Correlated Ion Transport
We tackle ionic transport and mechanisms in polymeric membranes from two opposite angles depending on the application:
1. maximize Li conductivity and transference number in polymer-based electrolytes to enable high power rechargeable battery applications [notable published work: https://doi.org/10.1021/acs.chemmater.8b01955].
2. minimize mass transport of the ions dissolved in the conducting hydrogel used in stretchable electronics to improve its long-term viability as bio-compatible implants [notable published work: https://doi.org/10.1021/acs.nanolett.9b03705].
Ionic liquids (ILs) have recently experienced a surge of interest justified by their vast applicability as, for instance, catalysts, tailored solvents, and electrolytes in solar cells and batteries. However, the complex ionic nature of such systems leads to unexpected ionic correlation effects that fundamentally alter the transport properties.
We highlighted the importance of rigorous multi-species concentrated solution theory, and found high degrees of ionic clustering that leads to negative alkali-cation transference number. We then used the novel insights to design improved electrolytes.
Notable published works:
We are interested in studying the connection between geometric frustration, disorder, strong ionic correlation and ionic conductivity, motivated by the observation that many of the best ionic conductors exhibit these features. We study symmetry and sublattice melting in inorganic crystals and construct models of ionic diffusion in ceramic glass materials, These investigations are powered by fast force field models and group-theoretic analysis.
Correlated diffusion calculations
We developed a new general method for analyzing and calculating diffusivity and ionic conductivity in media with strong ionic correlations from molecular trajectories. The approach automatically extracts and utilizes the collective diffusion eigenmodes of the displacement correlation matrix to denoise the calculation of the transport properties. The proposed approach is universally applicable, simple, and provably superior to previously available methods, exhibiting speed ups of several orders of magnitude.