Excess electron transport in cryoobjects
Bibliographic record
Abstract
Experimental results on excess electron transport in solid and liquid phases of Ne, Ar, and solid N2–Ar mixture are presented and compared with those for He. The muon spin relaxation technique in frequently switching electric fields was used to study the phenomenon of delayed muonium formation: excess electrons liberated in the μ+ ionization track converge upon the positive muons and form Mu (μ+e−) atoms. This process is shown to be crucially dependent upon the electron’s interaction with its environment (i.e., whether it occupies the conduction band or becomes localized in a bubble of tens of angstroms in radius) and upon its mobility in these states. The characteristic lengths involved are 10−6–10−4 cm, and the characteristic times range from nanoseconds to tens of microseconds. Such a microscopic length scale sometimes enables the electron to spend its entire free lifetime in a state which may not be detected by conventional macroscopic techniques. The electron transport processes are compared in: liquid and solid helium (where the electron is localized in a bubble); liquid and solid neon (where electrons are delocalized in the solid, and the coexistence of localized and delocalized electron states in the liquid was recently found); liquid and solid argon (where electrons are delocalized in both phases); orientational glass systems (solid N2–Ar mixtures), where our results suggest that electrons are localized in an orientational glass. This scaling from light to heavy rare gases enables us to reveal new features of excess-electron localization on a microscopic scale. Analysis of the experimental data makes it possible to formulate the following tendency of the muon end-of-track structure in condensed rare gases. The muon–self-track interaction changes from isolated-pair (muon plus the nearest track electron) in helium to multipair (muon in the vicinity of tens of track electrons and positive ions) in argon.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".