Enhancing machine-learning interatomic potentials for advanced materials modeling

Summary

Machine learning is significantly impacting computational materials science by enabling accurate and cost-effective calculations of interatomic potentials, which are essential for simulating material properties, according to Phys.org. However, the article notes that machine learning is not a complete solution, as many challenges still persist in the field.