Materials Informatics Driven Designing Mg Alloys for Biodegradable Short-Term Implants Using Machine Learning

Due to their non-toxic nature, high strength-to-weight ratio, and low density, which is nearly identical to human cortical bone, and notable biocompatibility and biodegradability, magnesium alloys have attracted the attention of researchers in the field of new age biomaterials during the past 2 decades. The Mg alloys are the ideal option for modern biodegradable biomaterial because they will degrade inside the human body and lower medical expenses of the second surgery to remove the short-term implant. It is important to have an in-depth understanding of the role of the alloying elements for designing Mg alloys with improved properties, i.e., higher strength with required/higher corrosion resistance, for better implant performance. Here, a materials informatics approach using four distinct machine learning techniques has been implemented to analyze Mg alloy databases to understand the role of the alloying elements in achieving the above features. The analyses show that Mn, Y and some other rare earth elements are suitable to improving the strength and corrosion properties of Mg alloys with enhanced performance as the material for short-term implants.