Machine learning recommends affordable new Ti alloy with bone-like modulus

Publisher:
Elsevier
Publication Type:
Journal Article
Citation:
Materials Today, 2020, 34, pp. 34-41
Issue Date:
2020
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© 2019 Elsevier Ltd A neural-network machine called “βLow” enables a high-throughput recommendation for new β titanium alloys with Young's moduli lower than 50 GPa. The machine was trained by using a very general approach with small data from experiments. Its efficiency and accuracy break the barrier for alloy discovery. βLow's best recommendation, Ti-12Nb-12Zr-12Sn (in wt.%) alloy, was unexpected in previous methods. This new alloy meets the requirements for bio-compatibility, low modulus, and low cost, and holds promise for orthopedic and prosthetic implants. Moreover, βLow's prediction guides us to realize that the unexplored space of the chemical compositions of low-modulus biomedical titanium alloys is still large. Machine-learning-aided materials design accelerates the progress of materials development and reduces research costs in this work.
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