Photochemically Driven Peptide Formation in Supersaturated Aerosol Droplets
Bibliographic record
Abstract
Abstract The condensation of amino acids into peptides plays a crucial role in protein synthesis and is thus essential for understanding the origins of life. However, the spontaneous formation of peptides from amino acids in bulk aqueous media is energetically unfavorable, posing a challenge for elucidating plausible abiotic mechanisms. In this study, we investigate the formation of amide bonds between amino acids within highly supersaturated aerosol droplets containing dicyandiamide (DCD), a cyanide derivative potentially present on primordial Earth. Metastable states, i.e. supersaturation, within individual micron‐sized droplets are studied using both an optical trap and a linear quadrupole electrodynamic balance. When irradiated with intense visible light, amide bond formation is observed to occur and can be monitored using vibrational bands in Raman spectra. The reaction rate is found to be strongly influenced by droplet size and kinetic modelling suggests that it is driven by the photochemical product of a DCD self‐reaction. Our results highlight the potential of atmospheric aerosol particles as reaction environments for peptide synthesis and have potential implications for the prebiotic chemistry of early Earth.
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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".