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Photothermal cantilever deflection spectroscopy

2014· article· en· W2176565820 on OpenAlexafffund
Seonghwan Kim, Dongkyu Lee, Thomas Thundat

Bibliographic record

VenueEPJ Techniques and Instrumentation · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMechanical and Optical Resonators
Canadian institutionsUniversity of AlbertaUniversity of Calgary
FundersMinistry of Education, Science and TechnologyNational Research Foundation of KoreaCanada Excellence Research Chairs, Government of CanadaNational Research FoundationUniversity of Calgary
KeywordsCantileverDeflection (physics)Photothermal therapyPhotothermal spectroscopyMaterials scienceSpectroscopyAdsorptionForce spectroscopyWavelengthMoleculeInfraredSelectivityChemistryOptoelectronicsOpticsAnalytical Chemistry (journal)NanotechnologyComposite materialPhysicsChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Microcantilever sensors offer high sensitivity in the detection of adsorbed molecules based either on resonance frequency shift or changes in cantilever deflection, as both of these signals can be detected with very high resolution. Despite the high sensitivity offered by this platform, cantilevers suffer from poor selectivity due to the lack of sufficiently selective interfacial layers which can be immobilized on cantilever surfaces. This problem can be overcome by using photothermal cantilever deflection spectroscopy (PCDS), which exploits the high thermomechanical sensitivity of bi-material microcantilevers. A bi-material cantilever responds to heat generated by the nonradiative decay process when the adsorbed molecules are resonantly excited with infrared (IR) light. The variation in the cantilever deflection as a function of illuminating IR wavelength corresponds to the conventional IR absorption spectrum of the adsorbed molecules. In addition, the mass of the adsorbed molecules can be determined by measuring the resonance frequency shift of the cantilever as an orthogonal signal for the quantitative analysis. This multi-modal PCDS offers unprecedented opportunities for obtaining very high selectivity in chemical and biological sensing without using selective interfacial layers or extrinsic labels.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.561

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)0.0010.000

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 head0.005
GPT teacher head0.246
Teacher spread0.241 · 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

Citations21
Published2014
Admission routes2
Has abstractyes

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