Applications of natural language processing and large language models in materials discovery

被引:0
|
作者
Xue Jiang [1 ]
Weiren Wang [2 ]
Shaohan Tian [1 ]
Hao Wang [1 ]
Turab Lookman [1 ]
Yanjing Su [3 ]
机构
[1] University of Science and Technology Beijing,Beijing Advanced Innovation Center for Materials Genome Engineering, Institute for Advanced Materials and Technology
[2] Liaoning Academy of Materials,undefined
[3] AiMaterials Research LLC,undefined
[4] Suzhou Laboratory,undefined
关键词
D O I
10.1038/s41524-025-01554-0
中图分类号
学科分类号
摘要
The transformative impact of artificial intelligence (AI) technologies on materials science has revolutionized the study of materials problems. By leveraging well-characterized datasets derived from the scientific literature, AI-powered tools such as Natural Language Processing (NLP) have opened new avenues to accelerate materials research. The advances in NLP techniques and the development of large language models (LLMs) facilitate the efficient extraction and utilization of information. This review explores the application of NLP tools in materials science, focusing on automatic data extraction, materials discovery, and autonomous research. We also discuss the challenges and opportunities associated with utilizing LLMs and outline the prospects and advancements that will propel the field forward.
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