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Record W2049782204 · doi:10.1364/ao.48.001062

Electrochemical threshold conditions during electro-optical switching of ionic electrophoretic optical devices

2009· article· en· W2049782204 on OpenAlexaff
Richard T. F. Wong, Peter C. P. Hrudey, Lorne Whitehead

Bibliographic record

VenueApplied Optics · 2009
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceElectrochemistryElectrodeIonIonic bondingOptoelectronicsAnalytical Chemistry (journal)Chemistry

Abstract

fetched live from OpenAlex

Electro-optical modulation by electrophoresis of dye ions is a promising technique for applications such as electronic paper displays and nonmechanical beam steering devices. To achieve a sufficient response rate in these devices, the transition time between two different optical states can be decreased by increasing the magnitude of the voltage applied across the electrodes, but this also leads to irreversible and undesirable electrochemical reactions. An electron tunneling model has been developed to describe the electrochemical reaction and to better understand the conditions determining its onset. The model gives rise to three predictions that were subsequently confirmed experimentally: the magnitude of the applied surface charge density should determine the rate of electrochemical activity, the bulk concentration of ions in the solution should shift the threshold voltage at which electrochemical reactions occur, and the reaction rate should be substantially enhanced around nanometer-sized bumps on the electrode surface. Applying this new understanding, the transition time of a device incorporating porous zinc antimonate (ZnSb2O6) electrodes and a solution of Methylene Blue dye in methanol was reduced by a factor of approximately 20.

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 score0.132
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 integrity0.0000.001
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 head0.003
GPT teacher head0.198
Teacher spread0.195 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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