MétaCan
Menu
Back to cohort
Record W2903808278 · doi:10.1002/ceat.201800260

Performance Characteristics of a Suspended‐Catalyst Oscillatory Membrane Photocatalytic Reactor

2018· article· en· W2903808278 on OpenAlexafffund
Hassan Gomaa, Rana Sabouni

Bibliographic record

VenueChemical Engineering & Technology · 2018
Typearticle
Languageen
FieldEnergy
TopicSolar-Powered Water Purification Methods
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCatalysisMembraneMembrane reactorFiltration (mathematics)Chemical engineeringPhotocatalysisSedimentationMaterials scienceSuspension (topology)Mixing (physics)Reaction rateChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The performance characteristics of an oscillatory membrane photocatalytic reactor were investigated using dye degradation over a suspended ZnO catalyst as a model reaction. Both flat‐surface membranes and ones with transverse turbulence promoters (TP) were used. Application of oscillatory motion can be effective in enhancing the performance of suspended‐catalyst membrane photocatalytic reactors. The eddy formation and vortex shedding when using membranes with TP gave rise to several synergistic effects by providing effective removal of catalyst deposits from the membrane surface, which enhanced the flux and increased the suspended‐catalyst fraction in solution, which consequently enhanced the reaction rate. The effective mixing in the reaction channel minimized particles sedimentation and agglomeration which further enhanced the catalyst suspension and increased its effective reaction area. The specific energy consumption favorably compared to a membrane cross‐flow filtration system.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueChemical Engineering & TechnologySame topicSolar-Powered Water Purification MethodsFrench-language works237,207