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Record W3024745121 · doi:10.1002/adma.201902177

Metal‐Free Hydrogen‐Bonded Polymers Mimic Noble Metal Electrocatalysts

2020· article· en· W3024745121 on OpenAlexafffund
Halime Coskun, Abdalaziz Aljabour, Phil De Luna, He Sun, Nobuyuki Nishiumi, Tsukasa Yoshida, Georg Koller, Michael G. Ramsey, T. Greunz, David Stifter, Moritz Strobel, Sabine Hild, Achim Walter Hassel, Niyazi Serdar Sariçiftçi, Edward H. Sargent, Philipp Stadler

Bibliographic record

VenueAdvanced Materials · 2020
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaAustrian Science Fund
KeywordsOverpotentialElectrocatalystMaterials sciencePlatinumElectrochemistryHydrogenPolymerElectrolysisCatalysisChemical engineeringElectrolysis of waterInorganic chemistryNoble metalMetalCombinatorial chemistryElectrodeChemistryOrganic chemistryPhysical chemistryComposite material

Abstract

fetched live from OpenAlex

The most active and efficient catalysts for the electrochemical hydrogen evolution reaction (HER) rely on platinum, a fact that increases the cost of producing hydrogen and thereby limits the widespread adoption of this fuel. Here, a metal-free organic electrocatalyst that mimics the platinum surface by implementing a high work function and incorporating hydrogen-affine hydrogen bonds is introduced. These motifs, inspired from enzymology, are deployed here as selective reaction centres. It is shown that the keto-amine hydrogen-bond motif enhances the rate-determining step in proton reduction to molecular hydrogen. The keto-amine-functionalized polymers reported herein evolve hydrogen at an overpotential of 190 mV. They share certain key properties with platinum: a similar work function and excellent electrochemical stability and chemical robustness. These properties allow the demonstration of one week of continuous HER operation without notable degradation nor delamination from the carrier electrode. Scaled continuous-flow electrolysis is reported and 1 L net molecular hydrogen is produced within less than 9 h using 2.3 mg of polymer electrocatalyst.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.217
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

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

Citations33
Published2020
Admission routes2
Has abstractyes

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