Doctoral Dissertations

Date of Award

12-2016

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Mechanical Engineering

Major Professor

Matthew M. Mench

Committee Members

Thomas A. Zawodzinski, Feng-Yuan Zhang, Kivanc Ekici

Abstract

All-vanadium redox flow batteries (VRFBs) are an emerging grid-scale energy storage technology; however, enhancements in terms of performance, efficiency, durability, and cost are required before it can become commercially viable. These improvements are achievable through the development of advanced materials, superior architecture, and ultimately a deeper fundamental understanding of the influence of various phenomena and operational parameters on cell performance. There currently are a lack of in-situ experimental diagnostic techniques which can help in achieving this fundamental understanding.

Two separate distributed diagnostic techniques were developed in this work: in-plane current distribution, and neutron radiography. Localized current distribution measurements can identify regions of reduced performance, and provide valuable insight regarding mass transport as a function of materials and design, and potentially localized degradation. A novel interpretation of the dimensionless Damkohler number was adapted to locally assess the relative contributions of kinetic and mass transport losses across the active area within an operating cell. Neutron radiography is an effective technique for the identification and quantification of individual phases within a two-phase fluid. This technique was implemented to determine the onset voltage of unwanted side reactions in an operating VRFB. Identification of such unfavorable operating conditions and limitations for different electrode materials can lead to a wider safe operating voltage window, which can be implemented to reduce charging times and improve cell efficiency.

The successful demonstration of these techniques provides the field with two validated in-situ diagnostic techniques, advanced analysis, and benchmark data that can provide feedback for engineering enhanced materials, designs, and more optimal operating conditions for these cells, ultimately leading to enhanced fundamental understanding and improved performance.

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