Intense Pulsed Light Conversion of Anatase to Rutile TiO<sub>2</sub> for Hybrid TiO<sub>2</sub>-SnO<sub>2</sub>/MWCNTs/PVB Room Temperature VOCs Sensor
Bibliographic record
Abstract
Volatile organic compounds (VOCs) are toxic air pollutants that require cost effective and accurate sensors for environmental monitoring. A VOCs sensing device was fabricated by spin coating low quantities of TiO2-SnO2loaded multi-walled carbon nanotubes (MWCNTs) with a polyvinyl butyral (PVB) support matrix onto a quartz crystal microbalance (QCM). TiO2was partially converted from anatase to rutile phase using rapid microwave and the intense pulsed light (IPL) techniques. Microwave facilitated the drying of the solution and crystal growth while IPL enabled the conversion of TiO2from anatase to rutile. The sensing properties were investigated with different VOCs, including ethanol, methanol, isopropanol, and toluene, at different concentrations. The anatase and rutile hybrid TiO2-SnO2/MWCNTs/PVB sensing composite film showed an average of 8.8 times higher responses to VOCs compared with pure anatase TiO2-SnO2/MWCNTs/PVB composite film prepared without IPL. The hybrid sensors exhibited negative motional resistance responses to VOCs and positive motional resistance responses to non-VOCs. The hybrid nanocomposite film also showed good stability at room temperature and the highest response towards ethanol with a limit of detection of 1 ppm.
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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) | 0.000 | 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) | 0.001 | 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 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".