超级电容器材料数据库使用Web Scraping和自然语言处理生成
Tikam C Soni1, M K Manoj2, M L Verma3
1Department of Metallurgical and Materials Engineering, National Institute of Technology Raipur, Raipur, 492010, (C.G.) India; Department of Metallurgy Engineering, Shri Rawatpura Sarkar University, Raipur, 492015, India.
通过分析研究摘要,创建了一个新的超级电容材料数据库. 该数据库有助于预测和设计先进的电化学储能设备,以实现可持续性.
科学领域:
- 材料科学 材料科学 材料科学
- 电化学 电化学 电化学
- 可持续能源 可持续能源
背景情况:
- 电化学储能对环境可持续性至关重要.
- 超级电容器提供高功率密度和长寿命,使它们成为电池的替代品.
- 现有的研究提供了对超级电容器材料和性能的见解.
研究的目的:
- 开发一个全面的超级电容材料数据库.
- 为了促进下一代超级电容器的预测和设计.
- 为了整合有关电极/电解质材料和设备性能的信息.
主要方法:
- 来自Scopus数据库的文章摘要的网络抓取.
- 使用正则表达式,BatteryBERT语言模型和ChemDataExtractor进行自然语言处理 (NLP).
- 数据提取和组织成一个结构化的数据库.
主要成果:
- 编制了一个包含28269条条目的数据库.
- 数据库包括21个字段,涵盖元数据,材料和性能参数.
- 处理的数据为超级电容研究提供了基础.
结论:
- 建立的数据库代表了超级电容研究的新资源.
- 这种资源可以加速改进超级电容器的发现和开发.
- 该数据库支持电化学能源存储的数据驱动设计和预测.
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