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Rice University

Development of a Predictive and Mechanistic Model for Capacitive Deionization

Abstract

dc:description.abstract

The 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.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
Masters
Discipline thesis:degree_discipline
Engineering
Grantor
Rice University
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Heldenbrand, Amy M
Advisor dc:contributor.advisor
  • Li, Qilin
Committee members dc:contributor.committeemember
  • Alvarez, Pedro J.J.
  • Tomson, Mason B

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • Copyright 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1911/88081
OAI identifier oai:identifier
oai:repository.rice.edu:1911/88081

Chain of custody

source
Harvested from
Rice University
Base URL
repository.rice.edu/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Heldenbrand, Amy M. Development of a Predictive and Mechanistic Model for Capacitive Deionization. Masters thesis, Rice University, 2015. https://hdl.handle.net/1911/88081