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Review  |  Open Access

                                        Journal of Materials

                                                 Informatics


                                          Li et al. J. Mater. Inf. 2026, 6, 10      DOI:10.20517/jmi.2025.87

               Agentic material science




               Chengbo Li , Nian Ran 1,2,*  , Jianjun Liu 1,2,3,*
                         1,2
               Keywords:
               AI agents, material science,
               material creation,
               self-driving laboratories,
               autonomous discovery,
               materials informatics
               Citation: Li, C.; Ran, N.;
               Liu, J. Agentic material
               science. J. Mater. Inf. 2026,
               6, 10.
               https://dx.doi.org/10.20517
               /jmi.2025.87
               Received: 15 Oct 2025
               First Decision: 31 Oct
               2025
               Revised: 15 Nov 2025
               Accepted: 25 Nov 2025  Abstract
               Published: 30 Jan 2026
                                   Artificial intelligence (AI) agents, leveraging capabilities in natural language understanding,
               Academic Editor:    multimodal knowledge fusion, and tool invocation, are driving material science towards a
               Hao Li              new stage of agent-driven. This article systematically reviews the progress of AI agents in
               Copy Editor:        material   science.   It   highlights   their   core   innovation   in   material   knowledge   processing,
               Xing-Yue Zhang
               Production Editor:  structure design, and property calculation, significantly accelerating the materials design
               Xing-Yue Zhang      process.  Furthermore,  the  article  analyzes  the  impact  of  agents  on  experiments,  which
                                   promote   the   automation   of   material   synthesis   and   characterization.   The   integration   of
                                   these capabilities is driving the development of self-driving laboratories, moving the field
                                   towards   end-to-end   autonomous   materials   creation.   By   providing   a   comprehensive
                                   overview of this rapidly developing field, this review aims to clarify the deep integration of
                                   AI agents with material science, thereby accelerating the realization of on-demand material
                                   design.










               1 State Key Laboratory of High Performance Ceramics, Shanghai Institute of Ceramics Chinese Academy of Sciences, Shanghai 200050,
               China.
               2 Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
               3 School of Chemistry and Materials Science, Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences,
               Hangzhou 310024, Zhejiang, China.

               * Correspondence to: Dr. Nian Ran, Prof. Jianjun Liu, State Key Laboratory of High Performance Ceramics, Shanghai Institute of Ceramics
               Chinese Academy of Sciences, Shanghai 200050, China. E-mail: rannian@mail.sic.ac.cn; jliu@mail.sic.ac.cn




               www.oaepublish.com                                    Submit a Manuscript: https://ucenter.oaepublish.com
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