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We present a general approach to isolate chemical reaction mechanism as an independently controllable variable across chemically distinct systems. Modern approaches to reduce the computational expense of molecular dynamics simulations often group multiple atoms into a single “coarse-grained” interaction site, which leads to a loss of chemical resolution. In this work we convert this shortcoming into a feature and use identical coarse-grained models to represent molecules that share nonreactive characteristics but react by different mechanisms. As a proof of concept, we use this approach to simulate and investigate distinct, yet similar, trifunctional isocyanurate resin formulations that polymerize by either chain- or step-growth. Because the underlying molecular mechanics of these models are identical, all emergent differences are a function of the reaction mechanism only. We find that the microscopic morphologies resemble related all-atom simulations and that simulated mechanical testing reasonably agrees with experiment.

A reactive molecular dynamics approach is used to simulate cross-linking of acrylate polymer networks. By employing the same force field and reactive scheme and studying three representative multifunctional acrylate monomers, we isolate the importance of the nonreactive moieties within these model monomers. Analyses of reactive trajectories benchmark the estimated gel points, cyclomatic character, and spatially resolved cross-linking tendencies of the acrylates as a function of conversion. These insights into the similarities and differences of the polymerization and resulting networks suggest molecular mechanics as a useful tool in the rational design of photopolymerization resins.

We develop and evaluate a semi-empirical particle-based model of electrophoresis using extensive mesoscale simulations. We parameterize the model using only measurable quantities from a broad set of colloidal suspensions with properties that span the experimentally relevant regime. With sufficient sampling, simulated diffusivities and electrophoretic velocities match predictions of the ubiquitous Stokes-Einstein and Henry equations, respectively. This agreement holds for non-polar and aqueous solvents or ionic liquid colloidal suspensions under a wide range of applied electric fields.

The aim of this paper is to introduce an approach for optimally organizing a variety of nonrepeating compliant-mechanism-like unit cells within a large deformable lattice such that the bulk behavior of the lattice exhibits a desired graded change in thermal expansion while achieving a desired uniform stiffness over its geometry. Such lattices with nonrepeating unit cells, called nonperiodic microarchitectured materials, could be sandwiched between two materials with different thermal expansion coefficients to accommodate their different expansions and/or contractions induced by changing ambient temperatures. This capability would reduce system-level failures within robots, mechanisms, electronic modules, or other layered coatings or structures made of different materials with mismatched thermal expansion coefficients. The closed-form analytical equations are provided, which are necessary to rapidly calculate the bulk thermal expansion coefficient and Young's modulus of general multimaterial lattices that consist first of repeating unit cells of the same design (i.e., periodic microarchitectured materials). Then, these equations are utilized in an iterative way to generate different rows of repeating unit cells of the same design that are layered together to achieve nonperiodic microarchitectured material lattices such that their top and bottom rows achieve the same desired thermal expansion coefficients as the two materials between which the lattice is sandwiched. A matlab tool is used to generate images of the undeformed and deformed lattices to verify their behavior and an example is provided as a case study. The theory provided is also verified and validated using finite-element analysis (FEA) and experimentation.

We develop and evaluate a semi-empirical particle-based model of electrophoresis using extensive mesoscale simulations. We parameterize the model using onlymeasurable quantities from a broad set of colloidal suspensions with properties that span the experimentally relevant regime. With sufficient sampling, simulated diffusivities and electrophoretic velocities match predictions of the ubiquitous Stokes-Einstein and Henry equations, respectively. This agreement holds for non-polar and aqueous solvents or ionic liquid colloidal suspensions under a wide range of applied electric fields.