定量主题 材料分析 科学文献 使用自然语言处理
1Computational Science Research Center, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea.
ACS applied materials & interfaces
|December 7, 2023
概括
这项研究使用自然语言处理来绘制257个材料科学主题,揭示研究趋势和国家利益. 它强调了新兴的跨学科领域,如材料中的机器学习和可穿戴电子产品的未来潜力.
科学领域:
- 材料科学 材料科学 材料科学
- 计算材料科学科学 计算材料科学
背景情况:
- 材料科学研究正在迅速扩大,这使得很难理解不断变化的景观,并确定战略见解.
- 科学出版物的数量和多样性不断增加,给研究人员,政策制定者和行业利益相关者带来了挑战.
研究的目的:
- 开发一种自然语言处理 (NLP) 协议,从大型科学文献中提取文本编码的主题.
- 发现研究兴趣,融合趋势和材料科学的战略格局.
- 为了解当前和未来的材料科学研究方向提供一个框架.
主要方法:
- 使用基于自然语言处理 (NLP) 的协议来分析大量的科学文献.
- 创建了一个主题地图,确定了257个不同的材料科学主题,包括生物相容材料,结构材料,电化学和光子学.
- 建立了一个主题协会网络,以分析跨学科的研究,并确定高中心性的领域.
主要成果:
- 创建了一个材料科学研究领域的综合主题地图,详细介绍了257个主题.
- 分析揭示了国家研究利益和竞争战略,美国在材料科学中早期采用机器学习.
- 期刊级别的分析表明,随着时间的推移,焦点发生了变化,主题协会网络强调了关键的跨学科领域,如机器学习支持的复合建模,能源政策和可穿戴电子产品.
结论:
- 开发的NLP协议有效地绘制了材料科学研究格局,并确定了新兴趋势.
- 该研究提供了对国家研究策略和材料科学跨学科研究未来潜力的宝贵见解.
- 这项工作为所有利益相关者更好地了解材料科学的动态和多样化的领域提供了便利.
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