Accurate and efficient methods for modeling colloidal mixtures in an explicit solvent using molecular dynamics

Most simulations of colloidal suspensions treat the solvent implicitly or as a continuum. However as particle size decreases to the nanometer scale, this approximation fails and one needs to treat the solvent explicitly. Due to the large number of smaller solvent particles, such simulations are computationally challenging. Additionally, as the ratio of nanoparticle size to solvent size increases, commonly-used molecular dynamics algorithms for neighbor finding and parallel communication become inefficient. Here we present modified algorithms that enable fast single processor performance and reasonable parallel scalability for mixtures with a wide range of particle size ratios. The methods developed are applicable for any system with widely varying force distance cutoffs, independent of particle sizes and independent of the interaction potential. As a demonstration of the new algorithm's effectiveness, we present results for the pair correlation function and diffusion constant for mixtures where colloidal particles interact via integrated potentials. In these systems, with nanoparticles 20 times larger than the surrounding solvent particles, our parallel molecular dynamics code runs more than 100 times faster using the new algorithms.