Abstract by Megan Searles
Physics and Astronomy
Ternary Systems and Machine Learning!
One of the most exciting advances in materials science in the past decade or so has been experimentation with machine learning models. These make calculations that were formerly slow and computationally expensive much more efficient. Using data obtained through VASP and converted to the newly developed multi-body tensor representation, we attempt to use kernel ridge regression and deep neural networks to predict the energies of ternary systems.