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Record W2329254368 · doi:10.1021/la403551c

Microcantilevers Bend to the Pressure of Clustered Redox Centers

2014· article· en· W2329254368 on OpenAlexaff
Éric R. Dionne, Violeta Toader, Antonella Badia

Bibliographic record

VenueLangmuir · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsSurface stressCantileverChemical physicsSurface plasmon resonanceRedoxNanotechnologyElectrochemistryDeflection (physics)MonolayerMaterials scienceChemistrySteric effectsElectrodePhysical chemistryStereochemistryComposite materialInorganic chemistryOpticsSurface energy

Abstract

fetched live from OpenAlex

The redox-activated deflection of microcantilevers has attracted interest for nanoactuation and chemical sensing. Microcantilever sensors are devices that transduce (bio)chemical reactions into a quantifiable nanomechanical motion via surface stress changes. Despite promising applications in analytical science, poor signal-to-noise ratios and a limited understanding of the molecular origins of the surface stress changes that cause the observed deflections remain obstacles to cantilever-based sensing becoming an established (bio)detection method, such as surface plasmon resonance and electrochemistry. We use phase-separated, binary self-assembled monolayers (SAMs) of ferrocenyldodecanethiolate and n-undecanethiolate as a model system to study the effect of the steric crowding of the redox centers on the surface stress change and cantilever deflection produced by the electrochemical oxidation of the surface-tethered ferrocene to ferrocenium. We correlate the measured surface stress change to the fraction of the clustered ferrocenyldodecanethiolate phase in the binary SAMs. The pairing of anions with the sterically crowded clustered ferroceniums induces a collective molecular reorientation which drives the cantilever deflection. The results provide fundamental insights into the response mechanism of microcantilever-based actuating and sensing technologies.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.348
Threshold uncertainty score0.171

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 head0.004
GPT teacher head0.239
Teacher spread0.235 · 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 designNot applicable
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

Citations15
Published2014
Admission routes1
Has abstractyes

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