Finally, because both the Brownian dynamics and MPM optical simulations are computationally efficient, this framework is well-suited for applying numerical optimization routines to design optical soft materials. Future work could adapt gradient-based, evolutionary, or machine-learning algorithms to design nanoparticles and disordered assemblies that display targeted photonic properties. Methods Brownian dynamics simulations. We perform Brownian dynamics simulations of N spherical nanoparticles of radius a in a triply-periodic cubic box of side length L using HOOMD-Blue (v2.9.7). We choose N = 8000 for all cases where MPM calculations adopt p-truncation and N = 1000 for cases where MPM calculations employ Q-truncation. We assume particle trajectories follow overdamped equations of motion and neglect interparticle hydrodynamic interactions, so that the equation of motion for a particle i can be numerically integrated over time t as