Practical Machine Learning Techniques to Accelerate Materials Science Research | by Nicholas Lewis | Aug, 2022
Predicting the Critical Temperature of Superconductors using Regression Techniques, Feature Selection, and Selection CriteriaPhoto by American Public Power Association on UnsplashThe U.S. energy grid loses about 5% of its power due to resistive losses in its transmission lines, according to an estimate from the EIA. What if we could find a way to eliminate all of that? As it turns out, there’s a really cool class of materials called superconductors — materials that conduct electricity with 0 resistance. If there’s no…