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Record W2768892807 · doi:10.1002/cjce.23083

Eco‐friendly synthesis from industrial wastewater of Fe and Cu nanoparticles over NaX zeolite and activity in 4‐nitrophenol reduction

2017· article· en· W2768892807 on OpenAlexaffvenue
Amal Elfiad, Daria C. Boffito, Sihem Khemassia, Federico Galli, Salah Chegrouche, Laâldja Meddour‐Boukhobza

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsZeoliteAdsorptionWastewaterNuclear chemistryIndustrial wastewater treatmentCopperMetalEffluentChemistryMaterials scienceInorganic chemistryCatalysisMetallurgyWaste managementOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract We deposited Fe and Cu over zeolite NaX (Fe/NaX and Cu/NaX) by adsorption from effluent industrial wastewater. We synthesized the zeolite NaX by the hydrothermal method. 5 g of NaX completely adsorbed 350 and 380 mg of Fe and Cu from the industrial wastewater, respectively, in 6 h. The distribution of Fe and Cu over the NaX was uniform and amounted at 14 and 18 mass%, respectively. Fe and Cu modify the morphology of the NaX zeolite: the particle size increased from 9 μm to 10 μm for the former and decreased to 3 μm for the latter. Fe/NaX and Cu/NaX are less crystalline than NaX. BET analysis showed that the specific surface area decreased by 30 % and 50 % compared to NaX for Fe/NaX and Cu/NaX, but the ratio between meso‐ and micropores increased by 7 and 13 times, respectively. Fe/NaX and Cu/NaX synthesized by adsorption from industrial wastewater reduced +99 % of 4‐p‐nitrophenol to 4‐aminophenol in less than 100 s, which is comparable to noble metal.

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 score0.009
Threshold uncertainty score0.998

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 head0.014
GPT teacher head0.200
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

Citations15
Published2017
Admission routes2
Has abstractyes

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