https://www.profitableratecpm.com/f4ffsdxe?key=39b1ebce72f3758345b2155c98e6709c
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations of interatomic potentials, that are mathematical functions that express the energy of a system of atoms and are an ingredient to simulate and predict the stability and properties of materials. But machine learning by itself is not a magic wand, and many problems remain.
