Electron stimulated desorption from condensed benzene
Bibliographic record
Abstract
) in thin films deposited on a Pt substrate is investigated by electron stimulated desorption (ESD) of anions and cations. The desorbed yields are recorded as a function of incident electron energy in the range of 10 to 950 eV for a fixed film thickness of 2 monolayers (ML) and for a fixed energy of 950 eV, as well as a function of film thickness from 0.5 to 8 monolayers (ML) for anions, and from 0.5 to 12ML for cations. Both energy and thickness dependencies are discussed in terms of the three main mechanisms yielding positively and/or negatively charged fragments: dissociative electron attachment (DEA), dipolar dissociation (DD) and dissociative ionization (DI) processes. At the probed energies, DD is the major mechanism, while DEA is predominantly induced by secondary electrons from the Pt substrate. Desorption of the parent positive ion is strongly suppressed. Similar qualitative behaviours are observed for the energy dependence of both anion and cation ESD yields, while some discrepancies exist in the thickness dependence, including a very significant systematic magnitude difference found between such ions formation. An estimation of the effective DD cross-section including the desorption probability is obtained. Feasible mechanisms behind the observed energy and thickness dependences for anion and cation yields are proposed. These results highlight the need for further investigations to better understand the underlying processes of electron induced dissociation in condensed matter.
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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) | 0.003 | 0.001 |
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".