Surface-enhanced Raman scattering for ultrasensitive chemical analysis of 1 and 2-naphthalenethiols
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".