Selective on-site detection and quantification of polystyrene microplastics in water using fluorescence-tagged peptides and electrochemical impedance spectroscopy
Bibliographic record
Abstract
In this study, we developed a method for the on-site selective detection and quantification of microplastics in various water matrices using fluorescence-tagged peptides combined with electrochemical impedance spectroscopy (EIS). Among the types of plastics found in seawater, polystyrene (PS) microplastics were selected. Fluorometry, scanning electron microscopy (SEM), and Raman spectroscopy were used to verify the specific interaction of these peptides with PS spherical particles of different sizes (ranging from 0.1 to 250 µm). Principal component analysis (PCA) was employed to determine the effects of temperature (25–65 °C), incubation time (5 and 10 min), and particle size on plastic-peptide bonding efficiency, based on fluorescence intensity. For each water type (pure, tap, NaCl (0.5 M), and seawater), EIS plots (Nyquist and Bode) were generated. Significant factors affecting the EIS response, including particle size, shape, and material, were analyzed by measuring electrical parameters for different microplastic concentrations (50 ppb to 20 ppm). The EIS parameters changed with increasing plastic concentration, determining a limit of detection (LOD) of 50 ppb (ng/mL) for pure and tap water and 400 ppb for saline water, as the lowest concentration producing a significant change in EIS parameters compared to the baseline. The sensor proved highly effective for detecting microplastics in low ionic strength environments such as pure and tap water. However, in high ionic strength environments like saline and seawater, the detection capability diminished, likely due to the masking effect of ions on the EIS response. • Developed a method for on-site detection of microplastics using EIS and peptide sensors. • Verified peptide-microplastic interactions using fluorometry, SEM, and Raman spectroscopy. • PCA analyzed the effect of temperature, incubation time, and particle size on bonding efficiency. • Determined detection limits: 50 ppb for pure/tap water, 400 ppb for salty water. • Sensor effective for various microplastics in different water types, despite ionic strength variations.
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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 | 0.000 |
| 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 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".