Miah, M. Saef Ullah and Junaida, Sulaiman and Sarwar, Talha and Nur, Ibrahim and Masuduzzaman, Md and Rajan, Jose (2023) An automated materials and processes identification tool for material informatics using deep learning approach. Heliyon, 9 (e20003). ISSN 2405-8440. (Published)
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Abstract
This article reports a tool that enables Materials Informatics, termed as MatRec, via a deep learning approach. The tool captures data, makes appropriate domain suggestions, extracts various entities such as materials and processes, and helps to establish entity-value relationships. This tool uses keyword extraction, a document similarity index to suggest relevant documents, and a deep learning approach employing Bi-LSTM for entity extraction. For example, materials and processes for electrical charge storage under an electric double layer capacitor (EDLC) mechanism are demonstrated herewith. A knowledge graph approach finds and visualizes different latent knowledge sets from the processed information. The MatRec received an F1 score of 9̃6% for entity extraction, 8̃3% for material-value relationship extraction, and 8̃7% for process-value relationship extraction, respectively. The proposed MatRec could be extended to solve material selection issues for various applications and could be an excellent tool for academia and industry.
| Item Type: | Article |
|---|---|
| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | EDLC; Entity-value extraction; Knowledge graph; Material informatics; Materials 4.0; Materials discovery; Process discovery |
| Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Faculty/Division: | Faculty of Industrial Sciences And Technology Institute of Postgraduate Studies Faculty of Computing |
| Depositing User: | Miss Amelia Binti Hasan |
| Date Deposited: | 06 Nov 2023 00:47 |
| Last Modified: | 06 Nov 2023 00:47 |
| URI: | http://umpir.ump.edu.my/id/eprint/39186 |
| Download Statistic: | View Download Statistics |
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