Supercapacitor Materials Database Generated using Web Scrapping and Natural Language Processing

IF 2.7 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS Journal of molecular graphics & modelling Pub Date : 2025-02-13 DOI:10.1016/j.jmgm.2025.108980
Tikam C. Soni , M.K. Manoj , M.L. Verma , Manwendra. K. Tripathi
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Abstract

Electrochemical energy storage plays a vital role in achieving environmental sustainability. Supercapacitors emerge as promising alternatives to batteries due to their high-power density and extended lifespan. Extensive scholarly research has been conducted on supercapacitor energy storage, providing valuable insights into materials and performance parameters. This study presents a comprehensive supercapacitor materials database, created by web scraping the article abstracts from the Scopus database and processing them using Regular Expressions, the BatteryBERT Language Model, and the ChemDataExtractor Python package. The final database comprises 28,269 recorded entries across 21 relevant fields, including metadata, electrode and electrolyte materials, and seven key device performance parameters. This initiative aims to establish a novel database that can support the prediction and design of advanced supercapacitors.

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来源期刊
Journal of molecular graphics & modelling
Journal of molecular graphics & modelling 生物-计算机:跨学科应用
CiteScore
5.50
自引率
6.90%
发文量
216
审稿时长
35 days
期刊介绍: The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design. As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.
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