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Record W4303457042 · doi:10.1103/physreve.106.045202

Concept of power absorbed and lost per electron in surface-wave plasma columns and its contribution to the advanced understanding and modeling of microwave discharges

2022· article· en· W4303457042 on OpenAlexafffund
Michel Moisan, Ivan Ganachev, Helena Nowakowska

Bibliographic record

VenuePhysical review. E · 2022
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversité de Montréal
FundersUniversidad de CórdobaUniversité de MontréalNatural Sciences and Engineering Research Council of CanadaNagoya University
KeywordsElectronPlasmaAtomic physicsPhysicsMicrowaveField (mathematics)Power (physics)Quantum mechanicsMathematics

Abstract

fetched live from OpenAlex

Microwave (MW) sustained discharges have distinct advantages over other existing types of discharges in terms of the specific understanding they can provide regarding discharge phenomena and mechanisms. First, only electrons can pick up energy from the discharge E-field since ions cannot respond to rapid oscillations above ≈100 MHz. A second remarkable feature of MW discharges is that their plasma sheath is stationary, unlike in radiofrequency (rf) discharges. Furthermore, the sheath voltage is low, so that the electron energy expended to sustain them can be ignored as a first approximation. These characteristics favored the development of the concept of power per electron, which involves determining the respective roles of the power absorbed per electron θ_{A} and the power lost on a per-electron basis θ_{L} in the equilibrium relationship between them. This led to establishing the following: (i) In the equilibrium relation of the power per electron (θ_{A}=θ_{L}), the power lost has precedence over the power absorbed, the latter simply adjusting to compensate for the losses. (ii) The value of the power absorbed θ_{A}, when conforming to compensate for the losses, determines the intensity of the high-frequency E-field in the discharge, the maintenance field, construing it as an internal parameter (as opposed to an operator-set). (iii) Ensuring a smaller volume within which power is absorbed (resulting from E-field confinement) compared to the loss volume (plasma) is a way to achieve higher maintenance E-field intensity, thus higher atomic (molecular) excitation and ionization rates, as is the case, for example, with microdischarges. (iv) In pulsed-operated discharges, the E-field intensity is maximum at the very beginning of the pulse and then decreases, eventually reaching stationarity as the pulse time elapses. (v) A significant and more comprehensive similarity law is procured than for direct-current (dc) discharges. (vi) The power per electron concept is valid for all MW discharges. In the case of dc and rf discharges, where ions are also accelerated in the E-field, θ_{A} is no longer proportional to the E-field intensity: θ_{A} is then the power necessary to maintain an electron-ion pair in the discharge. It can be used, taking into account the operating conditions (field frequency, gas nature and pressure, and discharge vessel properties), to optimize the power consumed for a given plasma-driven process.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
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 head0.020
GPT teacher head0.268
Teacher spread0.248 · 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 designSimulation or modeling
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
Published2022
Admission routes2
Has abstractyes

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