Machine Learning Prediction of Young's Modulus in Multi-Component Titanium-Based Biomedical Alloys

This repository contains the dataset and Code for predicting the Young's modulus of multi-component titanium (Ti) alloys. By integrating physicochemical properties with high-entropy-inspired thermodynamic descriptors, this project provides a machine learning approach to accelerate the discovery of low-modulus alloys for biomedical applications.