Presenter 1: Lang Liu (Research Fellow, Bhatia group, SoCE)
Title: Inhibitory effect of adsorbed water on transport of methane in carbon nanotubes
Abstract: The transport diffusion of methane at 300 K and pressures up to 15 bar in dry and wetted carbon nanotubes (CNTs) having diameters ranging from 0.95 to 2.034 nm was investigated using non-equilibrium molecular dynamics (NEMD) simulation. Due to their strong hydrogen bonding, pre-adsorbed water molecules transport in the form of clusters and block the diffusion of methane, reducing the methane diffusion coefficient dramatically compared to that in dry CNTs. The reduction in the methane diffusion coefficient is greater in narrower CNTs or at higher water densities. Since the diameter of the water clusters is almost invariant with water density, the corrected diffusivity of water in the (10, 10) CNT shows negligible dependence on the water density. It is further found that while decreasing the CNT diameter from 2.03 nm to 0.95 nm enhances the diffusion coefficient of pure methane by about one order of magnitude, the diffusion coefficient of water is almost independent of the CNT diameter, at a water density of 0.05 g/cm3. We propose a theoretical model for the strong dependency of methane diffusion in wetted CNTs on the diffusion coefficient of water, the pre-adsorbed water density and the CNT diameter. The model predicts the diffusion coefficients of the methane/water mixture from the diffusion coefficients of the pure components. This study provides a basic understanding of the coupled diffusion of immiscible components in nanochannels, and will facilitate progress in nanofiltrations and biomedical and biotechnological applications.
Presenter 2: Bertrand Caron (PhD student, Mark group, SCMB)
Title: Improving the predictive ability of Empirical Force Fields using graph theory: A Big-Data approach
Abstract: Computational methods can offer unique insight at an atomic level into the structure and dynamics of biomolecules. While ideally described quantum-mechanically, in practice simpler empirical “force field” descriptions are needed to describe inter-particle interactions. The predictive ability of any force field is only as good as the underlying model; and manual parametrisation of empirical force fields is a tedious, error-prone and arbitrary process where parameters developed on a handful of compounds are transferred with little regard to the immediate bonded environment. With the advent of large chemical databases (e.g. ChEMBL, ZINC, CSD) and the need for high-throughput, the development of robust, consistent, automated approaches is critical. The talk will focus on novel strategies using molecular graphs and large molecular datasets to simultaneously and consistently develop and refine parameters transferable to a wide range of compounds, with a systematic treatment of parameter interactions. Specifically, I will present two novel tools developed as part of collaboration with the CWI (VU, Amsterdam): OFraMP, an aided charge assignment graphical interface and FDB (Fragment DataBase), a repository of common fragments found in 200,000 ChEMBL molecules (10%) parametrised with a high-level of accuracy. Together, I will present how these tools can be used to develop parameters of near-QM fidelity for very big and complex structures such as dendrimers or large drugs. Ultimately, these parameters will be integrated as part of the Automated Topology Builder (ATB) web-server developed within the laboratory. Finally, I will present an algorithm I developed for assigning Lewis structures which can be used to cap fragments or even enumerate tautomers.