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Record W1982681297 · doi:10.2202/1542-6580.1799

Effects of Liquid and Gas Flow Rates on the Performance of a Fluidized Bed Photocatalytic Reactor

2008· article· en· W1982681297 on OpenAlexaff
Shuangshi Dong, Dandan Zhou, Xiaotao Bi

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicElectrohydrodynamics and Fluid Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFluidized bedPhotocatalysisChemical engineeringPhenolVolumetric flow rateMaterials scienceFreeboardTitanium dioxidePhotodegradationDegradation (telecommunications)CatalysisFluidizationWaste managementChromatographyChemistryOrganic chemistryComposite materialThermodynamics

Abstract

fetched live from OpenAlex

Titanium dioxide was immobilized onto spherical activated carbon particles via the sol-gel coating method. The photo-catalyst, annealed at 500 °C, was found to posses the highest activity according to the results of a bench-scale test. The photocatalytic performance of the immobilized photocatalyst was studied in a three-phase fluidized bed photoreactor, with the use of phenol as the model pollutant. Effects of both liquid and air flow rates on the phenol degradation rate were examined. The experimental results showed that the increase of liquid and air flow rates may enhance the phenol degradation rate. However, very high liquid and air flow rates could lead to the decrease in the performance of the three-phase fluidized bed photoreactor. The results on the effect of initial phenol concentration on the degradation rate indicated that the photocatalytic reaction in the three-phase fluidized bed followed the first order kinetics and could be reasonably fitted by the Langmiur-Hinshelwood kinetics model. Compared to the three-phase fluidized bed in which air is introduced into the bed from the distributor, the liquid-solids fluidized bed in which oxygen is provided by injecting air into the freeboard region of the reactor showed a better phenol destruction performance and is thus preferred for photodegradation of water contaminants.

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 score0.246
Threshold uncertainty score0.444

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)0.0000.000

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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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