Chapter VIII. Artificial Intelligence for Improving the Mechanical Properties of Materials

Кирилаха, Світлана (orcid.org/0009-0001-5688-5616) (2025) Chapter VIII. Artificial Intelligence for Improving the Mechanical Properties of Materials . ФОП Ямчинський О.В., м. Київ, Україна, pp. 105-112. ISBN 978-617-8830-09-0

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Abstract

The aim of this work is to test the effectiveness of a machine learning algorithm based on data from open databases, specifically Material Project. The artificial intelligence used, based on linear regression, applies transfer learning to adapt to the physicochemical models of high-entropy alloys. Open Python modules are used for implementation, providing flexibility in research. The accuracy of modeling the physicochemical properties of the material depends on the number of elements in the composition and the ability to combine materials into a single system. To verify the experimental results in practice, the Vickers hardness method, based on literature sources, is shown, which allowed for the assessment of the correctness of the proposed approach to predicting the properties of high-entropy alloys.

Item Type:	Book
Additional Information:	Кирилаха Світлана. Розділ VIII. Штучний інтелект для вдосконалення механічних властивостей матеріалів. Штучний інтелект у науці : монографія / [авт. колектив]; за ред. Яцишина Андрія та Яцишин Анни. – Київ: ФОП Ямчинський О.В., 2025. – С. 105-112. ISBN 978-617-8830-09-0
Keywords:	Artificial Intelligence (AI), Machine Learning (ML), Materials Science, Alloys, Vickers Method, Hardness, Structure, Mechanical Properties, High-Entropy Alloys
Subjects:	Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 00 Prolegomena. Fundamentals of knowledge and culture. Propaedeutics > 004 Computer science and technology. Computing. Data processing > 004.9 Application-oriented computer-based techniques Science and knowledge. Organization. Computer science. Information. Documentation. Librarianship. Institutions. Publications > 6 Applied Sciences. Medicine. Technology
Divisions:	Institute for Digitalisation of Education > Generic resouse
Depositing User:	д.пед.н. Анна Яцишин
Date Deposited:	19 Jan 2026 14:34
Last Modified:	19 Jan 2026 14:34
URI:	https://lib.iitta.gov.ua/id/eprint/748239

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