Li, Qilin2016-01-222016-01-222015-122015-10-22December 2Heldenbrand, Amy M. "Development of a Predictive and Mechanistic Model for Capacitive Deionization." (2015) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/88081">https://hdl.handle.net/1911/88081</a>.https://hdl.handle.net/1911/88081The objective of this research was to develop a mechanistic and predictive model for capacitive deionization (CDI). The commonly-known Gouy Chapman Stern (GCS) model was modified to account for finite ion size and pore geometry by including the Carnahan-Starling (CS) equation of state and considering boundary conditions resulting from difference in pore shape and size and the subsequent impact on potential and concentration profiles. This GCS-CS model with pore geometry was applied to six model activated carbons (MACs) of uniform pore size to analyze the effect of influent salt concentration, pore size and geometry, and applied voltage on ion removal. The general trends found in modeling results were consistent with data presented in the literature. These findings were then compared with the commonly used CDI models, which could not replicate them. This indicates the complexity present in this new model is necessary for accurate representation of ion adsorption in CDI.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Capacitive deionizationmodelingdouble-layer overlapdesalinationelectrosorptionion volume effectsThesis2016-01-22