MétaCan
Menu
Back to cohort
Record W4361270356 · doi:10.1002/cjce.24900

Efficient photocatalytic removal of <scp>N‐nitrosamines</scp> from amine washing wastewater using bismuth tungstate

2023· article· en· W4361270356 on OpenAlexafffundvenue
Vasu Maddineni, Feysal M. Ali, Hussameldin Ibrahim

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Regina
KeywordsPhotocatalysisCatalysisTungstateBismuthResponse surface methodologyMaterials scienceScanning electron microscopeAmine gas treatingNuclear chemistryHydroxyl radicalCentral composite designChemical engineeringChemistryRadicalOrganic chemistryMetallurgyComposite materialChromatography

Abstract

fetched live from OpenAlex

Abstract The most mature and practical technology to reduce industrial CO 2 emissions, the main contributor to global warming, is amine‐based post‐combustion CO 2 capture. However, this results in amine degradation products that pose a threat to human health as well as marine life. To reduce the impact on human health and marine life, identifying and treating carcinogenic and mutagenic compounds like N‐nitrosamines is extremely important. Photocatalysis, in particular, an advanced oxidation process which uses a UV light source and semiconductor catalysts is studied for the degradation of organic and inorganic pollutants. N‐Nitrosodiethylamine (NDEA) is treated with strong reactive hydroxyl radicals generated by a bismuth tungstate (Bi 2 WO 6 ) semiconductor under UV/visible irradiation. The Bi 2 WO 6 was studied both in pure form and surface‐modified forms using transition metal impregnation like Ag, Fe, Cu, and La. Various catalyst characterization techniques like Brunauer–Emmett–Teller (BET), X‐ray diffraction analysis (XRD), UV–visible, and scanning electron microscopy–energy‐dispersive X‐ray (SEM‐EDS) are used to study the surface textural and morphological properties of the catalyst. Furthermore, the effect of pH of the solution, catalyst dosing, and metal impregnation (%) on the photocatalytic degradation of NDEA is analyzed. The face centred‐central composite design (FC‐CCD) experimental design method was used through response surface methodology (RSM) and optimization studies for removal of NDEA. The quadratic model was obtained as a functional link between NDEA concentration and three operation variables for all metal impregnated Bi 2 WO 6 . The results showed that the pH of the solution was the most significant factor compared to other variables like catalyst dosing and metal impregnation. The average degradation efficiency of NDEA was 89.2% for Fe‐Bi 2 WO 6 , 87.4% Ag‐Bi 2 WO 6 , 86.9% for La‐Bi 2 WO 6 , and 85% for Cu‐Bi 2 WO 6 .

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.221
Teacher spread0.208 · 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

Citations3
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicAdvanced Photocatalysis TechniquesFrench-language works237,207