Investigations of electron removal processes in slow He$^{2+}$ and He$^{+}$-Ne$_2$ collisions indicate high Interatomic Coulombic Decay yield
Bibliographic record
Abstract
We implement an independent-atom and independent-electron model to investigate the collision systems of He$^{2+}$ and He$^{+}$ ion projectiles impinging on a neon dimer target. The dimer is set to be stationary at its equilibrium bond length with the projectile traveling parallel to the dimer axis at a speed corresponding to the collision energy of 10 keV/amu. Two approaches called multinomial and determinantal are used as an analysis of these collisions. Each of the analyses is broken down into two types of models that do not and do include a change in the projectile charge state due to electron capture from the dimer. All calculations are performed using both a frozen atomic target and a dynamic response model using the coupled-channel two-center basis generator method for orbital propagation. All one- and two- electron removal processes are calculated, though particular attention is paid to those that result in the Ne$^{+}$-Ne$^{+}$ fragmentation channel due to its association with interatomic Coulombic decay (ICD). We confirm in all analyses and models that Ne(2$s$) electron removal is strong so that ICD will contribute to dimer fragmentation as has been previously demonstrated. The model that takes into account the change in projectile charge state indicates that there is a pure ICD yield when utilizing a He$^{+}$ projectile.
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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 | 0.000 |
| Open science | 0.001 | 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".