Laboratory simulated aging of polystyrene particles and characterization of the resulting nanoscale plastics
Bibliographic record
Abstract
Plastics are increasingly produced and used worldwide for their easy accessibility and cost-effectiveness. However, improper plastic disposal has led to ecosystem pollution due to their slow degradation in the natural environment. While worldwide polystyrene (PS) production is estimated at around 21 million tons (8% of all polymer types), the observed PS in recovered plastics from environmental samples does not align with this production volume. Therefore, we hypothesize that the chemical composition of PS might undergo alternations during natural weathering, resulting in fewer identifiable PS components in extracted waste or other environmental samples. To test this hypothesis and comprehend the potential fate and behavior of PS after aging, we conducted lab-accelerated aging processes on pristine PS particles. Through thermal aging and probe sonication, the size distribution of 500 nm polystyrene particles (PS500) was reduced to around 200 nm, as measured by dynamic light scattering (DLS). We further examined the morphology of processed PS500 using atomic force microscopy (AFM), which confirmed changes in shape and size. In total, 97% of PS500 experienced distinct structural changes, whereas 40% of the particles exhibited a ring-opening reaction arising from the conjugated C=C bond breakage, followed by the C-H bond breakage after the laboratory-accelerate aging process; the remaining particles went through chemical changes to different extents. These physical and chemical changes resulting from the simulated aging process contribute to our understanding of the potential destiny of microplastics, underscoring the significance of weathering factors in micro/nanoplastics research.
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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 | 0.001 |
| 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".