Computational Design of Patchy Particles with Complex Surface Patterning

Synthesizing reconfigurable nanoscale synthons with predictive control over shape, size, and interparticle interactions is a holy grail for designing stimuli-responsive self-assembled materials. However, grand challenges in their rational design lie in the large space of potential experimental parameters and complex synthetic protocols. Here, we define a strategy for designing complex, reconfigurable building blocks that addresses the above limitations. Specifically, we engineer triblock, star-like polymers and leverage their microphase separation to control surface patterning on nanoparticles. Our theory characterizes the structural organization of grafted polymers as a function of parameters such as grafting density, chain length, block fractions, and core shape/sizes. Stripe-like patterning and corner/edge patch formation on arbitrarily shaped cores are readily accessible using our framework, all of which can be a priori predicted. We then employ assembly simulations to show that the resulting particles provide tighter control over structural and orientational orderings during self-assembly by overriding face-face alignments tendencies intrinsic to each core geometry. Our theories provide unique insights into nanoscale synthesis, allowing for a priori design of complex building blocks that can target novel assemblies for novel materials fabrication.