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

A neural-network machine called "beta Low" enables a high-throughput recommendation for new 13 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. beta Low'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, beta Low'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.