Comparative Computational Models for Diffusion and Reconfiguration in DNA-Based Meso-structures

We present a comparative computational analysis of transport and reconfiguration in programmable DNA-based meso-structures, emphasizing how distinct modeling frameworks capture different physical mechanisms. For multilayer core–shell DNA superlattices, finite element (FEM) simulations quantify mesoscale diffusion through anisotropic confinement, revealing shell-thickness–dependent kinetic barriers that decouple release rate from crystal size. Complementary coarse-grained Brownian dynamics simulations in HOOMD-Blue resolve nanoparticle trajectories and local mean-square displacements, linking microscopic random walks to effective diffusion coefficients. To probe structural reconfiguration, we apply a Monte Carlo framework for patchy hard tetrahedra with tunable color-encoded interactions and rotational degrees of freedom, capturing directional self-assembly and angular constraints. By juxtaposing continuum, particle-based, and discrete assembly models, this work highlights the nuanced strengths and limitations of each approach in describing programmable mesoscale architectures and guiding the design of reconfigurable soft-matter systems.