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Cole, Jacqueline M. (ORCID:0000000215528743)

Publications and source records attributed to Cole, Jacqueline M. (ORCID:0000000215528743).

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

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.

Kumar, Pankaj↗

Auto-generating databases of Yield Strength and Grain Size using ChemDataExtractor

Abstract The emerging field of material-based data science requires information-rich databases to generate useful results which are currently sparse in the stress engineering domain. To this end, this study uses the’materials-aware’ text-mining toolkit, ChemDataExtractor, to auto-generate databases of yield-strength and grain-size values by extracting such information from the literature. The precision of the extracted data is 83.0% for yield strength and 78.8% for grain size. The automatically-extracted data were organised into four databases: a Yield Strength, Grain Size, Engineering-Ready Yield Strength and Combined database. For further validation of the databases, the Combined database was used to plot the Hall-Petch relationship for, the alloy, AZ31, and similar results to the literature were found, demonstrating how one can make use of these automatically-extracted datasets.

36 MATERIALS SCIENCE↗