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Record W2767508130 · doi:10.1002/cphc.201701018

Electrochemistry of Metalloproteins Attached through Functional Self‐Assembled Monolayers on Gold and Ferromagnetic Electrodes

2017· article· en· W2767508130 on OpenAlexaff
Prakash Chandra Mondal, Claudio Fontanesi

Bibliographic record

VenueChemPhysChem · 2017
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
Fundersnot available
KeywordsChemistryMonolayerElectron transferCyclic voltammetryNickelSelf-assembled monolayerElectrochemistryInorganic chemistryElectrodeAnalytical Chemistry (journal)PhotochemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We report the experimental results of a study of the electron-transfer processes of redox-active metalloproteins bound to mixed self-assembled monolayers (SAMs) on magnetic (nickel or ultrathin gold-coated nickel) or nonmagnetic (gold) electrodes. Metalloproteins, such as hemoglobin (Hb), Cytochrome C (Cyt C), and Cyt C oxidase, are attached through electrostatic interactions to the free carboxylate or imidazole groups present in the mixed SAMs. The formation of both mixed SAMs and SAM/metalloprotein heterostructures were confirmed by using advanced surface analysis techniques, such as polarization modulation infrared reflection absorption spectroscopy and aqueous contact angle measurements. Electrochemical measurements indicated a stronger electronic coupling between Hb and Cyt C oxidase and the mixed-SAM-coated gold or gold-coated-nickel electrodes, whereas a weaker coupling was found between the protein and the pure nickel electrode. Surface coverage and the electron-transfer rate constant were estimated from the cyclic voltammetry data.

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)
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 score0.011
Threshold uncertainty score1.000

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)0.0000.000

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 head0.014
GPT teacher head0.219
Teacher spread0.206 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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