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Record W2144302120 · doi:10.1109/icdl.1996.565564

Decomposition of chloroform and trichloroethylene in deionized water with the use of low voltage electron beam

2002· article· en· W2144302120 on OpenAlexaff
P. Lubicki, J.D. Cross, Shesha Jayaram

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced oxidation water treatment
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChloroformChemistryAbsorbed doseDecompositionCathode rayAnalytical Chemistry (journal)IrradiationElectronRadiochemistryMaterials scienceEnvironmental chemistryChromatographyPhysics

Abstract

fetched live from OpenAlex

Paper presents the experimental setup and the results of the laboratory scale experiment concerning a water purification by electron beam irradiation. The setup was designed to use the circulation water flow in order to control (by the time of circulation) the absorbed dose of radiation. The electron beam was generated in vacuum p=10/sup -5/ Torr, and accelerated using the voltage within the range of V=100-185 kV. Electrons were injected into the water through titanium foil with thickness d=25 /spl mu/m. The electron beam current was within the range of I=0.5-1.2 mA. Trichloroethylene (TCE) and chloroform water solutions were used in the experiment. Although the initial contents of the compounds were higher than those occurring in real water sources and during drinking water treatment, it has been found that it is possible to decompose both of the chemicals with high efficiency L total decomposition in the case of TCE, and up to 90% of reduction for chloroform- using a relatively low accelerating voltage. The dependencies of the relative contaminant concentration (c=C/C/sub 0/, where C is a weight content of compound after electron irradiation, C/sub 0/ is an initial concentration of a contaminant) on the time of water circulation, and on the absorbed dose are presented. The results have indicated that the relative removal of TCE and chloroform mainly depends on the absorbed dose of electron radiation.

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 score0.045
Threshold uncertainty score0.604

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)0.0010.000

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 head0.012
GPT teacher head0.209
Teacher spread0.197 · 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

Citations5
Published2002
Admission routes1
Has abstractyes

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