https://en.people.cn/n3/2026/0912/c90000-20498946.html

https://www.nature.com/articles/s42256-026-01298-6

The Materials Artificial Intelligence Center of the CAS Shenzhen Institutes of Advanced Technology (SIAT) has developed MatBrain, a dual-model collaborative AI agent for materials research, enabling AI not only to “think” but also to “act.”

Traditional materials research typically requires lengthy development cycles from concept validation to application, involving continuous theoretical analysis, computational screening and experimental trial and error.

Mat-R1 functions as a “materials expert,” handling knowledge comprehension, scientific reasoning and result evaluation, while Mat-T1 serves as a “research executor,” calling materials databases, structure-generation models and computational software. The two models work through repeated cycles of “execute-analyze-feedback-re-execute” to complete research tasks.

The 30-billion-parameter Mat-R1 handles “thinking” — understanding material structures and properties, judging whether computational results are reasonable, and deciding the next research direction. The 14-billion-parameter Mat-T1 handles the “doing” — calling materials databases, crystal structure generation models and property calculation programs.

Results show that MatBrain can complete materials research tasks, including structure generation, property prediction, stability analysis and synthesis route planning, and further participate in open-ended materials discovery. In electrocatalyst applications, the model completed a full research chain from scientific hypothesis formation and generation of 30,000 candidate structures to multi-stage computational screening and experimental validation.