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Record W3120443905 · doi:10.1002/adma.202003855

3D‐Printable Fluoropolymer Gas Diffusion Layers for CO<sub>2</sub> Electroreduction

2021· article· en· W3120443905 on OpenAlexafffund
Joshua Wicks, Melinda L. Jue, V. A. Beck, James S. Oakdale, Nikola A. Dudukovic, Auston L. Clemens, Siwei Liang, Megan E. Ellis, Geonhui Lee, Sarah E. Baker, Eric B. Duoss, Edward H. Sargent

Bibliographic record

VenueAdvanced Materials · 2021
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Department of Energy
KeywordsFluoropolymerMaterials scienceElectrolyteChemical engineeringGaseous diffusionElectrochemistryPorosityDiffusionCatalysisElectrosynthesisElectrodeNanotechnologyCurrent densityLayer (electronics)Gas diffusion electrodeComposite materialOrganic chemistryChemistryPolymerPhysical chemistryFuel cells

Abstract

fetched live from OpenAlex

Abstract The electrosynthesis of value‐added multicarbon products from CO 2 is a promising strategy to shift chemical production away from fossil fuels. Particularly important is the rational design of gas diffusion electrode (GDE) assemblies to react selectively, at scale, and at high rates. However, the understanding of the gas diffusion layer (GDL) in these assemblies is limited for the CO 2 reduction reaction (CO 2 RR): particularly important, but incompletely understood, is how the GDL modulates product distributions of catalysts operating in high current density regimes &gt; 300 mA cm −2 . Here, 3D‐printable fluoropolymer GDLs with tunable microporosity and structure are reported and probe the effects of permeance, microstructural porosity, macrostructure, and surface morphology. Under a given choice of applied electrochemical potential and electrolyte, a 100 × increase in the C 2 H 4 :CO ratio due to GDL surface morphology design over a homogeneously porous equivalent and a 1.8 × increase in the C 2 H 4 partial current density due to a pyramidal macrostructure are observed. These findings offer routes to improve CO 2 RR GDEs as a platform for 3D catalyst design.

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 score0.077
Threshold uncertainty score0.868

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)0.0010.000

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 head0.255
Teacher spread0.247 · 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

Citations108
Published2021
Admission routes2
Has abstractyes

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