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Record W3045657912 · doi:10.1115/1.4046869

Design, Development, and Testing of a Low-Concentration Vanadium Redox Flow Battery

2020· article· en· W3045657912 on OpenAlexafffund
Kyle Lourenssen, J. L. Williams, Faraz Ahmadpour, Ryan Clemmer, S. Andrew Gadsden, Syeda Humaira Tasnim

Bibliographic record

VenueJournal of Electrochemical Energy Conversion and Storage · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Guelph
KeywordsFlow batteryVanadiumElectrolyteMultiphysicsBattery (electricity)Faraday efficiencyElectrolysisMaterials scienceRedoxNuclear engineeringPolarization (electrochemistry)ChemistryPower (physics)ElectrodeThermodynamicsEngineeringMetallurgyPhysics

Abstract

fetched live from OpenAlex

Abstract The purpose of this paper is to highlight the design, development, and testing of a low-concentration vanadium redox flow battery (VRFB). The low-cost implementation has a 7 cm × 7 cm active membrane area and an electrolyte volume of 450 mL for each positive and negative electrolyte. The electrolyte concentration is approximately 0.066 M vanadium. An H-cell for performing electrolysis with the electrolytes is developed, and the process and method for creating the electrolyte for this low-concentration implementation are described and documented. The maximum power density and energy efficiency of the battery among tests between 500 and 800 mA are 1.32 W/L and 28.51%, respectively. Results are presented in terms of polarization curves, charge/discharge cycles, and voltage, coulombic, and energy efficiencies. Adaptation of a COMSOL Multiphysics model is implemented to compare the computational performance figures and the results of our VRFB implementation. The numerical results agree with experimentation, and differences in the results can be attributed to the losses present in the experimental tests. The proposed battery and design are intended to investigate the performance and feasibility of a low-concentration VRFB. The ultimate long-term objective of this research is the development of a novel, cost-effective, and safe redox flow battery using hydrogen peroxide as one of the electrolytes.

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 categoriesnone
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 score0.347
Threshold uncertainty score0.355

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 integrity0.0000.000
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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2020
Admission routes2
Has abstractyes

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