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Record W2978310859 · doi:10.1515/jaots-2002-0202

Destruction of Volatile Organic Compounds in Air by a Superimposed Barrier Discharge Plasma Reactor and Activated Carbon Filter Hybrid System

2002· article· en· W2978310859 on OpenAlex

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

VenueJournal of Advanced Oxidation Technologies · 2002
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsMcMaster University
Fundersnot available
KeywordsTolueneDielectric barrier dischargeNonthermal plasmaVolumetric flow ratePressure dropActivated carbonChemistryPlasmaDecompositionDrop (telecommunication)Carbon fibersAnalytical Chemistry (journal)Materials scienceChromatographyElectrodeOrganic chemistryComposite materialAdsorption

Abstract

fetched live from OpenAlex

Abstract Superimposed barrier discharge and activated carbon filter hybrid systems were used to remove toluene and TCE from air streams. The superimposed barrier-discharge consisted of silent and surface discharges. Experiments were conducted for the gas flow rates from 1 to 10 L/min, applied power from 0 to 7 W and toluene and TCE initial concentrations from 0 to 2,000 ppm for 60 Hz ac applied voltage conditions. Discharge by-products were measured by FTIR, GC, and TLV-VOC detectors. The results show that 1) the toluene-decomposition efficiency monotonically increases with increasing applied power; 2) approximately 90% of the toluene is removed by the plasma reactors and up to 98% is removed by the hybrid system; 3) TCE removal is enhanced by the hybrid system and up to 50% is removed by a discharge reactor alone; 4) the pressure drop of the reactor and carbon filter increase with increasing gas flow rate; 5) TCE is decomposed to form CO

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)0.000
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 score0.003
Threshold uncertainty score0.388

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 head0.008
GPT teacher head0.217
Teacher spread0.209 · 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