j.revmat.2025.100010 · 被引用次数：20 · 研究领域：Machine Learning in Materials Science、Electronic and Structural Properties of Oxides、Advanced Materials Characterization Techniques

New materials, crucial for economic and technological progress, are prioritized globally with strategies to accelerate their advancement through big data and AI. AI for Materials (AI4Mater) serves as an overall framework for integrating AI into Materials Science and Engineering, which is structured around three main elements: materials data infrastructure, AI4Mater techniques, and applications. This article reviews the development procedure and recent innovations in materials data infrastructure, machine learning in materials, autonomous experiment, intelligent computation, and intelligent manufacture. These efforts aim to foster open access to AI resources and enhance the collective advancement of materials science, ultimately accelerating breakthroughs and elevating the engineering application of new materials in a sustainable manner.