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Record W2080793731 · doi:10.1063/1.1784452

Effect of current rate on energy deposition into exploding metal wires in vacuum

2004· article· en· W2080793731 on OpenAlexfundno aff
G. S. Sarkisov, K.W. Struve, D. H. McDaniel

Bibliographic record

VenuePhysics of Plasmas · 2004
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsnot available
FundersNational Nuclear Security AdministrationSandia National LaboratoriesRyerson UniversityU.S. Department of Energy
KeywordsCurrent (fluid)TungstenDeposition (geology)PinchPlasmaZ-pinchNanosecondPhysicsAtomic physicsMaterials scienceMetallurgyNuclear physicsOpticsThermodynamicsLaser

Abstract

fetched live from OpenAlex

This paper presents direct experimental proof of a significant increase of energy deposition into a metal core before voltage breakdown with the current rate for nanosecond exploding wires in a vacuum. This effect is demonstrated for nine different refractory and nonrefractory metals. The strongest influence of current rate was demonstrated for tungsten wires. Increasing the current rate from 20 to 150 A/ns changes the wire core from a solid to a cluster-like state. For nonrefractory metals such as Ag, Al, Cu, and Au, fast explosion allows deposition inside a metal core 1.5–2.9 times the atomization enthalpy before voltage breakdown. The slow explosion, with 20 A/ns, gives 2–3 times less energy deposition before voltage breakdown than the fast-explosion mode. The current-rate effect is important for optimization of wire ablation, reduction of the mass left behind in the wire-array load, and final x-ray yield in modern multi-MA wire-array Z-pinch facilities.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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

Citations98
Published2004
Admission routes1
Has abstractyes

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