Surface Vibrational Spectroscopy Study of Benzene and 2,2,2-Trifluoroacetophenone on Pt(111)
Bibliographic record
Abstract
High resolution electron energy loss spectroscopy (HREELS) data for C 6 H 6 and C 6 D 6 on Pt(111) were measured as a function of coverage. The spectra show five additional loss peaks with respect to earlier reports that were used in density functional theory (DFT) calculations of the properties of benzene on Pt(111). The spectra display a strong coverage dependence in the CH stretching region. HREELS and STM data for the adsorption of 2,2,2-trifluoroacetophenone (TFAP) on Pt(111) are used in the analysis of the benzene/Pt(111) system. The TFAP spectra display the same coverage dependence as benzene in the CH stretching region. An analysis of STM images of TFAP dimers shows that their azimuthal orientation is not consistent with the occupation of hcp0 sites. The data for benzene adsorption cannot be explained on the basis of existing density functional theory (DFT) calculations. In particular, the spectra are not consistent with either a C 2 v symmetry bridge adsorption or a combination of adsorption at C 2 v symmetry and hcp0 sites. The data provide a benchmark for evaluating the ability of emerging computational approaches to predict the chemisorption properties of strongly chemisorbed aromatics. The data for both benzene and TFAP are of relevance to the asymmetric hydrogenation of ketones on chirally modified Pt catalysts.
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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 | 0.000 |
| 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) | 0.002 | 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".