Electrochemical Surface-Enhanced Raman Spectroscopy (EC-SERS) and Computational Study of Atrazine: Toward Point-of-Need Detection of Prevalent Herbicides
Bibliographic record
Abstract
This paper presents an electrochemical SERS (EC-SERS) and computational study of the common herbicide atrazine. Herein, we highlight that the atrazine molecule shows a clear potential-dependent SERS signal that manifests as two different adsorption orientations at the nanostructured silver surface. This finding is supported by computational work and indicates that the initial adsorption orientation is perpendicular to the surface with the C–Cl moiety pointed away from the surface, and upon stepping to negative applied voltages, the atrazine molecule rotates such that the C–Cl and isopropyl moieties are orientated more planar to the surface, while the molecule remains oriented perpendicular to the surface. To the best of our knowledge, this paper represents the first EC-SERS study of atrazine and paves the way for a rapid point-of-need detection tool for atrazine monitoring in the environment wherein an enhanced signal can be detected at negative applied voltages.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".