Reagent-Free Quantification of Aqueous Free Chlorine via Electrical Readout of Colorimetrically Functionalized Pencil Lines
Bibliographic record
Abstract
Colorimetric methods are commonly used to quantify free chlorine in drinking water. However, these methods are not suitable for reagent-free, continuous, and autonomous applications. Here, we demonstrate how functionalization of a pencil-drawn film with phenyl-capped aniline tetramer (PCAT) can be used for quantitative electric readout of free chlorine concentrations. The functionalized film can be implemented in a simple fluidic device for continuous sensing of aqueous free chlorine concentrations. The sensor is selective to free chlorine and can undergo a reagent-free reset for further measurements. Our sensor is superior to electrochemical methods in that it does not require a reference electrode. It is capable of quantification of free chlorine in the range of 0.1-12 ppm with higher precision than colorimetric (absorptivity) methods. The interactions of PCAT with the pencil-drawn film upon exposure to hypochlorite were characterized spectroscopically. A previously reported detection mechanism relied on the measurement of a baseline shift to quantify free chlorine concentrations. The new method demonstrated here measures initial spike size upon exposure to free chlorine. It relies on a fast charge built up on the sensor film due to intermittent PCAT salt formation. It has the advantage of being significantly faster than the measurement of baseline shift, but it cannot be used to detect gradual changes in free chlorine concentration without the use of frequent reset pulses. The stability of PCAT was examined in the presence of free chlorine as a function of pH. While most ions commonly present in drinking water do not interfere with the free chlorine detection, other oxidants may contribute to the signal. Our sensor is easy to fabricate and robust, operates reagent-free, and has very low power requirements and is thus suitable for remote deployment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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 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".