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Record W3037728970 · doi:10.1088/1361-6463/ab9f69

Time and space-resolved imaging of an AC air discharge in contact with water

2020· article· en· W3037728970 on OpenAlexafffund
James J. Diamond, Ahmad Hamdan, Jacopo Profili, J. Margot

Bibliographic record

VenueJournal of Physics D Applied Physics · 2020
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAir waterSpace (punctuation)Materials scienceEnvironmental scienceChemistryPhysicsMechanicsComputer science

Abstract

fetched live from OpenAlex

Abstract Numerous physical and chemical phenomena are involved in liquid plasmas. These phenomena are highly sensitive to the plasma source and to experimental conditions. In this study, we investigate the temporal dynamics of an AC-sustained plasma produced in air by a discharge between a pin electrode and water. Depending on the gap distance (d), a discharge transition is observed at d = 4.5 mm. At d < 4.5 mm, voltage drop is observed during both positive and negative half-periods (i.e. when water is cathode and anode, respectively). Meanwhile, at d > 4.5 mm, voltage drop is observed only during the negative half-period (i.e. when water is anode). Before transition and when water is cathode, the plasma emission in the gap space consists of two components: a conical-like emission at the water surface and a cylindrical-like emission in the gap. When water is anode, strong emission is observed at the electrode pin, along with a disc-like emission at the water surface. Increasing d beyond 4.5 mm (i.e. after transition) modifies the emission structure at the water surface, forming an inner homogeneous spot at the center of an outer ring. The temporal evolution of the emission in the gap and at the water surface is also discussed, and its relationship with the injected power is assessed.

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 score0.016
Threshold uncertainty score0.422

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 head0.010
GPT teacher head0.230
Teacher spread0.221 · 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

Citations17
Published2020
Admission routes2
Has abstractyes

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