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Record W2045865073 · doi:10.1088/0022-3727/33/22/312

Dissipated power in a radio-frequency discharge in oxygen

2000· article· en· W2045865073 on OpenAlexaff
Nandini Gupta, G. R. Govinda Raju

Bibliographic record

VenueJournal of Physics D Applied Physics · 2000
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRadio frequencyPower (physics)OxygenElectrical engineeringAcousticsEnvironmental scienceMaterials sciencePhysicsEngineeringThermodynamics

Abstract

fetched live from OpenAlex

Radio-frequency discharges in oxygen are widely used in plasma processes like etching and covering technologies. The manner and location in which power is dissipated in the discharge determines the character of the etch or deposition. Discrepancies between experimental values of power dissipation with theoretically predicted values as reported in the literature are the motivation for the present paper. The basic idea is to identify various sources of power dissipation in the bulk and the sheath, and use scaling relationships available from existing models to compute their contributions. It was seen that a two-temperature distribution better approximates the electron energy distribution function as opposed to a single-temperature Maxwellian. Also, at given ranges of power and pressure, ohmic heating in the pre-sheath region and not stochastic heating in the sheath region may be the predominant mechanism.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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 designTheoretical or conceptual
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

Citations2
Published2000
Admission routes1
Has abstractyes

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