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Record W2047002326 · doi:10.1063/1.3686309

Experimental technique for direct observation of onset of reaction in shocked powder mixtures

2012· article· en· W2047002326 on OpenAlexaff
F. X. Jetté, Samuel Goroshin, Andrew Higgins, David L. Frost, Julian Lee

Bibliographic record

VenueAIP conference proceedings · 2012
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsDefence Research and Development CanadaMcGill University
Fundersnot available
KeywordsThermocoupleMaterials sciencePhotomultiplierNanosecondComposite materialShock (circulatory)Optical fiberPolycarbonateTemperature measurementMillisecondOpticsAnalytical Chemistry (journal)LaserChemistryChromatographyDetectorThermodynamics

Abstract

fetched live from OpenAlex

A new experimental technique was developed to directly observe the onset of shock initiation in powder mixtures contained in recovery capsules over time scales ranging from hundreds of nanoseconds to at least hundreds of milliseconds. Simultaneously with a thermocouple embedded in the test mixture to monitor bulk temperature changes, a photomultiplier tube detected light emissions produced by the reacting sample. A window/optic fiber system was developed that remained intact and did not move during the experiment. A polycarbonate window was placed into a steel recovery capsule, which was held solidly in place in a steel anvil designed to protect the fiber optic and to prevent motion of the window. Samples of as-blended 5Ti+3Si powders and ball-milled mixtures 5Ti+3Si were tested in this setup. In all experiments, a weak light emission peak was observed upon shock passage followed by much more intense light beginning a few milliseconds to a few hundreds of milliseconds later. The intense light emissions occurred at approximately the same time as a bulk temperature increase measured with the thermocouple. These results suggest that only a very small fraction of the sample was initiated by the shock.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.250
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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