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Record W2115273247 · doi:10.2166/wst.2009.640

Design and study of a cost-effective solar photoreactor for pesticide removal from water

2009· article· en· W2115273247 on OpenAlexfundno aff
Patrick Athéba, Didier Robert, Albert Trokourey, Drissa Bamba, Jean‐Victor Weber

Bibliographic record

VenueWater Science & Technology · 2009
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsnot available
FundersAgence Universitaire de la Francophonie
KeywordsPhotocatalysisMineralization (soil science)PesticideChemistryKineticsPesticide degradationDegradation (telecommunications)Environmental chemistryWater treatmentEnvironmental scienceChemical engineeringPulp and paper industryEnvironmental engineeringCatalysisOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

In order to remove pesticides from water, a basic photoreactor has been built. We evaluated the performance of this photoreactor using two commercial photocatalytic materials from Ahlstrom group and from Saint-Gobain, with solar and artificial UV-lamps. We compared the kinetics of photocatalytic degradation and mineralization of Diuron in the same reactor with of both photocatalyst supports. We showed that Diuron is easily degraded under solar or artificial irradiation, while the kinetics of mineralization in the same condition are very slow. The behaviour of these commercial materials has been studied after several uses in the same conditions. We showed the effectiveness of this basic and cheap photoreactor for the elimination of pesticide in water.

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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.255
Teacher spread0.239 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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