Flexible Composite Inverse Opal Fabrics for Visual Detection of BTEX Vapor
Bibliographic record
Abstract
Photonic crystal (PC) is widely used in BTEX vapor colorimetric detection due to its tunable photonic band gap, which has battery-free and signal output instrument-free advantages. Recently, responsive PC fabrics have also attracted a lot of interest. Compared to hard substrates such as glass slide and silicon wafer, these fabrics have better flexibility and portability, which can make them more widely usable. However, at present, the PC fabrics are mainly achieved by deposition of colloidal microspheres or nanosheets, which are easy to be destroyed by stretching, bending, and washing, and the dense stacked structure hinder the diffusion of vapor as well. In this study, the PEGDA inverse opal structure (IOs) with a porous structure and an ultrahigh specific area was constructed on polyester fabrics by sacrificing SiO 2 PC template of glass/SiO 2 PCs/fabric sandwich structure, and the IOs coating showed a very good bonding force with the fabrics. Benefiting from the porous structure of IOs coating, the diffusion rate of vapor was greatly increased. Besides, functional polymers and flexible MOFs were infiltrated into the IOs to selectively absorb BTEX and enhance the absorption as well, thus effectively reducing the detection limits (2.92, 1.85, 0.52, and 0.13 g/m 3 for benzene, toluene, ethylbenzene, xylene, respectively) and response speed (0.3 s for response and 0.8 s for recover), and in addition, the repeatability was good after 10 cycles. More importantly, the method to construct IOs on fabrics was universal; the IOs can be replaced with any polymer, so it is expected to be applied for the detection of other analytes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".