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Record W3104696030 · doi:10.1088/1361-6595/abc9ff

Spatio-temporal dynamics of a nanosecond pulsed microwave plasma ignited by time reversal

2020· article· en· W3104696030 on OpenAlexaff
Valentin Mazières, Romain Pascaud, Olivier Pascal, Richard Clergereaux, Luc Stafford, Simon Dap, Laurent Liard

Bibliographic record

VenuePlasma Sources Science and Technology · 2020
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsNanosecondPlasmaMicrowaveMetastabilityRise timeAtomic physicsDuty cycleWaveformPulse (music)ArgonMillimeterMaterials sciencePhysicsOpticsVoltageLaser

Abstract

fetched live from OpenAlex

Abstract In the present paper, a detailed investigation of the spatio-temporal dynamics of the recently developed time reversal microwave plasma source is presented. This novel source allows to ignite a plasma at a desired location in a reverberant cavity by focusing the electromagnetic energy in time and space. An important feature is the possibility to control the plasma position only by changing the input microwave waveform. The source is operated in a repetitive pulsed mode with very low duty cycle (typically 5 × 10 −2 %). Nanosecond pulses have rise time lower than 1 ns. The generated plasmas have typical sizes in the millimeter range and are observed using imaging for dozens of nanoseconds. The plasma behavior is investigated for different pressures and repetition frequencies. A strong dependence is observed between each discharge pulse suggesting the existence of an important memory effect. The latter is probably due to argon metastable atoms and/or residual charges remaining in the post-discharge and allowing the next breakdown to occur at a moderate electric field.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.005
GPT teacher head0.178
Teacher spread0.173 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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