A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor

Kumar, Pankaj; Kabra, Saurabh; Cole, Jacqueline M.

doi:10.1038/s41597-024-03979-6

Title: A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor

Journal Article · 23 November 2024 · Scientific Data

DOI: https://doi.org/10.1038/s41597-024-03979-6 · OSTI ID:2478567

Kumar, Pankaj; Kabra, Saurabh;

Abstract There has been an ongoing need for information-rich databases in the mechanical-engineering domain to aid in data-driven materials science. To address the lack of suitable property databases, this study employs the latest version of the chemistry-aware natural-language-processing (NLP) toolkit, ChemDataExtractor, to automatically curate a comprehensive materials database of key stress-strain properties. The database contains information about materials and their cognate properties: ultimate tensile strength, yield strength, fracture strength, Young’s modulus, and ductility values. 720,308 data records were extracted from the scientific literature and organized into machine-readable databases formats. The extracted data have an overall precision, recall and F-score of 82.03%, 92.13% and 86.79%, respectively. The resulting database has been made publicly available, aiming to facilitate data-driven research and accelerate advancements within the mechanical-engineering domain.

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Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 2478567

Journal Information:: Scientific Data, Journal Name: Scientific Data Journal Issue: 1 Vol. 11; ISSN 2052-4463

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor Kumar, Pankaj; Kabra, Saurabh; Cole, Jacqueline figshare https://doi.org/10.6084/m9.figshare.25881025	dataset	January 2024

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