Dust Collisions in Protoplanetary Disks: Atomic Simulations of the Surface Free Energy
Bibliographic record
Abstract
Coagulation of dust particles in protoplanetary disks is the first step on the journey to the formation of planets. The surface free energy (SFE) of the dust particles determines the effectiveness of particles sticking to each other after collision, as well as the critical collision velocity above which fragmentation will occur. Studies of SFE have focused on the simplest silicate, silica, usually at standard temperature and pressure. However, protoplanetary dust grains have a wide variety of mineralogical compositions, temperatures, and a low-pressure environment lacking in water vapor. We perform molecular dynamics simulations using a ReaxFF-type potential of the SFE of silica, albite, and anorthite at temperatures ranging from 30 to 700 K in a true vacuum. We find that the SFE drops by tens of percent with increasing temperature or shifting to more complex silicate compositions. More dramatically, we find that the values of the SFE in a vacuum are two orders of magnitude higher than those usually measured in terrestrial laboratories. Our results confirm previous work that suggests that hydroxylation by monolayers of water produces this reduction in SFE in experiments. The coagulation of dust grains thus appears to depend critically on the cleanliness of their surfaces, as well as their temperature and composition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".