TiO<sub>2</sub> Hollow Nanofiber/Polyaniline Nanocomposites for Ammonia Detection at Room Temperature
Bibliographic record
Abstract
Abstract Ammonia (NH3) detection has gained considerable attention in agricultural and environmental monitoring, chemical and pharmaceutical processing, and disease diagnosis, which requires the development of sensors with high sensitivity. Herein, we propose a novel gas sensor based on nanocomposites of TiO2 hollow nanofibers and polyaniline (PANI) for the sensitive detection of ammonia at room temperature. TiO2 nanostructures in anatase phase were prepared by the combination of coaxial electrospinning and calcination treatment. The resulting material was mixed with PANI and deposited onto gold interdigitated electrodes (IDEs). The hybrid platforms exhibited superior sensing performance compared to the platform based on their individual phases, which is ascribed to a synergistic effect from p‐n heterojunction formation. Specifically, the platforms based on TiO2/PANI nanocomposite showed a fast response towards NH3 (e. g., 55 s at 10 ppm) at room temperature (25 °C). Additionally, the platform demonstrated the ability to detect NH3 at low concentrations (10–30 ppm) and a detection mechanism was proposed to explain the results. Overall, these results show the promise of electrospun TiO2 hollow nanofibers/PANI composites for the development of high‐performance room temperature ammonia sensors.
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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".