Solubility, diffusivity and permeability of gases in glassy polymers

Gas separation membranes of high CO2 permeability and selectivity have great potential in both natural gas sweetening and carbon dioxide capture. Many modified PIM membranes results permselectivity above Robinson upper bound. The big problem that should be solved for these polymers to be commercialized is their aging through time. In high glassy polymeric membrane such as PIM-1 and its modifications, solubility selectivity has more contribution towards permselectivity than diffusivity selectivity. So in this thesis work pure and mixed gas sorption behavior of carbon dioxide and methane in three PIM-based membranes (PIM-1, TZPIM-1 and AO-PIM-1) and Polynonene membrane is rigorously studied. Sorption experiment is performed at different temperatures and molar fraction. Sorption isotherms found from the experiment shows that there is a decrease of solubility as the temperature of the experiment increases for both gases in all polymers. There is also a decrease of solubility due to the presence of the other gas in the system in the mixed gas experiments due to competitive sorption effect. Variation of solubility is more visible in methane sorption than carbon dioxide, which will make the mixed gas solubility selectivity higher than that of pure gas solubility selectivity. Modeling of the system using NELF and Dual mode sorption model estimates the experimental results correctly Sorption of gases in heat treated and untreated membranes show that the sorption isotherms don’t vary due to the application of heat treatment for both carbon dioxide and methane. But there is decrease in the diffusivity coefficient and permeability of pure gases due to heat treatment. Both diffusivity coefficient and permeability decreases with increasing of heat treatment temperature. Diffusivity coefficient calculated from transient sorption experiment and steady state permeability experiment is also compared in this thesis work. The results reveal that transient diffusivity coefficient is higher than steady state diffusivity selectivity.

Exploiting molecular simulations as an atomic-level microscope to elucidate clinically relevant cation chloride cotransporters

The cation chloride cotransporters (CCCs) represent a vital family of ion transporters, with several members implicated in significant neurological disorders. Specifically, conditions such as cerebrospinal fluid accumulation, epilepsy, Down’s syndrome, Asperger’s syndrome, and certain cancers have been attributed to various CCCs. This thesis delves into these pharmacological targets using advanced computational methodologies. I primarily employed GPU-accelerated all-atom molecular dynamics simulations, deep learning-based collective variables, enhanced sampling methods, and custom Python scripts for comprehensive simulation analyses. Our research predominantly centered on KCC1 and NKCC1 transporters. For KCC1, I examined its equilibrium dynamics in the presence/absence of an inhibitor and assessed the functional implications of different ion loading states. In contrast, our work on NKCC1 revealed its unique alternating access mechanism, termed the rocking-bundle mechanism. I identified a previously unobserved occluded state and demonstrated the transporter's potential for water permeability under specific conditions. Furthermore, I confirmed the actual water flow through its permeable states. In essence, this thesis leverages cutting-edge computational techniques to deepen our understanding of the CCCs, a family of ion transporters with profound clinical significance.