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Record W2047179736 · doi:10.1081/ese-200056129

Photocatalytic Treatment of Linear Alkylbenzene Sulfonate (LAS) in Water

2005· article· en· W2047179736 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Chemistry and Analysis
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotocatalysisAqueous solutionSulfonateChemistryDegradation (telecommunications)Linear alkylbenzeneWater treatmentCatalysisInorganic chemistryNuclear chemistryPulmonary surfactantEnvironmental engineeringSodiumOrganic chemistryEnvironmental science

Abstract

fetched live from OpenAlex

The photocatalytic degradation of aqueous linear alkylbenzene sulfonate (LAS) was studied. Two different photocatalysts, Degussa P25 TiO2 and Hombikat UV 100 TiO2, were used to degrade aqueous linear alkylbenzene sulfonate in slurry batch photoreactors. For a 100 mg/L LAS solution based on first-order rate constants, the optimum photocatalyst loading for Degussa P25 TiO2 was 4.0 g/L, while for Hombikat UV 100 TiO2 it was 2.0 g/L. The photoactivity of Degussa P25 TiO2 it was higher than that of Hombikat UV 100 TiO2 for the treatment of LAS. A mixture of both photocatalysts did not improve the LAS degradation rates in batch experiments. Combination of Degussa P25 TiO2 and 600 mg/L H2O2 along with irradiation with UV light at either 254 or 365 nm did not improve the LAS degradation rates over the photocatalytic or photolytic processes individually.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.093
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.278
Teacher spread0.259 · 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