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Record W2732593758 · doi:10.1109/tps.2017.2716116

Compact Nanosecond Magnetic Pulse Compression Generator for High-Pressure Diffuse Plasma Generation

2017· article· en· W2732593758 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Plasma Science · 2017
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaSiemensMcGill University
KeywordsMaterials scienceNanosecondPulse generatorPlasmaVoltageGenerator (circuit theory)Pulsed powerPulse (music)OpticsOptoelectronicsElectrical engineeringPhysicsPower (physics)Laser

Abstract

fetched live from OpenAlex

We report on the development of a low-cost, adjustable high-voltage/high-power nanosecond-pulse generator for diffuse plasma generation in a high-pressure gas-discharge cell. The generator produces scalable impulsions of 0-40 kV, at an adjustable pulse-repetition frequency up to 7 kHz. Details pertaining to its working principles, electrical architecture, components, and specifications are presented. Voltage and current pulses are measured for resistive loads of 1.5 kQ to 5 MQ. The energy per pulse along with the generator's overall efficiency is presented as a function of the input voltage. A maximum value of 13.5 mJ/pulse can be delivered to a 3-kΩ load. Our preliminary investigation using a pin-to-plate geometry in air and at pressures up to 2.75 atm [280.5 kPa] demonstrates the production of uniform diffuse plasma volumes. The domain of existence of the diffuse plasma regime is briefly explored, as a function of pressure and voltage pulse amplitude.

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.

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 categoriesScience and technology studies
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 score0.217
Threshold uncertainty score0.999

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 studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.033
GPT teacher head0.293
Teacher spread0.260 · 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