Validation and Optimization of an Effective Oxidation and Digestion Method for Isolating Microplastics from Source and Treated Drinking Water Matrices
Bibliographic record
Abstract
To-date, no method for isolating microplastics (MPs) from background organic and inorganic particles prior to analysis using Raman spectroscopy has been systematically evaluated for freshwater and treated drinking waters. In this study, seven oxidation and digestion methods which were previously presented in the literature were evaluated to compare performance when isolating MPs (> 2 μm) from tap water. Results showed that Fenton’s reaction followed by digestion using cellulase and trypsin was optimal. Subsequent trials were conducted to optimize this method by varying an acidification step as well as reducing reaction times of the oxidation and digestion steps to minimize overall processing time. Adding H2SO4 prior to commencing the Fenton reaction, instead of following its completion, and reducing the reaction time from 24 to 1 h minimized the formation of Fe(III)-organic precipitate. The optimized method was then evaluated using three different source waters to confirm its applicability and reproducibility.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".