Electron-induced molecular dissociation at a surface leads to reactive collisions at selected impact parameters
Bibliographic record
Abstract
Crossed molecular beams of gases have provided definitive information concerning the dynamics of chemical reactions. The results have, however, of necessity been averaged over collisions with impact parameters ranging from zero to infinity, thus obscuring the effect of this important variable. Here we employ a method through which impact parameter averaging is suppressed in a surface reaction. We aim a highly collimated reactive 'projectile' molecule along a surface at a stationary adsorbed 'target' molecule, with both the projectile and target being observed by Scanning Tunnelling Microscopy (STM). The projectile was CF2 recoiling from electron-induced bond-breaking in chemisorbed CF3 on Cu(110) at 4.6 K. The collimation of the resulting CF2 'surface-molecular-beam' restricted it to a lateral spread of ±1° as a consequence of its interaction with the Cu rows below. This collimation was modelled by molecular dynamics simulations. In the experiments the recoiling CF2 projectile was aimed, successively, at impact parameters of b = 0 and +3.6 Å at a chemisorbed second CF2, b = +1.8 Å at a chemisorbed I-atom, or b = -4.0, b = -0.4 and b = +3.2 Å at a chemisorbed vinyl radical. The pattern of reactive and non-reactive scattering was determined by STM. These collimated surface-molecular-beams have the potential to aim molecular projectiles with selected impact parameters at the many target species identifiable at a surface 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".