Unveiling the physical mechanisms driving delafossite crystal (ABX2) formation through interpretable machine learning

Abstract

A method integrating machine learning with first-principles calculations is employed to forecast the formation energy of delafossite crystals, facilitating the rapid identification of stable crystals. This approach identifies several stable candidates and highlights the importance of atomic ionization energy and electron affinity in the formation of delafossite crystals.