Investigation of the Adsorption of <scp>l</scp>-Cysteine on a Polycrystalline Silver Electrode by Surface-Enhanced Raman Scattering (SERS) and Surface-Enhanced Second Harmonic Generation (SESHG)
Bibliographic record
Abstract
The adsorption of l -cysteine ( l -Cys) onto a polycrystalline silver electrode surface was investigated by in situ spectroelectrochemical methods. Surface-enhanced Raman spectroscopy (SERS) and surface-enhanced second-harmonic generation (SESHG) measurements were performed in a 0.2 M KCl solution in the presence and absence of l -Cys. The experimental results indicated that l -Cys strongly adsorbs onto silver and remains on the surface at potentials as negative as −900 mV (vs Ag/AgCl). A peak around −650 mV was observed in the SESHG intensity versus applied potential plots obtained in the presence of l -Cys. The peak was indicative of an abrupt change in the electronic properties of the interface at that potential. The SERS spectra at potentials more negative than ca. −650 mV showed an increase in the intensity of vibrational modes assigned to the carboxylate group of l -Cys. The combination of the SERS and the SESHG results suggests a potential-induced reorientation of the adsorbed l -Cys molecules for potentials more negative than −650 mV. The data interpretation considered the different possible conformational forms of l -Cys adsorbed on the Ag surface. At potentials more positive than ca. −650 mV, l -Cys molecules adsorb with the protonated amino group pointing toward the surface. In this case, the positively charged amino group is stabilized by the coadsorbed chloride anions. The molecule changes its conformation at potentials more negative than −650 mV as the chloride ions leave the surface. The C α −C β bond rotation brings the carboxylate group closer to the surface at these potentials.
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 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 | 0.000 |
| 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 | 0.001 | 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".