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Record W4413128520 · doi:10.1021/acs.chas.5c00098

Chemical Hazard Assessment of Asymmetric Vanadium Flow Battery Electrolytes in Failure Mode

2025· article· en· W4413128520 on OpenAlexafffund
Kourosh Khaje, Behzad Fuladpanjeh‐Hojaghan, Jürgen Gailer, Viola Birss, Edward P.L. Roberts

Bibliographic record

VenueACS Chemical Health & Safety · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVanadiumFlow batteryFailure mode and effects analysisHazardElectrolyteBattery (electricity)Mode (computer interface)Materials scienceEnvironmental scienceReliability engineeringMetallurgyChemistryEngineeringComputer scienceThermodynamicsElectrodePhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Emerging battery technologies are transforming the landscape of energy storage. Within this domain, flow batteries are increasingly seen as critical enablers for the integration and deployment of renewable energy systems. Nevertheless, the electrolytes utilized in these systems present potential risks to both human health and environmental safety. Over the past five decades, vanadium–vanadium flow batteries have become a commercially viable solution; however, several distinct electrolyte compositions have been proposed for asymmetric vanadium flow batteries (V-X FB: X = Ce, Br, Fe, Mn, Zn, H 2, O 2 ), each driven by unique technical and commercial motivations. This study aims to evaluate their risks, prioritize further research investments, and identify gaps in current efforts to advance safer and more sustainable energy storage technologies. This research builds on our prior work, entitled Chemical Hazard Assessment of Vanadium–Vanadium Flow Battery Electrolytes in Failure Mode, [ Khaje, K. ACS Chem. Health Saf. 2025, 32, 449–460]. But shifts the focus to asymmetric vanadium flow batteries that are at a lower technology readiness level and are earlier in the commercialization pathway. Overcharging of batteries has been identified as one of the primary potential failure modes, directly leading to electrolyte degradation. This condition poses significant hazards due to the potential generation of toxic gases. Depending on the electrolyte composition, overcharging may result in the release of gases, such as Cl 2, Br 2, SO 2, H 2 S, PH 3, NO 2, CO 2, NH 3, or HCN, each carrying immediate risks to human health. This study shows that electrolytes containing bromide, chloride, and cyanide ions are particularly concerning, as they present the most severe toxicity hazards during failure modes. Future experimental work is needed to evaluate conditions under which gases are produced by these flow batteries under both normal and severe overcharging conditions and to quantify the associated hazards. This will provide critical insights for improving battery safety and guiding future research and development in energy storage technologies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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 score0.291
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.311
Teacher spread0.303 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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