ABSTRACT
There has been substantial interest in applying induced polarization phenomena, which broadly include electrode and membrane polarization, to characterize organic contamination and biogeochemical environments. The presence of dispersed electronically conductive grains contributes to the electrode polarization, which arises due to the capacitive charging of the Stern Layer at the conductor-electrolyte interface. On the other hand, the membrane polarization is driven by spatial inhomogeneity in the ionic transferences, i.e., the proportion of current carried by the cation vs. the anion. Several phenomenological models, semi-quantitative models, and models for particular pore shapes have been proposed for understanding induced polarization. Here, we developed theoretical frameworks to quantitatively explain electrode and membrane polarization based on insights from experiments on model systems. We obtained quantitative agreement between experiment and theory, not just for characteristic frequencies and amplitudes, but for the entire spectral shape of the phase angle between electric field and current density. The amplitude, scaling of the characteristic frequency with feature size, and the spectral shape of the phase angle associated with electrode polarization differ markedly from those associated with membrane polarization.
BIOGRAPHY
Qiuzi obtained her BS in physics from Zhejiang University (China) in 2008 and a Ph.D. in Theoretical Condensed Matter Physics from the University of Maryland – College Park in 2013. Her graduate research covered four distinct research areas: transport in disordered mesoscopic systems with a primary focus on graphene, quantum computation, three-dimensional topological insulators, and cold dipolar molecules. Qiuzi joined ExxonMobil Research and Engineering – Corporate Strategic Research in 2013. She has worked on a wide range of topics covering geoscience and material science, in collaboration with experts in different areas, including theoretical physicists, experimental physicists, computational scientist and material scientists.
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