Neural Network Regressor for Designing Biomedical Low Elastic Modulus Ti-Zr-Nb-Mo Medium Entropy Alloys
The excellent biocompatibility of Ti and Zr alloys makes them the best candidates for orthopedic implantations. The design of high Ti and Zr-containing alloys that show low Young's modulus for implant manufacturing is the objective of this work. Here, a feed-forward-back propagation neural netw...
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Veröffentlicht in: | Key engineering materials 2023-12, Vol.967, p.89-94 |
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Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The excellent biocompatibility of Ti and Zr alloys makes them the best candidates for orthopedic implantations. The design of high Ti and Zr-containing alloys that show low Young's modulus for implant manufacturing is the objective of this work. Here, a feed-forward-back propagation neural network was used to speed up the design process and optimize alloy composition. The β-typeTi45-Zr39-Nb12-Mo4 alloy is designed and showed promising properties. The alloy showed a low elastic modulus of 78 GPa and a high yield strength of 891 MPa resulting in a high elastic admissible strain that made it suitable for orthopedic applications. |
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ISSN: | 1013-9826 1662-9795 1662-9795 |
DOI: | 10.4028/p-nbmZ4t |