Detection of triacetone triperoxide by thermal decomposition peroxy radical chemical amplification coupled to cavity ring-down spectroscopy
Bibliographic record
Abstract
Triacetone triperoxide (TATP) is frequently used in improvised explosive devices because of its ease of manufacture and tremendous explosive force. In this paper, we describe a new method for detection of TATP, thermal decomposition peroxy radical chemical amplification cavity ring-down spectroscopy (TD-PERCA-CRDS). In this method, air is sampled through a heated inlet to which ~ 1 ppmv nitric oxide (NO) is added. To verify the purity of synthetic standards, the mid-infrared spectrum of TATP vapor was recorded. The thermal decomposition of TATP is shown to produce radicals which oxidize NO to nitrogen dioxide (NO 2 ), whose concentration increase is monitored by optical absorption at 405 nm using a blue diode laser CRDS. The sensitivity could be improved through addition of ~ 1% ethane (C 2 H 6 ), which fuels catalytic conversion of NO to NO 2 . The limit of detection of TD-PERCA-CRDS with respect to TATP is 22 pptv (1 s data), approximately six orders of magnitude below TATP’s saturation vapor pressure. Insights into the mechanism of TATP thermal decomposition, TD-PERCA-CRDS interferences, and the suitability of TD-PERCA-CRDS as a peroxy radical explosive detection method at security check points are discussed.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".