On the Relationship between Shock and Thermal Initiating Conditions for Various Reactive Powder Mixtures
Bibliographic record
Abstract
Abstract The critical conditions for initiation of reaction by shock loading in various compositions that produce little or no gas upon reaction were investigated. Shock recovery experiments using Mn+S were first carried out in two different apparatus geometries and for two different initial sample densities. In one geometry, the sample was subjected to a planar shock followed by interactions with the confining walls. In the other geometry, a curved shock free of wall interactions was delivered to the sample. The low‐density (55 % TMD) Mn+S was found to be significantly more sensitive to the curved shock than to the planar shock with wall interactions. For high‐density (90 % TMD) Mn+S samples however, shock sensitivity was the same in both apparatuses. Next, the reaction onset temperature and the critical initiating shock pressure were determined for a number of powder mixtures using DTA and shock recovery (in the geometry producing planar shocks with interactions with the confinement walls), respectively. For the majority of the mixtures tested, the minimum shock energy required to cause the entire sample mixture to react was found to be much less than the enthalpy of the sample at its reaction onset temperature, with no significant correlation between these two parameters. The process of arrested ball‐milling, which results in a reduction of the reaction onset temperature of a mixture, may lead to an increase in shock sensitivity. Additionally, thermal sensitivity in the particular mixtures considered was not increased when they were first shock‐compacted by sub‐critical shocks.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".