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Record W4285398693 · doi:10.1149/ma2022-01482000mtgabs

Comparison of Zinc Bromine and Zinc Iodine Flow Batteries: From Electrolde to Electrolyte

2022· article· en· W4285398693 on OpenAlexaff
A. Keith Jameson, Előd Gyenge

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFlow batteryZincElectrolyteVanadiumEnergy storageBattery (electricity)BromineSolubilityRedoxChemistryInorganic chemistryMaterials scienceElectrodeOrganic chemistryPower (physics)Physics

Abstract

fetched live from OpenAlex

Research in flow batteries and their application in large scale energy storage has received a growing amount of attention and promise over the past two decades. Although the energy density of flow batteries is low relative to the Li-ion battery, their comparatively lower costs, preferred safety, and ease of scalability has made flow batteries some of the most promising contenders for large-scale stationary energy storage, and are currently commercially available for this purpose. The zinc-bromine flow battery (ZBFB), despite being one of the first proposed flow batteries in the 1980s, has only recently gained enough traction to compete with the well established all-vanadium redox flow batteries. This is largely due to the high solubility of the bromine redox species in aqueous electrolytes, which has allowed the ZBFB is achieve double the energy density of the all-vanadium technology. Recently, an analogue to the zinc-bromine flow battery was introduced: the zinc-iodine flow battery (ZIFB). Similar to the ZBFB, the main advantages of this technology arose from the high solubility of the electroactive species in the electrolyte (iodine/tri-iodide). The solubility of the iodine redox species is even higher than that of analogous bromine electrolytes, and accordingly, the highest energy densities of all aqueous flow batteries to date has been for the ZIFB. Despite the similarities between the two technologies, they are held back by different issues, and so different approaches have been taken to improving the performances of the ZBFB and ZIFB. The ZBFB primarily suffers from a low power-density due to the sluggish kinetics of the bromine redox couple. Therefore, a majority of research on the ZBFB has focused on identifying new, low cost electrode materials that minimize kinetic losses at the bromine half-cell. In contrast, a majority of research on the ZIFB has been on improvements to the electrolyte composition. The ZIFB is plagued by issues of a thick, high impedance iodine film that forms at the positive electrode on charge. Due to the strong Lewis acid nature of the iodine species, a variety of charge-transfer complexes can be formed in the electrolyte, having a variety of effects on the battery performance. This presentation provides an overview on the similarities and differences between the ZBFB and ZIFB technologies. We performed a variety of half-cell and flow battery tests varying the electrode and electrolyte compositions. A number of low cost carbon materials are used as electrode materials, along with a variety of modifications to the bromine and iodine electrolytes. Through the use of high-surface area carbon blacks, the exchange current of the bromine redox couple is able to be increased by two orders to magnitude in comparison to glassy carbon. Additions of MSA or other acids to the ZBFB increases the oxidation kinetics greatly, and accordingly the overall energy efficiency of the ZBFB. For the ZIFB, the presence of high surface area catalysts have little to no effect on the overall performance. We found that in aqueous electrolytes, the iodine electrode is largely held back by the iodine film that forms on charge. Therefore, by adding ions to the electrolyte such as Br - , Cl - , and SO 4 2- , we were able to increase the solubility of the iodine film and the reversibility of the battery, and accordingly its efficiency. Although the ZIFB initially performs better than the ZBFB, after making systematic adjustments to both the electrode and electrolyte compositions, the discrepancy between their performances is largely minimized, demonstrating both can be viable for the future of large-scale energy storage. Figure 1

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.277
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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