Disentangling surface atomic motions from surface field effects in ultrafast low-energy electron diffraction
Bibliographic record
Abstract
Abstract Ultrafast low-energy electron diffraction holds potential to provide atomic level details to the surface dynamics controlling processes from surface chemistry to exotic collective effects. Accessing the primary timescales requires subpicosecond excitation pulses to prepare the corresponding nonequilibrium state. The needed excitation for maximum contrast above background invariably leads to photoinduced electron emission with the creation of surface fields that affect diffraction and must be quantified to recover the key structural dynamics. Using 2 keV ultrashort low-energy electron bunches, we investigate this field effect on the ensuing electron distribution in projection imaging and diffraction as a function of excitation intensity. Using a structural model, we demonstrate a quantitative separation of the surface field effect on electron diffraction, enabling isolation of the structural dynamics of interest. Particle trajectory simulations provide insight into the correlation between geometrical characteristics of the charge separated region and the corresponding intensity modulation at the detector.
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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 | 0.000 | 0.001 |
| 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".