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Record W2323140299 · doi:10.1021/ac2012703

Cyclic Biamperometry at Micro-Interdigitated Electrodes

2011· article· en· W2323140299 on OpenAlexaff
Mehdi Rahimi, Susan Mikkelsen

Bibliographic record

VenueAnalytical Chemistry · 2011
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCyclic voltammetryElectrodeChemistryRedoxBorosilicate glassWorking electrodeElectrochemistryFerrocyanideReference electrodeAnalyteAnalytical Chemistry (journal)Chemically modified electrodeVoltammetryNanotechnologyInorganic chemistryMaterials scienceChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Cyclic biamperometry was studied as an analytical method for use with commercially available, comb-type, coplanar microinterdigitated electrodes (μIDEs), using the ferri-/ferrocyanide redox couple as a model analyte. The μIDEs studied in this work were made of gold that had been deposited onto a Ti/W adhesion layer on borosilicate glass chips and had 5 and 10 μm bands with equal gap sizes. Close proximity of the two working electrodes, and their interdigitation, resulted in signal amplification by redox cycling. Results were compared with those obtained by cyclic voltammetry, where one of the two IDE electrodes was used as the working electrode and external reference and auxiliary electrodes were used. Amplification factors of almost 20 were achieved due to redox cycling. Attempts to apply cyclic voltammetry to the μIDEs, with one of the combs as the working and the other as the auxiliary electrode, were unsuccessful due to corrosion of the auxiliary electrode comb. Results of this study, and the electrochemically unique feature of biamperometry to probe but not change the net contents of the medium under examination, suggest the applicability of scanning biamperometry at μIDEs to the very small volumes and electrochemical cell dimensions that are now of great interest.

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), Insufficient payload (model declined to judge)
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 score0.187
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)0.0110.001

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 head0.019
GPT teacher head0.232
Teacher spread0.213 · 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

Citations25
Published2011
Admission routes1
Has abstractyes

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