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Record W1970232442 · doi:10.1021/la0625594

Infrared Near-Field Detection of a Narrow Resonance Due to Molecular Vibrations in a Nanoparticle

2007· article· en· W1970232442 on OpenAlexaff
Vyacheslav Romanov, Gilbert C. Walker

Bibliographic record

VenueLangmuir · 2007
Typearticle
Languageen
FieldEngineering
TopicNear-Field Optical Microscopy
Canadian institutionsUniversity of Toronto
FundersNational Institute of Biomedical Imaging and Bioengineering
KeywordsDipoleInfraredMolecular physicsSurface roughnessMaterials scienceOpticsNanoparticleChemistryNanotechnologyPhysics

Abstract

fetched live from OpenAlex

Di-iron nonacarbonyl particles on a gold surface have been imaged using an apertureless near-field scanning infrared microscopy. First and second harmonic detection, with and without an auto-homodyning option, have been used to collect the near-field spectrum of a single vibrational mode of the bridging carbonyls in di-iron nonacarbonyl nanocrystalline flakes on a gold surface. The experimental results have been compared to two theoretical models, a static image-dipole effective medium and an image dipole modified by a Fresnel coefficient for the appropriate observation angle. The calculations have taken into account the roughness of the gold film. The phase dependence of the near-field contrast has been investigated using broadband and tunable CO2 lasers. Particle size effects on contrast and spatial resolution have been studied to determine the limits of applicability of the half-space approximation.

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 score0.002

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 communication0.0000.000
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 head0.004
GPT teacher head0.220
Teacher spread0.216 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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