Synthesis and Characterization of Polymeric Graphene Quantum Dots Based Nanocomposites for Humidity Sensing
Bibliographic record
Abstract
Graphene quantum dots (GQDs) were synthesized and incorporated with polyethylenedioxythiophene:poly(4-styrenesulfonate) (PEDOT:PSS) and carbon nanotube (CNT) to form a composite that can be used for humidity sensors. The 600 nm thick composite films contained bulk heterojunctions of CNT/GQD and CNT/PEDOT:PSS. The sensors made from the composites responded well to humidity in a range from 60 to 80% at room temperature and atmospheric pressure. With a CNT content of 0.4 wt.% (GPC-1) to 0.8 wt.% (GPC-2) and 1.2 wt.% (GPC-3), the sensitivity of the humidity sensing devices based on CNT-doped graphene quantum dot-PEDOT:PSS composites was increased from 4.5% (GPC-1) to 9.0% (GPC-1) and 11.0% (GPC-2), respectively. The fast response time of the GPC sensors was about 20 s and it was much improved due to CNTs doping in the composites. The best value of the recovery time was found to be of 40 s, for the GPC composite film doped with 1.2 wt.% CNT content.
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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".