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Record W3152658238 · doi:10.1039/d1cc01010g

Wireless electrochemiluminescence at functionalised gold microparticles using 3D titanium electrode arrays

2021· article· en· W3152658238 on OpenAlexaff
Samantha F. Douman, D. A. Collins, Loanda R. Cumba, Stephen Beirne, Gordon G. Wallace, Zhilian Yue, Emmanuel I. Iwuoha, Federica Melinato, Yann Pellegrin, Robert J. Forster

Bibliographic record

VenueChemical Communications · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsBell (Canada)
FundersEuropean Regional Development FundCentre of Excellence for Electromaterials Science, Australian Research CouncilAustralian National Fabrication FacilityWater Research CommissionAgence Nationale de la RechercheEnvironmental Protection AgencyScience Foundation Ireland
KeywordsElectrochemiluminescenceElectrodeTitaniumMaterials scienceNanotechnologyWirelessTitanium dioxideColloidal goldOptoelectronicsChemistryNanoparticleComputer scienceComposite materialTelecommunicationsMetallurgy

Abstract

fetched live from OpenAlex

Wireless electrochemiluminescence is generated using interdigitated, 3D printed, titanium arrays as feeder electrodes to shape the electric field. Gold microparticles (45 μm diameter), functionalised with 11-mercaptoundecanoic acid, act as micro-emitters to generate electrochemiluminescence from [Ru(bpy)3]2+, (bpy is 2,2'-bipyridine) where the co-reactant is tripropylamine. The oxide coated titanium allows intense electric fields, whose distribution depends on the geometry of the array, to be created in the absence of deliberately added electrolyte. COMSOL modelling and long exposure ECL imaging have been used to map the electric field distribution. Significantly, we demonstrate that by controlling the surface charge of the gold microparticles through the solution pH, the light intensity can be increased by a factor of more than 10.

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 score0.007

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.285
Teacher spread0.263 · 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

Citations23
Published2021
Admission routes1
Has abstractyes

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Same venueChemical CommunicationsSame topicAdvanced biosensing and bioanalysis techniquesFrench-language works237,207