Neural Network Regressor for Designing Biomedical Low Elastic Modulus Ti-Zr-Nb-Mo Medium Entropy Alloys

Nour Mahmoud Eldabah; Amin Shoukry; Wael Khair-Eldeen; Sengo Kobayashi; Mohamed Abdel Hady Gepreel

doi:10.4028/p-nbmZ4t

Paper Titles

Optical-Emission Properties of GaN-Based Nanopillar Light-Emitting Diodes Prepared on Non-Polished and Non-Single-Crystalline Substrates
p.57

Effect of High Temperature and Humidity on Bond Strength of Al/Resin Adhesive Joints
p.63

Carbon Dots Release from Biodegradable Coatings Deposited by Aerosol-Assisted Open-Air Plasma
p.71

Plasma Immersion Ion Implantation of a Fe-Mn-C Based Steel for Biomedical Applications: Effect of Gases and Treatment Times on the Surface Properties
p.79

Neural Network Regressor for Designing Biomedical Low Elastic Modulus Ti-Zr-Nb-Mo Medium Entropy Alloys
p.89

Development and Characterisation of New Hydrogels for Medical Science Education
p.95

Effects of C Doping on the Structure and Functional Characteristics of Fe-Mn Alloys after Equal Channel Angular Pressing
p.101

Effect of Rotary Swaging on Mechanical and Corrosion Properties of Zn-1%Mg and Zn-1%Mg-0.1%Ca Alloys
p.107

Improvement of Work-Hardening Behavior of Co-Cr-W-Ni Alloy by Adding Mn/Fe for Balloon-Expandable Stents
p.115

HomeKey Engineering MaterialsKey Engineering Materials Vol. 967Neural Network Regressor for Designing Biomedical...

Neural Network Regressor for Designing Biomedical Low Elastic Modulus Ti-Zr-Nb-Mo Medium Entropy Alloys

Abstract:

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.

You might also be interested in these eBooks

International Conference on Processing and Manufacturing of Advanced Materials Processing, Fabrication, Properties, Applications - THERMEC 2023

View Preview

View Preview

Info:

Periodical:

Key Engineering Materials (Volume 967)

Pages:

89-94

DOI:

https://doi.org/10.4028/p-nbmZ4t

Citation:

Cite this paper

Online since:

December 2023

Authors:

Nour Mahmoud Eldabah*, Amin Shoukry, Wael Khair-Eldeen, Sengo Kobayashi, Mohamed Abdel Hady Gepreel

Keywords:

Artificial Neural Network, CALPHAD, Low Elastic Modulus, Medium Entropy Alloys, β-Titanium Alloys

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] M. Saini, Y. Singh, P. Arora, V. Arora, K. Jain, World Journal of Clinical Cases: WJCC 3 (2015) 52.

Google Scholar

[2] M. Long, H. Rack, Biomaterials 19 (1998) 1621-1639.

Google Scholar

[3] K. Miura, N. Yamada, S. Hanada, T.-K. Jung, E. Itoi, Acta biomaterialia 7 (2011) 2320-2326.

Google Scholar

[4] J.D.C. Tardelli, C. Bolfarini, A.C. Dos Reis, Journal of Trace Elements in Medicine and Biology 62 (2020) 126618.

DOI: 10.1016/j.jtemb.2020.126618

Google Scholar

[5] S.S. Sidhu, H. Singh, M.A.-H. Gepreel, Materials Science and Engineering: C 121 (2021) 111661.

Google Scholar

[6] M. Niinomi, Materials Science and Engineering: A 243 (1998) 231-236.

Google Scholar

[7] K.S. Tun, M. Gupta, T. Srivatsan, Processing challenges and properties of lightweight high entropy alloys, High Entropy Alloys, CRC Press, 2020, pp.95-124.

DOI: 10.1201/9780367374426-4

Google Scholar

[8] J.W. Yeh, Y.L. Chen, S.J. Lin, S.K. Chen, High-entropy alloys–a new era of exploitation, Materials science forum, vol 560, Trans Tech Publ, 2007, pp.1-9.

DOI: 10.4028/www.scientific.net/msf.560.1

Google Scholar

[9] K.-K. Wong, H.-C. Hsu, S.-C. Wu, W.-F. Ho, Journal of Alloys and Compounds 868 (2021) 159137.

Google Scholar

[10] S. Hu, T. Li, Z. Su, D. Liu, Intermetallics 140 (2022) 107401.

Google Scholar

[11] M. Abdel-Hady, K. Hinoshita, H. Fuwa, Y. Murata, M. Morinaga, Materials Science and Engineering: A 480 (2008) 167-174.

DOI: 10.1016/j.msea.2007.06.083

Google Scholar

[12] L. Zhuang, E. Langer, Journal of materials science 24 (1989) 381-388.

Google Scholar

[13] M. Abdel-Hady, H. Fuwa, K. Hinoshita, H. Kimura, Y. Shinzato, M. Morinaga, Scripta Materialia 57 (2007) 1000-1003.

DOI: 10.1016/j.scriptamat.2007.08.003

Google Scholar

[14] P. Ji, B. Chen, B. Li, Y. Tang, G. Zhang, X. Zhang, M. Ma, R. Liu, Journal of Materials Science & Technology 69 (2021) 7-14.

Google Scholar

[15] M. Niinomi, M. Nakai, International journal of biomaterials 2011 (2011).

Google Scholar