Paper-Based, Hand-Drawn Free Chlorine Sensor with Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate)
Bibliographic record
Abstract
The concentration of free chlorine used for disinfecting drinking water, recreational water, and food processing water is critical for environmental and human health conditions, and should be controlled within stipulated ranges. This report, for the first time, describes a paper-based electrochemical free chlorine sensor fabricated by hand-drawing. The electrical resistivity of a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) chemoresistor increases when it is exposed to free chlorine in water due to oxidation reactions. Because the relative change of the electrical resistance represents the sensor's response, the sensor can be fabricated by hand-drawing with different shapes and dimensions. The fabrication steps are all at room temperature, require no instrumentation or equipment, and can be carried out by untrained personnel. The fabricated sensor is mechanically stable, reusable, has a wide sensing range, and can accurately measure free chlorine concentrations in real water samples. Therefore, the low-cost, hand-drawn free chlorine sensor is of great significance for water quality monitoring in less developed areas where fabrication facilities, analytical equipment, and trained personnel are limited, but the need for analytical devices is critical. In addition to the free chlorine sensor demonstrated in this study, other types of PEDOT:PSS-based sensors and electronic devices can be fabricated by the developed hand-drawing process.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".