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Record W1945485575 · doi:10.1002/pssb.200982278

Characterization of dye molecules and carbon nanostructures by tip‐enhanced Raman spectroscopy

2009· article· en· W1945485575 on OpenAlex
Niculina Peica, Serge Röhrig, Andreas Rüdiger, Katharina Brose, C. Thomsen, Janina Maultzsch

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuephysica status solidi (b) · 2009
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsRaman spectroscopyMaterials scienceCharacterization (materials science)ConfocalOpticsSpectroscopyNanostructureMicroscopeImage resolutionRaman microscopeOptoelectronicsReflection (computer programming)Resolution (logic)NanotechnologyRaman scattering

Abstract

fetched live from OpenAlex

Abstract Tip‐enhanced Raman spectroscopy (TERS) is a high sensitivity and high spatial resolution analytical technique based on the strong field enhancement provided by a sharp metallic tip. Using a commercial atomic force microscope (AFM) combined with a confocal optical setup in reflection geometry, we are targeting samples on non‐transparent electrodes. The resulting design challenges with respect to quantum efficiency, optical accessibility of the tip and the optics themselves, were balanced and taken into consideration for the presented ultra‐high vacuum–TERS setup. Second, we describe the development of a TERS setup at normal pressure in air, and we present the confocal Raman and TERS spectra of dye molecules and other nanostructures.

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.

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 score0.007
Threshold uncertainty score0.398

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 head0.005
GPT teacher head0.221
Teacher spread0.217 · 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