Benha University

Nour Mahmoud Massoud

Lecturer

Faculty of Engineering, Benha Mechanical Engineering

Design and characterization of low Young’s modulus Ti-Zr-Nb-based medium entropy alloys assisted by extreme learning machine for biomedical applications

Journal of Alloys and Compounds • 2023
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Publication Information
Authors Nour Mahmoud Eldabah, Amin Shoukry, Wael Khair-Eldeen, Sengo Kobayashi, Mohamed Abdel-Hady Gepreel
Keywords Medium entropy alloys, Ti-Zr-Nb alloy, Biomedical implantations, CALPHAD, Extreme learning machine, Low Young’s modulus
Journal Journal of Alloys and Compounds
Publisher Elsevier
Volume 968
Issue Not Available
Pages 171755
publication.type International
Paper Link Open Link
Supplementary Materials Not Available
Abstract
Medium entropy alloys are considered midway between traditional and high entropy alloys. Consequently, typical design techniques are challenging for developing such alloys. In this study, the extreme learning machine approach was effectively used for the compositional design of Ti-Zr-Nb-Mo medium entropy alloys to obtain low Young’s modulus with moderate strength for biomedical applications. The newly developed alloys exhibited low Young’s modulus as low as 69.5 GPa, with a yield strength of more than 600 MPa. The difference between experimental and simulated results was slight, indicating that neural networks can be used to design medium entropy alloys. Furthermore, the introduced alloys displayed adequate bio characteristics such as decreased magnetic susceptibility and over 98% cell viability. These novel Ti-Zr-Nb-M medium entropy alloys are promising candidates for biomedical implantation because of their superior biomedical properties
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