Multiscale molecular simulations of the formation and structure of polyamide membranes created by interfacial polymerization

Large scale molecular simu lations to model the formation of polyamide membranes have been carried out using a procedure that mimics experimental interfacial polymerization of trimesoyl chloride (TMC) and metaphenylene diamine (MPD) monomers. A coarse - grained representation of the m onomers has been developed to facilitate these simulations, which captures essential features of the stereochemistry of the monomers and of amide bonding between them. Atomic models of the membranes are recreated from the final coarse - grained representatio ns. Consistent with earlier treatments, membranes are formed through the growth and aggregation of oligomer clusters. The membranes are inhomogeneous, displaying opposing gradients of trapped carboxyl and amine side groups, local density variations, and r egions where the density of amide bonding is reduced as a result of the aggregation process. We observe the interfacial polymerization reaction is self - limiting and the simulated membranes display a thickness of 5 – 10 nm. They also display a surface roughn ess of 1 – 4 nm. Comparisons are made with recently published experimental results on the structure and chemistry of these membranes and some interesting similarities and differences are found

Statistical inference of the mechanisms driving collective cell movement

Numerous biological processes, many impacting on human health, rely on collective cell movement. We develop nine candidate models, based on advection-diffusion partial differential equations, to describe various alternative mechanisms that may drive cell movement. The parameters of these models were inferred from one-dimensional projections of laboratory observations of Dictyostelium discoideum cells by sampling from the posterior distribution using the delayed rejection adaptive Metropolis algorithm (DRAM). The best model was selected using the Widely Applicable Information Criterion (WAIC). We conclude that cell movement in our study system was driven both by a self-generated gradient in an attractant that the cells could deplete locally, and by chemical interactions between the cells