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Record W1773443732 · doi:10.1039/c5lc00573f

Reversible nanostructuration of microfluidic electrode devices by CNT magnetic co-entrapment

2015· article· en· W1773443732 on OpenAlexaff
Zorione Herrasti, Fernando Martínez, Eva Baldrich

Bibliographic record

VenueLab on a Chip · 2015
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsApplied Nanotools (Canada)
FundersEuropean Regional Development FundInstituto de Salud Carlos III
KeywordsEntrapmentMicrofluidicsElectrodeNanotechnologyMaterials scienceChemistryMedicine

Abstract

fetched live from OpenAlex

Carbon nanotubes (CNTs) have been extensively used to produce electrodes of enhanced performance but have only been very recently exploited in microfluidic devices. In these cases, CNT electrodes had to be produced prior to device assembly, which might damage the CNT layer. Here, we show a fast and simple method for the reversible nanostructuration of microfluidic electrode devices in situ. The procedure is based on the attachment of single-walled CNTs (SWCNTs) onto the surface of magnetic particles (MPs) and magnetic confinement of the MP/SWCNT composite onto the sensor in a two-step process that provided homogeneous coating. As it is shown, subsequent magnet removal allows MP/SWCNT release and electrode reutilization. Compared to most previously described methods, ours is faster, simpler and also reversible.

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 score0.022
Threshold uncertainty score0.445

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)0.0000.000

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 head0.008
GPT teacher head0.202
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.

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

Citations3
Published2015
Admission routes1
Has abstractyes

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