基于BERTopic主题模型的锂电池前沿监测及主题分析研究

doi:10.19799/j.cnki.2095-4239.2024.0697

储能科学与技术 ›› 2025, Vol. 14 ›› Issue (1): 406-416.doi: 10.19799/j.cnki.2095-4239.2024.0697

基于BERTopic主题模型的锂电池前沿监测及主题分析研究

周洪¹^,²(), 俞海龙³, 王丽平⁴, 黄学杰³()

^1.中国科学院武汉文献情报中心，湖北武汉 430071
^2.中国科学院大学经济与管理学院信息资源管理系，北京 100191
^3.中国科学院物理研究所，北京 100190
^4.电子科技大学材料与能源学院，四川成都 611731

收稿日期:2024-07-29 修回日期:2024-08-28 出版日期:2025-01-28 发布日期:2025-02-25
通讯作者: 黄学杰 E-mail:zhouh@mail.whlib.ac.cn;xjhuang@iphy.ac.cn
作者简介:周洪（1987—），男，副研究员，研究方向为技术创新、战略情报，E-mail：zhouh@mail.whlib.ac.cn；
基金资助:
北京市凝聚态物理实验中心项目(2023BNLCMPKF015);国家自然科学基金(22322903);中国科学院武汉文献情报中心青年领军人才项目(E0KZ451)

Frontier monitoring and topic analysis of lithium batteries based on BERTopic model

Hong ZHOU¹^,²(), Hailong YU³, Liping WANG⁴, Xuejie HUANG³()

^1.National Science Library (Wuhan), Chinese Academy of Sciences, Wuhan 430071, Hubei, China
^2.Department of Information Resources Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100191, China
^3.Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China
^4.School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China

Received:2024-07-29 Revised:2024-08-28 Online:2025-01-28 Published:2025-02-25
Contact: Xuejie HUANG E-mail:zhouh@mail.whlib.ac.cn;xjhuang@iphy.ac.cn

摘要/Abstract

摘要：

随着锂电池领域论文数量的激增和研究主题的日益丰富，准确监测该领域的发展趋势和把握最新研究动向变得日益复杂。通过运用大数据和机器学习技术，采用BERTopic主题模型对Web of Science数据库中的18万余篇锂电池论文进行文本分析，绘制了锂电池领域的主题图，识别了新兴研究主题和高被引主题。结果表明，锂电池研究活动正显著加速，锂硫电池、锂枝晶生长抑制、电池回收和金属回收等新兴主题快速发展，而材料研究如二硫化钼纳米材料、氧化铁电极材料则具有显著的高学术影响力。研究还探讨了《锂电池百篇论文点评系列》对当前锂电池研究主题的监测情况，该系列对多数科学技术主题有良好覆盖。本研究为锂电池领域的主题监测提供了新方法，为政策制定和技术研发提供了情报支持，并为“锂电池百篇论文点评”系列的后续研究提供了参考。

关键词: 锂电池, BERTopic, 新兴主题, 高被引主题, 前沿监测

Abstract:

The number of papers published in the field of lithium batteries is increasing rapidly, and increasingly diverse research topics are being explored. Against this backdrop, accurately monitoring the development trends and understanding the latest research directions in this field has become an increasingly complex task. By applying big data and machine-learning technologies, the BERTopic model was used to conduct text analysis on more than 180000 papers on the lithium battery from the Web of Science database. The topic landscape of this field of study was mapped, and emerging research topics and highly cited topics were identified. The results show that research on lithium batteries is significantly accelerating, and the emerging topics are lithium–sulfur batteries, dendrite growth inhibition, battery recycling, and metal recycling rapidly developing. Meanwhile, material research topics such as molybdenum disulfide nanomaterials and iron oxide electrode materials have significant academic influence. The study also discusses the monitoring of current lithium battery research topics by the "Reviews of selected 100 recent papers for lithium batteries", which has good coverage of most scientific and technological topics. This research provides a new method for topic monitoring in the field of lithium batteries, offering intelligence support for policy-making and technological development and providing references for subsequent research in the "Reviews of selected 100 recent papers for lithium batteries."

Key words: lithium batteries, BERTopic, emerging topics, highly cited topic, frontier monitoring

中图分类号:

TM 911

周洪, 俞海龙, 王丽平, 黄学杰. 基于BERTopic主题模型的锂电池前沿监测及主题分析研究[J]. 储能科学与技术, 2025, 14(1): 406-416.

Hong ZHOU, Hailong YU, Liping WANG, Xuejie HUANG. Frontier monitoring and topic analysis of lithium batteries based on BERTopic model[J]. Energy Storage Science and Technology, 2025, 14(1): 406-416.

图/表 6

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基于BERTopic主题模型的锂电池前沿监测及主题分析研究

Frontier monitoring and topic analysis of lithium batteries based on BERTopic model

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