Deactivated fused silica tubing: A solution for flexible time weighted averaging needle trap sampling
Bibliographic record
Abstract
In time-weighted averaging (TWA) with needle trap extraction (NTE), the control of the sampling rate is critical for accurate analysis. By adjusting the diffusion length and cross-sectional area, the sampling rate can be modified in accordance with Fick's first law of diffusion. In this study, deactivated fused silica tubing (DFST) of varying lengths was used to fine-tune these parameters, allowing for precise control of the sampling rate in TWA-NTE devices. The fabricated devices were used to extract benzene, toluene, ethylbenzene, o-xylene (BTEX), and selected alkanes as model compounds. Experimental sampling rates were obtained using a standard gas flow generating system and compared to theoretical values, showing statistical similarity. The devices were tested in various real-world environments, including a parking lot, garages, and a box containing a burning candle, and their practical applicability was confirmed. The use of DFST effectively controlled both diffusion length and cross-sectional area, thereby enhancing sampling performance. The results of this study demonstrate that DFST serves as a versatile and adjustable attachment for needle trap devices (NTD), significantly broadening the range of NTD applications in terms of concentration and sampling time. This approach not only reduces analysis costs but also improves adherence to Fick's law by minimizing the influence of other mass transfer mechanisms. Consequently, more consistent and predictable extraction behavior was observed, particularly for higher molecular weight species, strengthening the overall applicability of the TWA-NTE method. • Deactivated fused silica tubing is a feasible method to extend TWA-NTE application. • DFST-TWA-NTE enhances single needle sampling for diverse analytes and concentrations. • Deactivated tubing and Teflon plug boosts TWA-NTE flexibility and improve sampling. • DFST optimizes sampling process for enhanced efficiency. • DFST shows promise for real-world hygiene and environmental sampling.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".