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Record W4401548678 · doi:10.3390/en17164001

The Role of Solar Concentrators in Photocatalytic Wastewater Treatment

2024· article· en· W4401548678 on OpenAlexaff
Joy Sankar Roy, Younès Messaddeq

Bibliographic record

VenueEnergies · 2024
Typearticle
Languageen
FieldEnergy
TopicTiO2 Photocatalysis and Solar Cells
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPhotocatalysisWastewaterWaste managementEnvironmental scienceMaterials scienceSolar energySewage treatmentEnvironmental engineeringEngineeringChemistryElectrical engineering

Abstract

fetched live from OpenAlex

The global challenge of sustainable and affordable wastewater treatment technology looms large as water pollution escalates steadily with the rapid pace of industrialization and population growth. The photocatalytic wastewater treatment is a cutting-edge and environmentally friendly technology that uses photons from light source to degrade and remove organic and inorganic contaminants from water. Thus, utilizing solar energy for photocatalytic wastewater treatment holds great promise as a renewable solution to alleviate pressures on the global water crisis. Employing solar concentrators to intensify sunlight for photocatalysis represents a promising avenue for future applications of a low-cost and rapid sustainable wastewater purification process. This groundbreaking approach will unveil fresh technological avenues for a cost-effective, sustainable, and swift wastewater purification process utilizing sunlight. This review article explores diverse solar concentrating systems and their potential applications in the wastewater treatment process.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.217
Teacher spread0.210 · 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

Citations16
Published2024
Admission routes1
Has abstractyes

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