470710 Interfacial Properties of Model Systems Using Molecular Dynamics Based Framework

Friday, November 18, 2016: 9:00 AM
Yosemite A (Hilton San Francisco Union Square)
Karnesh Jain, Andrew J. Schultz and Jeffrey R. Errington, Chemical and Biological Engineering, University at Buffalo, The State University of New York, Buffalo, NY

The behavior of fluids at solid surfaces plays a significant role within numerous natural phenomena and industrial applications. To this end, understanding and predicting the interfacial properties of these systems is crucial for the development of emerging technologies. Within our group, we have developed an interface potential based approach for determining interfacial properties. In previous work, we performed simulations within a grand canonical ensemble and calculated the interface potential using transition matrix Monte Carlo methods. However, there are limitations to working within this ensemble, particularly when applying the technique to complex molecules and working at relatively low temperatures. Recently, we developed a means for calculating the interface potential using an Isothermal Isobaric ensemble (NPT). In this presentation, we discuss how to implement this approach within a molecular dynamics based framework. The general approach is employed within a “spreading” and “drying” framework to calculate wetting properties, such as the spreading/drying coefficient, interfacial tension and contact angle. We used umbrella sampling to sample states along the order parameter path (defined by volume). We show ways of processing the acquired data using pyMBAR software and a force integration technique to construct an interface potential. Molecular dynamics simulations have been performed using the GROMACS and LAMMPS packages. Results are presented for a model system consisting of fluid-fluid interactions described by Lennard-Jones potential on a structureless 9-3 surface (GROMACS) and an atomistically detailed substrate (LAMMPS). The results obtained using molecular dynamics are compared with those obtained from NPT Monte Carlo simulation.

Extended Abstract: File Not Uploaded