Thermodynamic Stability of Multimetallic Nanoparticles

Metal nanoparticles find tremendous application in modern technology, ranging from catalysis to medicine. However, how different metals mix at the nanoscale and their exact thermodynamically preferred chemical ordering (positioning of different metal atoms on the nanoparticle lattice) is unknown. In this presentation, I will highlight recent computational advances on accurately describing the thermodynamic stability of bimetallic nanoparticles of any size, shape, metal composition and chemical ordering, by combining Density Functional Theory calculations with machine learning. The developed models can be extended to multimetallic nanoparticles, as well as used for the description of chemical adsorption on the nanoparticle surface, thus, connecting nanoparticle stability with application properties (sensing, catalysis, etc.).