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Record W3134918096

Fabrication of high surface area ribbon electrodes for use in redox flow batteries via coaxial electrospinning

2021· article· en· W3134918096 on OpenAlexaff
Shashi Yadav, Antoni Forner‐Cuenca, Kevin M. Tenny, Yet‐Ming Chiang, Fikile R. Brushett, Rhodri Jervis, PR Shearing, E. C. Roberts, JT Gostick

Bibliographic record

VenueDSpace@MIT (Massachusetts Institute of Technology) · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of CalgaryUniversity of Waterloo
Fundersnot available
KeywordsRibbonMaterials scienceElectrospinningElectrodeComposite materialPolyacrylonitrileCoaxialAnodeFabricationFiberPorosityNanotechnologyPolymerChemistryElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

A method for the preparation of electrospun with fibers possessing a ribbon-like cross-sectional shape was developed. These materials could prove beneficial as flow-through electrodes, since ribbons provide a higher surface-to-volume ratio compared to fibers, thereby providing higher reactive surface area at a given porosity. Fabrication of these materials was accomplished by electrospinning a coaxial fiber with a polystyrene core and polyacrylonitrile shell, followed by leaching of the core material leading to the collapse of the shell into a flat ribbon. The surviving shell was then carbonized to make an electrically conductive and electrochemically reactive fibrous structure. Analysis by x-ray computed tomography showed that ribbons of approximately 400 nm × 800 nm were produced, and experimental characterization revealed that they did indeed offer higher volumetric surface area than previously reported electrospun cylindrical fiber electrodes. The electrodes were characterized for various physical and transport properties and compared to commercial Freudenberg H23 carbon paper in terms of performance in a vanadium redox flow battery. The ribbon-based electrode had better performance and higher power density than commercial Freudenberg H23 electrode in the activation region, though suffered early onset of mass transfer limitations.

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)0.001
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 score0.062
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.249
Teacher spread0.234 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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