Integrating molecular modeling tools with a chemical process simulation package will provide a complete, rigorous, and accurate framework for predicting and correlating physical properties. We have recently demonstrated the accuracy and efficiency that can be achieved when molecular modeling is based on combining Discontinuous Molecular Dynamics (DMD) with second order Thermodynamic Perturbation Theory (TPT). The DMD algorithm can simulate the reference fluid more efficiently than any other MD method. Because the attractive forces show up as perturbations that can be accurately treated by the theory, optimization of the attractive part of the potential proceeds extremely efficiently. The attractive part of the potential is characterized in terms of a sequence of steps with variable depth. Noting that equilibrium and transport properties can be computed from MD, we refer to our molecular model as the Step Potential Equilibria And Dynamics (SPEAD) Model.

    By developing a convenient interface for entering the molecular structure graphically and managing the simulations simply, molecular simulation methodology is made accessible to the entire chemical, physical, and engineering community. Engineers and scientists can now conceive of a new component one day and be simulating chemical processes containing that component by the end of the week. This kind of tool will play a central role as chemical engineering evolves from process design to product design.

    Highly efficient molecular modeling opens the door to a broad range of engineering opportunities at the nano scale. The key problem is to draw connections between the atomistic scale familiar to chemists and the finite element (FE) scale familiar to engineers. These so-called “mesoscale” dynamics require models that accurately track coarse grained models of individual molecules while accurately representing the macroscopic properties that are required at the FE. SPEAD alone serves this purpose for homogeneous fluids, but elaborate mesoscale models are required for inhomogeneous materials. Sample inhomogeneous applications include: adhesion, adsorption, self-assembly, Langmuir-Blodgett films, protein docking, and protein folding.