Aging of Polystyrene Micro/Nanoplastics Enhances Cephalosporin Phototransformation via Structure-Sensitive Interfacial Hydrogen Bonding
Bibliographic record
Abstract
Beyond their roles in adsorbing and transporting pollutants, microplastics (MPs) and nanoplastics (NPs), particularly polystyrene variants (PS-M/NPs), have emerged as potential accelerators for the transformation of coexisting contaminants. This study uncovered a novel environmental phenomenon induced by aged PS-M/NPs and delved into the underlying mechanisms. Our findings revealed that the aged PS-M/NP particles significantly amplified the photodegradation of common cephalosporin antibiotics, and the extent of enhancement was tightly correlated to the molecular structures of cephalosporin antibiotics. Notably, the results confirmed that the hydroxyl radical (OH•) acted as the primary agent to drive the accelerated degradation. Furthermore, in-depth analysis utilizing in situ Fourier transform infrared spectroscopy, batch adsorption experiments, and theoretical calculations underscored that the structure-dependent enhancement stemmed from the specific hydrogen bonding sites, rather than mere adsorption capacity. Specifically, the −OOH group (hydroperoxyl group) on the PS surface exhibited a greater potential to generate OH• compared to the −OH group. Therefore, cephalosporins that formed hydrogen bonds with −OOH moieties on the aged PS surfaces, as opposed to −OH, would experience a more pronounced degradation enhancement. Thus, the unique interaction pattern between contaminants and PS-M/NPs transforms aged PS into a selective reactor, facilitating the targeted degradation of pharmaceuticals in aquatic ecosystems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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 teacher head, 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".