Efficient Monte Carlo Simulation of Faceted Nanoparticles Using Analytical Interaction Potentials

Understanding how energetic interactions between faceted nanoparticles (NPs) drive their self-assembly into higher-order architectures is a key area of investigation, given the valuable optical, catalytic, and plasmonic properties these assemblies exhibit. Re- cently, we devised an approach to derive analytical potentials that accurately capture the orientation-dependent van der Waals interactions between faceted NPs. In this work, we incorporate these analytical potentials into a Monte Carlo simulation frame- work to enable fast yet accurate simulation of NP self-assembly. Through the imple- mentation of virtual cluster moves in this framework, we mitigate unphysical energy traps and account for size-dependent diffusion of particles and their clusters. We find that the analytical potentials allow us to simulate NP assembly orders of magnitude faster than atomistic and coarse-grained models while yielding assembly morphologies closely resembling those from atomistic simulations. In contrast, coarse-grained mod- els of the NPs fail to capture the expected morphologies. Additionally, we explore the phase behavior of faceted NPs of varying shapes under weak and strong interactions, marking one of the first attempts at studying the phase diagram of attractive faceted particles. Our analysis reveals that, compared to hard-core potentials, attractive inter- actions enhance the ordering of particles in their assemblies. Specifically, they shift the transitions between isotropic and semiordered phases to lower volume fractions, but have little effect on the transition between semiordered and crystalline phases, which are primarily driven by entropy. Overall, our results offer new insights into the role of interparticle attraction in the phase behavior of faceted NPs, and emphasize the ad- vantages of our analytical potential over traditional hard-core potentials by accounting for enthalpic interactions between NPs.