(482h) Designing Anion Exchange Membranes with Improved Ion Conductivity By Mesoscale Simulations | AIChE

(482h) Designing Anion Exchange Membranes with Improved Ion Conductivity By Mesoscale Simulations

Authors 

Lee, M. T. - Presenter, National Taipei University of Technology
Understanding morphology of anion exchange membranes (AEM) and their transport properties is the key for future development of AEM fuel cells. The present work devises standard protocols for predicting the microstructure of AEM and diffusivity of hydroxide ions based on dissipative particle dynamics (DPD) simulations.1 The protocols aim to improve the accuracy of DPD in modeling ion conductivity in AEM by adapting recently developed DPD approaches. AEM molecules are dissected into coarse grained beads with non-uniform interaction diameters based on the Connolly volume of repeating units and functional groups. Mismatch parameters are determined by activity coefficients of bead components and the calibration curves constructed by particle insertion method. Hydroxide ions which interact with water and cationic groups are modelled explicitly by the corresponding association potentials, similar to the DPD proton model in polyelectrolyte membranes.2 The methodology is applied to study aromatic polymer PPO-TMA (polyphenylene oxide trimethylamine) and QAPS (quaternary ammonium polysulfone) with different side chain modifications, in order to avoid over-assembling of polymer backbones and to promote hydroxide transport. The method preserves the efficiency and simplicity of conventional DPD methods with improved descriptions for chemical specifics, and is expected to provide insights into the principles of new membranes design.

References:

[1] Lee, M.-T., Exploring Side Chain Designs for Enhanced Ion Conductivity of Anion Exchange Membranes by Mesoscale Simulations. The Journal of Physical Chemistry C 2019, just accepted.

[2] Lee, M. T.; Vishnyakov, A.; Neimark, A. V., Modeling Proton Dissociation and Transfer Using Dissipative Particle Dynamics Simulation. Journal of Chemical Theory and Computation 2015, 11, 4395-4403.