Continuous Monitoring of Monochloramine in Water, and Its Distinction from Free Chlorine and Dichloramine Using a Functionalized Graphene-Based Array of Chemiresistors
Why this work is in the frame
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Bibliographic record
Abstract
Monochloramine (MCA) is commonly added to drinking water as a disinfectant to prevent pathogen growth. The generation of MCA at the treatment plant requires tight control over both pH and the ratio of free chlorine (FC) to ammonia to avoid forming undesirable byproducts such as dichloramine (DCA) and trichloramine (TCA), which can impart odor and toxicity to the water. Therefore, continuous monitoring of MCA is essential to ensuring drinking water quality. Currently, standard colorimetric methods to measure MCA rely on the use of reagents and are unsuitable for online monitoring. In addition, other oxidants can interfere with MCA measurement. Here, we present a solid-state, reagent-free MCA sensing method using an array of few-layer graphene (FLG) chemiresistors. The array consists of exfoliated FLG chemiresistors functionalized with specific redox-active molecules that have differential responses to MCA, FC, and DCA over a range of concentrations. Chemometric methods were employed to separate the analytes' responses and to generate multivariate calibration for quantification. A minimum of three sensors are required in the array to maintain full functionality. The array has been demonstrated to quantify MCA in buffered and tap water as a low-cost, reagent-free approach to continuous monitoring.
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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 it