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Record W4401048952 · doi:10.1021/acs.langmuir.4c01444

Electrocatalysis of CO<sub>2</sub> Reduction by Immobilized Formate Dehydrogenase without a Metal Redox Center

2024· article· en· W4401048952 on OpenAlexafffund
ZhangFei Su, Reem Elmahdy, Jan F. Biernat, Aicheng Chen, Jacek Lipkowski

Bibliographic record

VenueLangmuir · 2024
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsUniversity of Guelph
FundersCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsElectrocatalystRedoxFormateChemistryInorganic chemistryFormate dehydrogenaseCenter (category theory)MetalReduction (mathematics)Oxidation reductionTransition metalCatalysisElectrochemistryElectrodePhysical chemistryOrganic chemistryBiochemistryCrystallography

Abstract

fetched live from OpenAlex

Nicotinamide adenine dinucleotide-dependent formate dehydrogenase from Candida boidinii was immobilized in a 1,2-dimyristoyl- sn -glycero-3-phosphocholine/cholesterol floating lipid bilayer on the gold surface as a biocatalyst for electrochemical CO 2 reduction. We report that, in contrast to common belief, the enzyme can catalyze the electrochemical reduction of CO 2 to formate without the cofactor protonated nicotinamide adenine dinucleotide. The electrochemical data indicate that the enzyme-catalyzed reduction of CO 2 is diffusion-controlled and is a reversible reaction. The orientation and conformation of the enzyme were investigated by surface-enhanced infrared reflection absorption spectroscopy. The α-helix of the enzyme adopts an orientation nearly parallel to the surface, bringing its active center close to the gold surface. This orientation allows direct electron transfer between CO 2 and the gold electrode. The results in this paper provide a new method for the development of enzymatic electrocatalysts for CO 2 reduction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations12
Published2024
Admission routes2
Has abstractyes

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