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Record W2567910435 · doi:10.1038/srep40063

Laser-guided energetic discharges over large air gaps by electric-field enhanced plasma filaments

2017· article· en· W2567910435 on OpenAlex
F. Théberge, J.-F. Daigle, Jean-Claude Kieffer, François Vidal, Marc Châteauneuf

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.

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldEngineering
TopicLaser-induced spectroscopy and plasma
Canadian institutionsInstitut National de la Recherche ScientifiqueDefence Research and Development Canada
Fundersnot available
KeywordsElectric fieldPlasmaLaserAtomic physicsPlasma chemistryMaterials sciencePhysicsOpticsNuclear physics

Abstract

fetched live from OpenAlex

Recent works on plasma channels produced during the propagation of ultrashort and intense laser pulses in air demonstrated the guiding of electric discharges along the laser path. However, the short plasma lifetime limits the length of the laser-guided discharge. In this paper, the conductivity and lifetime of long plasma channels produced by ultrashort laser pulses is enhanced efficiently over many orders of magnitude by the electric field of a hybrid AC-DC high-voltage source. The AC electric pulse from a Tesla coil allowed to stimulate and maintain the highly conductive channel during few milliseconds in order to guide a subsequent 500 times more energetic discharge from a 30-kV DC source. This DC discharge was laser-guided over an air gap length of two metres, which is more than two orders of magnitude longer than the expected natural discharge length. Long plasma channel induced by laser pulses and stimulated by an external high-voltage source opens the way for wireless and efficient transportation of energetic current pulses over long air gaps and potentially for guiding lightning.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.244
Teacher spread0.237 · 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