Strategies for Tuning Hierarchical Porosity of 3D rGO to Optimize Ion Electrosorption

Abstract

Capacitive deionization (CDI) is a desalination technology under intensive research following the principle of electrical double layer capacitors for brackish water. It has some advantages over other conventional desalination technologies as it is a convenient process that operates at ambient temperatures and pressures, high water recovery, and no chemical usage. To address one of the CDI challenges regarding the electrode material; this thesis studied a laboratory-scale CDI cell to evaluate the desalination performance and efficiency of different types of 3D rGO electrodes with distinct pore structures. This thesis provides a further understanding of the impact of porous characteristics of the electrode materials on their electrosorption performance. A systematic investigation was conducted on the cause-effect relationship among various parameters, such as precursor concentrations, 3D rGO packing densities in-plane and out-of-plane porosities. Firstly, when the precursor concentration (GO) was changed from low to high concentrations to produce 3D rGO, sample rGO-4 showed a dual pore size distribution with higher numbers of mesopores as well as the less stacking of the rGO sheets. Also, it demonstrated better specific capacitance of 236 F/g. Secondly, when a dosage of 100 μl of 30% H2O2 was added to the GO solution, in-plane nanopores were created increasing the specific capacitance to 284 F/g. Lastly, when the out-of-plane hierarchal pores were created by employing sacrificing nanocrystal-template crystals α-Fe2O3, sample T-rGO displayed higher micropores volume and more active sites with a highly interconnected structure, facilitating better ion access and achieving a specific capacitance of 409 F/g. In CDI experiments, sample T-rGO demonstrated a fast and stable salt adsorption and desorption cycle and reached 100% complete desorption/regeneration within an average of 59 minutes and a high electrosorption capacity of 7.3 mg/g.

Date of Award	Mar 2019
Original language	American English
Supervisor	Linda Zou (Supervisor)