Forensic characterization of spontaneous acetone peroxide formation from consumer-aged 2-propanol
Bibliographic record
Abstract
Numerous instances of well-aged consumer-grade 2-propanol (isopropanol) containing solid primary explosive material have been reported and turned over to the authorities. Herein, one such sample that was turned over to the Bureau of Alcohol, Tobacco, Firearms and Explosives has been analytically characterized to understand the solid primary explosive material as well as the liquid composition for forensic purposes. Upon examination by several analytical methodologies, the liquid phase of the sample contained isopropanol with measurable amounts of species indicative of isopropanol degradation and precursors to triacetone triperoxide. These species included acetone, methanol, acetic acid, isopropyl acetate, hydroxy-propanone, linear acetone peroxides, several atypical linear acetone peroxides species, and cyclic acetone peroxides ( e.g., triacetone triperoxide). The solid material in the container was predominately triacetone triperoxide as well as diacetone diperoxide and tetraacetone tetraperoxide. Microscopic properties and x-ray powder diffractograms of the solid material recovered from the aged isopropanol differed from traditionally synthesized triacetone triperoxide. This comprehensive analysis serves as a reference and aid in analysis for forensic laboratories when alleged samples of spontaneously formed triacetone triperoxide are encountered.
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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 | 0.001 | 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".