关键词: 智能驱动, 自主实验, 多模态数据库, 智能计算, 大模型

Abstract:

As an important means to accelerate the research and development of new materials and industrial innovation, the intelligent research and development of materials during the whole process promotes the revolutionary transformation of experience-driven material science to the emergence of machine intelligence. This paper examined the technical synergy framework composed of intelligent computing, autonomous experiments, multimodal databases, and domain-specific large models and analyzed the strategic initiatives and divergent implementation paths for research and development of AI-driven materials across different countries. By deconstructing the pivotal roles of large-scale scientific infrastructure, breakthroughs in cross-scale modeling algorithms, and human-machine collaborative knowledge discovery mechanisms, this paper proposed a strategy for intelligence-enhanced discovery grounded in the triadic integration of data, algorithm, and computing power. This strategy offers a systematic solution and a technological evolution framework for establishing an autonomous and controllable paradigm for the research and development of new materials.

Key words: AI-driven, autonomous experimentation, multimodaldatabases, intelligent computation, large model