Jianjun Liu
Shanghai Institute of Ceramics, Chinese Academy of Sciences, Shanghai, 201899, China 

The multi-scale structures and macroscopic properties of ceramic materials are mutually coupled and constrained. The development of integrated structural and functional ceramic materials requires revealing deep level physical and chemical properties, while relying on precise measurement and collaborative regulation of complex and multi-dimensional chemical compositions, multi-scale structures, preparation processes, and multiple physical field conditions. Therefore, the research and development of traditional ceramic materials usually requires reducing the multi-scale structural dimensions of ceramics in order to achieve the establishment of simple scientific models, or rely on scientists'"genius style" innovation or experience trial and error. Artificial intelligence technology has the ability to explore causal relationships that are "mutually coupled" or "deeply hidden" from past calculations and experimental data, providing a new model for understanding the multi­dimensional world of ceramic science and preparing high-performance ceramic materials. This talk focuses on the new progress in the research and development of ceramic materials driven by data science and artificial intelligence technology. We have established a database of ceramic material structure and physicochemical properties, developed artificial intelligence algorithms for material structure design and preparation process optimization, further developed material science large models, grinding sintering process automation experiments, multimodal databases, etc., and constructed a design preparation characterization integrated material intelligence scientist system, Preliminary progress has been made in establishing catalytic material descriptors, designing and preparing high specific energy battery materials, and hyper elastomers.