Theoretical analyses on water cluster structures in polymer electrolyte membrane by using dissipative particle dynamics simulations with fragment molecular orbital based effective parameters

Abstract

The mesoscopic structures of polymer electrolyte membrane (PEM) affect the performances of fuel cells.

Dissipative Particle Dynamics Simulation: A Review on Investigating Mesoscale Properties of Polymer Systems

“…[ 68 ] Similar studies of Nafion have since been reported. [ 69–72 ] These studies have revealed that water particles and hydrophilic Nafion side chains spontaneously form aggregates embedded in the hydrophobic phase of the Nafion backbone. However, the sizes of the water clusters obtained are diverse.…”

“…[ 80 ] In these membranes, proton transport is affected by various factors. [ 69,81–85 ] In one of these studies, a series of DPD‐based investigations of sulfonated polyetheretherketone (SPEEK) were performed; the results obtained for the membrane were compared with those of Nafion. [ 69 ] The results showed that the proton transport performance of the SPEEK membrane depends strongly on the degree of sulfonation and the degree of aggregation of water clusters is lower than that of water clusters in Nafion.…”

“…[ 69,81–85 ] In one of these studies, a series of DPD‐based investigations of sulfonated polyetheretherketone (SPEEK) were performed; the results obtained for the membrane were compared with those of Nafion. [ 69 ] The results showed that the proton transport performance of the SPEEK membrane depends strongly on the degree of sulfonation and the degree of aggregation of water clusters is lower than that of water clusters in Nafion. Sulfonated polysulfone ionomers, [ 83 ] sulfonated polyimides, [ 84,85 ] and sulfonated poly(phenylenes) [ 86 ] have been studied as well.…”

Multithreaded parallelization of the energy and analytic gradient in the fragment molecular orbital method

“…The accuracy can be systematically improved by increasing the order of the many‐body expansion . FMO has been used to analyze protein‐ligand binding, model chemical reactions in enzymes, optimize protein structures, build coarse grained models for molecular dynamics (MD), obtain density of states (DOS) of materials and study electron excitations …”

“…[29] The accuracy can be systematically improved by increasing the order of the many-body expansion. [30] FMO has been used to analyze protein-ligand binding, [31][32][33][34] model chemical reactions in enzymes, [35] optimize protein structures, [36] build coarse grained models for molecular dynamics (MD), [37] obtain density of states (DOS) of materials [38] and study electron excitations. [39] FMO method has been parallelized with high efficiency, [40,41] in GAMESS, [42,43] using generalized distributed data interface (GDDI), [44,45] and in other programs: ABINIT-MP, [46] OpenFMO, [47] and PAICS, [48] ABINIT-MP has been efficiently parallelized on the Earth Simulator [49] and K [34] supercomputers.…”