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A multi-criteria decision-making and machine learning approach to predict the tribological behavior of microwave-sintered Ti-0.8Ni–0.3Mo/X wt.% TiB composites

Year: 2026

Type: article

Source: Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science

DOI: 10.1177/09544062261473015

Authors: Chandramohan Anitha, Pandiarajan Balasundar, Noor Mohamed Mohammed Raffic, Maria Dasan Thomas Victor, Thulasiram Ramkumar, Sankara Narayanan Senthil, Balasubramaniyan Karthekeyan Parrthipan, Pandiarajan Narayanasamy

Institutions: Mepco Schlenk Engineering College, Madurai Kamaraj University, P P Savani University

Language: English

Topic: Machine Learning in Materials Science

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: closed

OpenAlex ID: W7172452587

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Cites: 55

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