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Record W3010281656 · doi:10.1139/cjc-2020-0005

An electrochemical immittance analysis of the dielectric properties of self-assembled monolayers

2020· article· en· W3010281656 on OpenAlexaffvenue
Éric R. Dionne, Fadwa Ben Amara, Antonella Badia

Bibliographic record

VenueCanadian Journal of Chemistry · 2020
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsImmittanceDielectric spectroscopyChemistryDielectricCapacitancePermittivityMonolayerElectrical impedanceCapacitive sensingIonic bondingEquivalent circuitAnalytical Chemistry (journal)Chemical physicsIonElectrochemistryOptoelectronicsMaterials scienceElectrodeElectronic engineeringOrganic chemistryPhysical chemistryVoltageElectrical engineering

Abstract

fetched live from OpenAlex

The ability of organic self-assembled monolayers (SAMs) to act as insulating barriers to electron transfer, ion transport, or molecular diffusion is critical to their application in a variety of technologies. The use of appropriate analytical tools to characterize the dielectric properties of these molecular thin films is important for the control of structural defects and establishing structure–property relations. In this context, we analyze the ionic permeability and dielectric response of SAMs formed from a homologous series of n-alkanethiolates (CH 3 (CH 2 ) n S, where n = 9, 11, 13, 15, 17, and 19) on gold using the immittance quantities of the complex impedance, capacitance, and permittivity available from the same electrochemical impedance spectroscopy (EIS) measurement. The most sensitive parameters and frequency range for characterizing the capacitive behavior and assessing the ion-blocking quality of the SAMs under non-Faradaic conditions are identified. We also investigate the effect of chain length on the interfacial capacitance and dielectric constant of ionic insulating SAMs. The advantages of the capacitance quantity and related permittivity data over traditional impedance representations and equivalent electric circuit modeling are discussed.

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 score0.002
Threshold uncertainty score0.247

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 science0.0000.000
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 head0.004
GPT teacher head0.159
Teacher spread0.155 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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