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Record W1978858217 · doi:10.1039/b410488a

Surface-enhanced Raman scattering for ultrasensitive chemical analysis of 1 and 2-naphthalenethiols

2004· article· en· W1978858217 on OpenAlex

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

VenueThe Analyst · 2004
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRaman scatteringRaman spectroscopyDensity functional theoryNanostructureMoleculeExcitationInfraredAnalytical Chemistry (journal)Detection limitCopperChemistrySpectral lineMaterials scienceMolecular physicsNanotechnologyComputational chemistryOpticsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The results of the search for the optimal experimental conditions for ultrasentitive chemical analysis of 1-naphthalenethiol (1-NAT) and 2-naphthalenethiol (2-NAT) using surface-enhanced Raman scattering (SERS) are discussed. The report begins with a review of the vibrational spectra, including infrared and Raman spectra of the target molecules, and the interpretation of the observed frequencies aided by local density functional theory (DFT) calculations at the B3LYP/6-311G(d,p) level of theory. Several metal nanostructures were tested for SERS activity, including island films and colloids of silver, gold and copper. Correspondingly, the most effective laser line for excitation in the visible and near infrared region was sought. The achieved detection limit for 1-naphthalenethiol, and for 2-naphthalenethiol, on silver nanostructures is in the zeptomole regime.

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 score0.003
Threshold uncertainty score0.186

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 head0.021
GPT teacher head0.272
Teacher spread0.250 · 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