Ice Nucleation of Model Nanoplastics and Microplastics: A Novel Synthetic Protocol and the Influence of Particle Capping at Diverse Atmospheric Environments
Bibliographic record
Abstract
Little is known about airborne atmospheric aerosols containing emerging contaminants such as nano- and microplastics. A novel, minimum energy usage, synthetic protocol of plastic micro/nanoparticles was herein developed. Stable plastic hydrosols were synthesized and characterized using three different types of plastics. The ice nucleation efficiency (INE) was investigated in both normal and synthetic seawater to mimic environmental ice nucleation. Among the three tested plastic precursors (low-density polyethylene, high-density polyethylene, and polypropylene), polypropylene produced the highest particle density with narrow particle size distribution. The change of size, shape, surface charge, and electronic behavior of the plastic nano- and microparticles accounted for the altered INE. The effects of environmental factors such as particle acidity and temperature on ice nucleation were also examined. An increase in pH increased INE due to an increased particle density (number of particles per unit volume), whereas increased temperature decreased INE significantly due to aggregation (attaching particles to produce a larger particle). Four types of capping were used on the surfaces of nano- and microplastics to investigate how the plastics act to nucleate ice when mixed with different particles. They include (a) ZnO as an emerging metal contaminant, (b) kaolin as a clay mineral, (c) HgCl 2 as a toxic ionic water pollutant, and (d) phenanthrene as a polycyclic aromatic hydrocarbon. Capping by ZnO and HgCl 2 decreased the INE of plastic nano- and microparticles, whereas kaolin and phenanthrene enhanced INE significantly. The association of contaminants to micro- and nanoplastics changes INE likely due to water affinity, surface buckling, and lattice mismatch energy of ice, affecting ice nuclei formation processes. The observed differential physicochemical behaviors of nano- and microplastics, with and without co-contaminant cappings, provide further insights to understand natural environmental ice nucleation and precipitation events. Our work shows that future emissions of nano- and microplastics may become important for cloud formation and thus anthropogenic climate change.
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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) | 0.000 | 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".