Trace Detection of Perfluorooctanoic Acid in Water Using a Microfluidic Electrochemical Sensor with a Stand-Alone Molecularly Imprinted Polymer
Bibliographic record
Abstract
Perfluorooctanoic acid (PFOA), a persistent and highly toxic member of the PFAS family, poses grave health risks via water contamination. In this study, we present the development of a low-cost, highly selective microfluidic sensor that integrates a stand-alone molecularly imprinted polymer (MIP) membrane for the PFOA detection in water. The MIP, synthesized in situ between two sidewall electrodes, facilitates selective recognition of PFOA through hydrogen bonding and hydrophobic interactions. Chronoamperometric measurements demonstrated high sensitivity and stability, with an optimized method, realizing a detection limit of 150 ng/L—below Health Canada’s maximum allowable concentration for drinking water. Real-sample validation using municipal tap water showed good recovery (84–110%). Compared to other reported electrochemical sensors, this platform offers simplified fabrication, eliminates electrode pretreatment, and demonstrates competitive performance in real-world conditions. This work presents a promising method for on-site PFAS monitoring using a robust, portable, and low-cost sensing platform.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".