AI材料科学家MatPilot通过人机协作，加速新材料发现。
MatPilot: an LLM-enabled AI Materials Scientist under the Framework of Human-Machine Collaboration
- 基于多智能体系统实现自然语言交互的人机协同
- 可生成科学假说与实验方案并驱动自动化平台
- 适合材料研究团队提升研发效率与迭代能力
人工智能的快速发展，特别是大语言模型的兴起，为材料科学研究带来了前所未有的机遇。我们提出并开发了一位名为MatPilot的AI材料科学家，其在新材料发现方面展现出令人鼓舞的能力。MatPilot的核心优势在于自然语言交互式的人机协同，通过多智能体系统增强人类科研团队的研究能力。该系统融合了人类的独特认知能力、丰富经验与持续好奇心，以及AI智能体在高级抽象、复杂知识存储和高维信息处理方面的优势。它能生成科学假说与实验方案，并利用预测模型与优化算法驱动自动化实验平台开展实验。结果表明，该系统具备高效验证、持续学习与迭代优化的能力。
原文摘要 · Abstract (English)
The rapid evolution of artificial intelligence, particularly large language models, presents unprecedented opportunities for materials science research. We proposed and developed an AI materials scientist named MatPilot, which has shown encouraging abilities in the discovery of new materials. The core strength of MatPilot is its natural language interactive human-machine collaboration, which augments the research capabilities of human scientist teams through a multi-agent system. MatPilot integrates unique cognitive abilities, extensive accumulated experience, and ongoing curiosity of human-beings with the AI agents' capabilities of advanced abstraction, complex knowledge storage and high-dimensional information processing. It could generate scientific hypotheses and experimental schemes, and employ predictive models and optimization algorithms to drive an automated experimental platform for experiments. It turns out that our system demonstrates capabilities for efficient validation, continuous learning, and iterative optimization.
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