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Record W4382140450 · doi:10.1016/s1452-3981(23)14471-3

Kinetics of Electrochemical Reduction of NAD+ on a Glassy Carbon Electrode

2013· article· en· W4382140450 on OpenAlexfundno aff
Sasha Omanovic

Bibliographic record

VenueInternational Journal of Electrochemical Science · 2013
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Engineering and Technology, Peshawar
KeywordsOverpotentialNAD+ kinaseChemistryElectrochemistryCyclic voltammetryGlassy carbonElectron transferKineticsDielectric spectroscopyReaction rate constantNicotinamide adenine dinucleotideAnalytical Chemistry (journal)Inorganic chemistryElectrodePhotochemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The kinetics of reduction of nicotinamide adenine dinucleotide, NAD, was investigated on glassy carbon (GC) electrode at various temperatures, electrode potentials and NAD concentrations using electrochemical methods of linear polarization voltammetry, differential pulse voltammetry and electrochemical impedance spectroscopy. It was shown that under the experimental conditions employed, the NAD reduction reaction is under diffusion control, is irreversible (requires overpotential of more than-550 mV), and is of pseudo-first order with respect to NAD. The reduction process involves the exchange of 1.54 or 1.62 electrons, depending on reduction potential. This indicates that 54 or 62 mol % of NADH is produced, respectively, while the remaining quantity is NAD2. The kinetics of NAD reduction at a formal potential of the NAD /NADH couple was found to be rather slow, and only moderately temperature dependent: the apparent formal heterogeneous electron-transfer rate constant is in the order of 10-14 cm s-1, and the apparent formal Gibbs energy of activation is 53.1 kJ mol –1

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 score0.003
Threshold uncertainty score0.699

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 studies0.0000.000
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 head0.004
GPT teacher head0.214
Teacher spread0.210 · 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

Citations30
Published2013
Admission routes1
Has abstractyes

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