Reaction dynamics at a metal surface; halogenation of Cu(110)
Bibliographic record
Abstract
Scanning Tunnelling Microscopy (STM) is opening up a new field of reaction dynamics, followed one-molecule-at-a-time, only recently applied to reaction at a metal surface. Here we combine experiment with theory in studying the motions involved in the successive breaking by electron-induced reaction of the two carbon-halogen bonds, C-Cl or C-I, in physisorbed p-dihalobenzene, to form chemisorbed halogen-atoms and organic residue on Cu(110) at 4.6 K. We characterize the geometry of the physisorbed initial state, p-dichlorobenzene (pDCB) and p-diiodobenzene (pDIB), at the copper surface, as well as the successive final states of both chemisorbed reaction products: electron #1 giving rise to the first halogen-atom and a chemisorbed halophenyl and electron #2 giving a second halogen-atom and a chemisorbed phenylene. The major findings reported are (a) the distance and angular distributions of the chemisorbed reaction products relative to the physisorbed reagent molecule, (b) an approximate ab initio calculation, coupled with classical molecular dynamics (MD), of the repulsion between the products on the excited potential-energy surfaces, pes*, following excitation by electrons #1 or #2, and subsequently MD on the ground-state pes with inclusion of inelastic surface-interaction as a means to understanding the above, (c) observation of the changing dynamics with the chemistry of the halogen-atom, and (d) characterization of the effects of secondary encounters among the reaction products in the constrained space of the more highly localized reaction of pDIB. Item (d) shows clear evidence of high reactivity in surface-aligned collisions with restricted impact parameter, termed Surface Aligned Reaction, SAR, characterized by STM.
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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) | 0.001 | 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".