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Record W2031842416 · doi:10.1088/0022-3727/35/18/308

CFC-11 destruction by microwave torch generated atmospheric-pressure nitrogen discharge

2002· article· en· W2031842416 on OpenAlexaff
Mariusz Jasi ski, J. Mizeraczyk, Z. Zakrzewski, Toshikazu Ohkubo, Jen‐Shih Chang

Bibliographic record

VenueJournal of Physics D Applied Physics · 2002
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTorchAtmospheric pressureMicrowaveNitrogenPlasma torchEnvironmental scienceMaterials scienceChemistryPlasmaMeteorologyMetallurgyGeographyEngineeringPhysicsTelecommunicationsNuclear physics

Abstract

fetched live from OpenAlex

A novel plasma method and its application for destruction of Freons using a moderate-power (several hundred watts) microwave torch discharge (MTD) in atmospheric-pressure flowing nitrogen are presented. The capability of the MTD to decompose Freons is demonstrated using a chlorofluorocarbon CCl 3 F (Freon CFC-11) as an example. The gas flow rate and microwave power (2.45 GHz) delivered to the MTD were 1–3 litre min −1 and 200–400 W, respectively. Concentration of the CFC-11 in the nitrogen was up to 50%. The results show that the decomposition efficiency of CFC-11 is up to 100% with the removal rate of several hundred g h −1 and energy efficiency of about 1 kg kWh −1 . This impressive performance, superior to that of other methods, is achieved without generating any significant unwanted by-products. As a result of this investigation, a relatively low-cost prototype system for Freon destruction based on a moderate-power MTD and a scrubber is proposed.

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 score0.001
Threshold uncertainty score0.002

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)0.0000.000

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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

Citations61
Published2002
Admission routes1
Has abstractyes

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