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Record W2055733347 · doi:10.1021/la052767g

Electric Field Driven Protonation/Deprotonation of Self-Assembled Monolayers of Acid-Terminated Thiols

2006· article· en· W2055733347 on OpenAlexaff
Ian J. Burgess, Brian Seivewright, R. Bruce Lennox

Bibliographic record

VenueLangmuir · 2006
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsDeprotonationProtonationChemistryDielectric spectroscopyMonolayerSelf-assembled monolayerAnalytical Chemistry (journal)Computational chemistryPhotochemistryElectrochemistryPhysical chemistryOrganic chemistryElectrodeIon

Abstract

fetched live from OpenAlex

Using electrochemical impedance spectroscopy (EIS), we provide an explanation for the pH dependence of the voltammetric peak height for the electric-field-driven protonation and deprotonation of carboxylic acid-terminated thiol self-assembled monolayers (SAMs). The current flowing through the interface can be divided into a purely capacitive current and a protonation/deprotonation current that is directly related to the rate of change of the SAM's protonation (or deprotonation). We demonstrate that at applied potentials close to those corresponding to half-ionization of the SAM and pHs near the pK(1/2), the equivalent circuit describing the interface consists of a Helmholtz film capacity in parallel with a "protonation/deprotonation" impedance which is further shown to be a series combination of a resistor, Rp, and capacitor Cp. Explicit expressions for Rp and Cp are derived in terms of the rate constants for the forward (protonation) and reverse (deprotonation) reactions. Simulated EIS data demonstrate the agreement between our model of the interface and experimental impedance and voltammetric 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 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 score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.004
GPT teacher head0.222
Teacher spread0.218 · 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

Citations81
Published2006
Admission routes1
Has abstractyes

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