| 褚旭龙,刘进长,史冬梅.人工智能在材料科学领域的应用发展研究
——基于 WOS 核心数据库的文献计量分析[J].全球科技经济瞭望,2023,38(4):52~61 |
| 人工智能在材料科学领域的应用发展研究
——基于 WOS 核心数据库的文献计量分析 |
| Research of the Application and Development of ArtificialIntelligence in Material Science Field: A Bibliometric AnalysisBased on WOS Core Database |
| 投稿时间：2023-02-20 |
| DOI：10.3772/j.issn.1009-8623.2023.04.008 |
| 中文关键词: 人工智能；交叉科学；材料科学；文献计量 |
| 英文关键词: artificial intelligence; interdisciplinary science; material science; bibliometrics |
| 基金项目: |
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| 摘要点击次数: 1641 |
| 全文下载次数: 846 |
| 中文摘要: |
| 以实验试错法和基于密度泛函理论的方法为代表的传统新材料发现方法，逐渐在开发成本、
效率以及周期等方面显现出不足。人工智能，特别是机器学习和深度学习，综合强大的数据处理和高预
测性能，在材料发现、材料设计、材料检测和材料分析等领域展示出优势，对新材料研发创新具有重要
推动作用。以近 10 年美国信息情报研究所（ISI）下属的 Web of Science（WOS）核心数据库收录的相
关文献为数据源，使用 CiteSpace 软件开展可视化分析，旨在总结分析人工智能在材料科学领域发展
的研究现状、研究热点及其研究发展趋势，为中国人工智能与材料科学融合创新发展提供相关参考，
以期提升研究水平。 |
| 英文摘要: |
| The traditional methods for discovering new materials, including experimental trial-and-error methods
and methods based on density functional theory, gradually show shortcomings in development cost, efficiency and
cycle. Artificial intelligence, especially machine learning and deep learning, combining powerful data processing and
high predictive performance, demonstrates advantages in material discovery, material design, material detection, and
material analysis, and plays an important role in promoting innovation in new material research and development.
This paper uses relevant articles collected from the Web of Science (WOS) core database under the Institute of
Information and Intelligence (ISI) in the past 10 years as the data source, and uses CiteSpace software for visual
analysis, aiming to summarize and analyze the research status, hotspots, and the trends of artificial intelligence in the
field of materials science, and to provide relevant reference for the integrated innovation and development of artificial
intelligence and materials science in China, and improve its research level. |
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