Discovery and prediction of multiphase nanoparticle interface morphologies using a Monte Carlo Potts approach

Multicomponent nanoparticles are currently being synthesized and explored in massive high-throughput combinatorial libraries. The design of materials with targeted properties is complicated by the astronomical number of possible compositions, phases, and morphologies.

Here, we demonstrate a computational approach to predict the internal nanoscale morphology of the phases formed in multiphase nanoparticles. The approach is based on a description of the total energy of the nanoparticle, written in terms of the surface and interfacial energies between all combinations of phases within the particle. This nanoparticle energy is mapped onto a Potts model, with interactions in the model accounting for surface and interfacial energies. Monte Carlo simulations are then used to optimize the energetics of the nanoparticle, resulting in a prediction of the internal nanoparticle morphology.

We use this approach to calculate an interface morphology diagram for bi- and triphase nanoparticles. We subsequently present the calculated interface morphology boundaries between biphase nanoparticles as well as some previously unreported triphase nanoparticle interface morphologies. Additionally, we show how this approach can be used in combination with DFT-calculated surface and interfacial energies to predict nanoparticle morphologies of several binary and ternary metal systems, with results that are in qualitative agreement with experimental observations.