Glycine formation in CO2:CH4:NH3 ices induced by 0-70 eV electrons
Bibliographic record
Abstract
Glycine (Gly), the simplest amino-acid building-block of proteins, has been identified on icy dust grains in the interstellar medium, icy comets, and ice covered meteorites. These astrophysical ices contain simple molecules (e.g., CO2, H2O, CH4, HCN, and NH3) and are exposed to complex radiation fields, e.g., UV, γ, or X-rays, stellar/solar wind particles, or cosmic rays. While much current effort is focused on understanding the radiochemistry induced in these ices by high energy radiation, the effects of the abundant secondary low energy electrons (LEEs) it produces have been mostly assumed rather than studied. Here we present the results for the exposure of multilayer CO2:CH4:NH3 ice mixtures to 0-70 eV electrons under simulated astrophysical conditions. Mass selected temperature programmed desorption (TPD) of our electron irradiated films reveals multiple products, most notably intact glycine, which is supported by control measurements of both irradiated or un-irradiated binary mixture films, and un-irradiated CO2:CH4:NH3 ices spiked with Gly. The threshold of Gly formation by LEEs is near 9 eV, while the TPD analysis of Gly film growth allows us to determine the “quantum” yield for 70 eV electrons to be about 0.004 Gly per incident electron. Our results show that simple amino acids can be formed directly from simple molecular ingredients, none of which possess preformed C—C or C—N bonds, by the copious secondary LEEs that are generated by ionizing radiation in astrophysical ices.
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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".