Suspended clay and surfactants enhance buoyant microplastic settling
Bibliographic record
Abstract
Abstract Most of the plastic waste that enters rivers and the oceans is unaccounted for. Approximately half of the world’s produced plastics are buoyant in water, meaning that processes must take place that effectively increase their density, causing them to settle out of solution. One such mechanism is biofouling, in which organic matter grows on the surface of plastics, making them denser. Here we present a new mechanism supported by laboratory experiments for buoyant plastic settling in which particles of clay adhere to the surface of the plastic, mediated by the presence of surfactants. Although the plastic particles in our experiments were a hundred times larger than the micrometer-sized clay particles, we show that clay can adhere to the plastic with sufficient mass to cause the plastic to sink. This occurs even though the plastic is electrically neutral. It is hypothesized that the hydrophobic tails of the surfactant molecules are attracted to the plastic while the hydrophilic heads attract the clay. A greater fraction of plastic sinks if the surfactant concentration is larger. Our findings suggest that microplastic settling is enhanced in muddy rivers due to interactions with naturally occurring or discharged surfactants, even in the absence of biofouling.
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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".