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Record W1999419699 · doi:10.1149/1.1639165

Microfabrication of Glassy Carbon by Electrochemical Etching

2004· article· en· W1999419699 on OpenAlexaff
Gregory K. Kiema, Solomon Ssenyange, Mark T. McDermott

Bibliographic record

VenueJournal of The Electrochemical Society · 2004
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicrofabricationGlassy carbonElectrochemistryEtching (microfabrication)Materials scienceCarbon fibersNanotechnologyChemical engineeringChemistryComposite materialCyclic voltammetryPhysical chemistryElectrodeFabricationEngineering

Abstract

fetched live from OpenAlex

Due to the broad impact of microfabrication technology on chemistry and biology, new methods to pattern and etch a variety of materials are being explored in a number of laboratories. We have developed a method for the etching of glassy carbon (GC) that opens pathways for the creation of new electrode patterns and devices. The method involves standard pattern transfer to a photoresist layer and anodization of the exposed GC substrate in basic electrolyte. The electrode reaction results in a breakup of the carbon lattice and likely involves the intercalation of hydroxide anions. The depth of etching can be controlled with potential, time or charge. The etching process is isotropic due to the nano-scale graphitic microcrystallite size of GC. We demonstrate the fabrication of microchannel structures directly into GC and the preparation of arrays of submicrometer sized carbon electrodes via the etching of patterned carbon films. © 2004 The Electrochemical Society. All rights reserved.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.003
GPT teacher head0.196
Teacher spread0.194 · 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
GenreMethods

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

Citations17
Published2004
Admission routes1
Has abstractyes

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