MétaCan
Menu
Back to cohort
Record W4206517027 · doi:10.1002/celc.202101617

Carbon Aerogel Based Thin Electrodes for Zero‐Gap all Vanadium Redox Flow Batteries – Quantifying the Factors Leading to Optimum Performance

2022· article· en· W4206517027 on OpenAlexaff
Andrés Parra-Puerto, Matthew Markiewicz, Zhuo Zheng, Anthony Kucernak

Bibliographic record

VenueChemElectroChem · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsBallard Power Systems (Canada)
FundersEngineering and Physical Sciences Research CouncilShell Global Solutions InternationalShell
KeywordsMaterials scienceElectrodeMicroporous materialElectrolyteAerogelPower densityCarbon fibersPorosityVanadiumSpecific surface areaChemical engineeringComposite materialMetallurgyChemistryCatalysisPower (physics)

Abstract

fetched live from OpenAlex

Abstract Direct growth of resorcinol−formaldehyde carbon aerogels (CAGs) on carbon paper electrodes was achieved using a new approach. Materials with variations in density, mesoporosity and microporosity were prepared. Microstructural properties of the resultant thin electrodes are shown to directly influence performance in zero‐gap redox flow battery (RFB). BET analysis shows a total surface area between 643 to 931 m 2 g −1 . Deposition of only ≈15 wt.% CAG on the carbon electrode leads to a 320‐fold increase in electrochemical surface area. Analysis of the results saw a strong positive correlation of RFB performance with surface area. The best performing electrodes had a good balance between microporous and external surface area, and on the macroscopic scale had sufficiently large pores to allow efficient electrolyte permeation. The poorest performing electrodes which had the highest surface area, also had poor macroscopic porosity leading to large mass transport and solution resistance losses. The best performing electrodes were tested in a zero‐gap setup using polarization curves, showing a 25 % increase in power density at 100 mA cm −2 and a peak power density of 706 mW cm −2 at 1 V using thin electrodes.

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 score0.069
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
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.040
GPT teacher head0.279
Teacher spread0.238 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueChemElectroChemSame topicAdvanced battery technologies researchFrench-language works237,207