大语言模型在材料科学领域研究进展-中国材料进展

文章信息/Info

Title:: Research Progress of Large Language Models in the Field of Materials Science

作者:: 闫姿霓; 饶梓元; 曾小勤; 1.上海交通大学轻合金精密成型国家研究中心，上海 200240 2.上海交通大学金属基复合材料国家重点实验室，上海 200240

Author(s):: YAN Zini; RAO Ziyuan; ZENG Xiaoqin; 1.National Engineering Research Center of Light Alloy Net Forming，Shanghai Jiao Tong University, Shanghai 200240，China 2.State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China

Keywords:: large language model; natural language processing; artificial intelligence; interpretability; materials science

摘要:: 数据驱动方法已成为材料研究的重要趋势，大语言模型的出现不仅为材料科学领域非结构化数据的处理提供了潜在的解决方案，还能够通过其强大的语言理解和生成能力，助力科研中的知识发现、自动化分析、可解释性提升以及多模块协同操作，从而推动材料科学研究的效率提升与创新突破。文章从大语言模型的理论基础出发，探讨其重要功能、优化方法及其在材料科学中的应用。特别是，大语言模型能够有效处理和提取非结构化文本中的关键信息，帮助加速材料的发现与设计。文章还展望了大语言模型在人工智能与材料科学融合领域的未来发展前景，指出其在推动材料科学研究自动化和智能化方面的巨大潜力。

Abstract:: Data-driven approaches have become an important trend in materials research. The emergence of large language models not only provides a potential solution for processing unstructured data in the field of materials science, but also, through their powerful language understanding and generation capabilities, facilitates knowledge discovery, automated analysis, improved interpretability, and multi-module collaborative operations, thus enhancing research efficiency and driving breakthroughs in materials science. This article explores the theoretical foundations of large language models, examines their key functions, optimization methods, and applications in materials science. In particular, large language models can effectively process and extract key information from unstructured texts, helping to accelerate material discovery and design. The article also envisions the future development of large language models in the integration of artificial intelligence and materials science, highlighting their significant potential in advancing the automation and intelligence of materials research.