Quantitative SNIFTIRS studies of (bi)sulfate adsorption at the Pt(111) electrode surface
Bibliographic record
Abstract
Subtractively normalized interfacial Fourier transform infrared reflection spectroscopy (SNIFTIRS) was applied to study (bi)sulfate adsorption on a Pt(111) surface in solutions of variable pH while maintaining a constant total bisulfate/sulfate ((bi)sulfate) concentration without the addition of an inert supporting electrolyte. The spectra were recorded for both the p- and s-polarizations of the IR radiation in order to differentiate between the IR bands of the (bi)sulfate species adsorbed on the electrode surface from those species located in the thin layer of electrolyte. The spectra recorded with p-polarized light consist of the IR bands from both the species adsorbed at the electrode surface and those present in the thin layer of electrolyte between the electrode surface and ZnSe window whereas the s-polarized spectra contain only the IR bands from the species located in the thin layer of electrolyte. A new procedure was developed to calculate the angle of incidence and thickness of the electrolyte between the Pt(111) electrode surface and the ZnSe IR transparent window. By combining these values with the knowledge of the optical constants for Pt, H(2)O and ZnSe, the mean square electric field strength (MSEFS) at the Pt(111) electrode surface and for thin layer of solution were accurately calculated. The spectra recorded using s-polarization were multiplied by the ratio of the average MSEFS for p- and s-polarizations and subtracted from the spectra recorded using p-polarization in order to remove the IR bands that arise from the species present within the thin layer cavity. In this manner, the resulting IR spectra contain only the IR bands for the anions adsorbed on the Pt(111) electrode surface. The spectra of adsorbed anions show little change with respect to the pH ranging from 1 to 5.6. This behavior indicates that the same species is predominantly adsorbed on the metal surface for this broad range of pH values and the results suggest that sulfate is the most likely candidate for this adsorbate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".