Porous Self-Assembly in Binary Mixtures of Lobed Colloidal Particles

The self-assembly of colloidal particles is emerging as a promising approach for designing novel advanced materials. During self-assembly, particles spontaneously reorganize to form macrostructures with desired properties for applications in diverse fields, including in tissue engineering, catalysis, and photonics. The addition of attractive hard lobes to the surfaces of the colloidal particles can provide directionality for the interparticle interactions and create more excluded volume around each particle, leading to the formation of porous morphologies. In this work, we performed Langevin Molecular Dynamics simulations of binary mixtures of lobed colloidal particles, where the self-assembly process is mediated by short-range interactions between the lobes of the particles. We investigated the formation of porous macrostructures in mixtures of particles with varying number/size of their lobes across a range of temperatures. Among the self-assembled morphologies, we primarily identified the formation of three-dimensional aggregates, spherical aggregates, and crystalline structures. We observed that the formation of crystalline structures is progressively preferred as the number of lobes in the particles increases, and that the crystalline character of these structures leads to more homogeneous pore sizes, in contrast to random and spherical aggregates that have more heterogeneous pore sizes. We also observed that the larger lobes allowed the self-assembly of the lobed particles at higher temperatures when compared to the smaller lobes. The evolving understanding of how to optimize the bottom-up design of lobed colloidal particles gained by leveraging simulation techniques can serve as a guide for further improving the manufacturing of advanced materials.