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Record W2807617216 · doi:10.1039/c8cp02147c

Measuring the orientation of a single CdSe/CdS nanocrystal at the end of a near-field tip for the realization of a versatile active SNOM probe

2018· article· en· W2807617216 on OpenAlexaff
Rabeb Jazi, Thi Phuong Lien Ung, Pierre Maso, Gérard Colas des Francs, Michel Nasilowski, Benoît Dubertret, Jean‐Pierre Hermier, Xavier Quélin, Stéphanie Buil

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2018
Typearticle
Languageen
FieldEngineering
TopicNear-Field Optical Microscopy
Canadian institutionsCanadian Nautical Research Society
FundersAgence Nationale de la Recherche
KeywordsPerpendicularNear-field scanning optical microscopeDipoleOpticsCoupling (piping)NanocrystalOptical microscopeLayer (electronics)Materials scienceMicroscopeOrientation (vector space)Near and far fieldOptical axisRealization (probability)NanotechnologyChemistryPhysicsGeometryScanning electron microscope

Abstract

fetched live from OpenAlex

The orientation of a CdSe/CdS nanocrystal attached at the end of a scanning near field optical microscope (SNOM) tip is analyzed by its coupling with a flat gold layer. The Purcell factors for a set of distances to the gold surface are measured after a NC is caught by a SNOM tip. These measurements are compared with the modeling of the emission of a 2D dipole on a gold layer taking into account the layer of polymer serving as a glue for the NC. The 2D dipole is perpendicular to the c-axis of the NC, which is the growth axis. The behavior of the Purcell factor as a function of the distance to the gold layer depends on the angle made by this axis and the surface. The adjustment of the experimental results and the modelization gives the orientation of the NC at the end of the SNOM tip. Different orientations of the c-axis are determined.

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 score0.005

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 head0.015
GPT teacher head0.235
Teacher spread0.220 · 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
Published2018
Admission routes1
Has abstractyes

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