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An automated materials and processes identification tool for material informatics using deep learning approach.

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.

SUBMITTER: Miah MSU

PROVIDER: S-EPMC10559754 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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An automated materials and processes identification tool for material informatics using deep learning approach.

Miah M Saef Ullah MSU Sulaiman Junaida J Sarwar Talha Bin TB Ibrahim Nur N Masuduzzaman Md M Jose Rajan R

Heliyon 20230914 9

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 ...[more]

PMID: 37809409

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Dataset Information

An automated materials and processes identification tool for material informatics using deep learning approach.

Publications

An automated materials and processes identification tool for material informatics using deep learning approach.

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