Electron, proton and ion induced molecular synthesis and VUV spectroscopy of interstellar molecules in the ice phase
Bibliographic record
Abstract
Abstract Planets and their moons are constantly subjected to irradiation from both their respective planetary magnetospheres and the solar wind. Energetic particles (electrons, protons and ions) in such radiation may induce complex chemistry within the icy mantles of such bodies, producing many organic compounds. Such processes can be simulated in laboratory experiments. In this report we present recent results from experiments exploring both molecular synthesis and the morphology of such ices. The morphology of any ice may be characterised by IR and Vacuum Ultra-Violet (VUV) spectroscopy. The latter is particularly useful for studying ices in which infrared inactive molecules like oxygen (O2) are common. We have shown that oxygen forms dimers in typical planetary ices and that, in contrast to previous analysis, many of the chemical reactions within the ice involve such dimer (and larger cluster) chemistry. We also present the results of a series of experiments that explore electron, proton and ion irradiation on Solar System relevant ices such as carbon dioxide (CO2) at different temperatures. Infrared spectra recorded before and after irradiation are used to identify and quantify molecules formed in such irradiation, e. g. ozone. These experiments show that the morphology of the ice plays a critical role in the chemistry.
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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) | 0.001 | 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".