Agentic material science

AI agents, leveraging capabilities in natural language understanding, multimodal knowledge fusion, and tool invocation, are driving material science towards a new stage of agent-driven. This article systematically reviews the progress of AI agents in material science. It highlights their core innovation in material knowledge processing, structure design, and property calculation, significantly accelerating the materials design 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.