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Record W2921947889 · doi:10.1002/ejic.201801528

Effect of Microwave Irradiation Parameters on Co/Fe Hydrotalcite Nanocatalysts for the Total Oxidation of VOCs

2019· article· en· W2921947889 on OpenAlexfundno aff
Cynthia Abou Serhal, Isabelle Mallard, Christophe Poupin, Madona Labaki, Stéphane Siffert, Renaud Cousin

Bibliographic record

VenueEuropean Journal of Inorganic Chemistry · 2019
Typearticle
Languageen
FieldMaterials Science
TopicLayered Double Hydroxides Synthesis and Applications
Canadian institutionsnot available
FundersVlaamse regeringUniversité LibanaiseAgence Universitaire de la FrancophonieEuropean Commission
KeywordsNanomaterial-based catalystChemistryHydrotalciteCatalysisCalcinationCrystalliteX-ray photoelectron spectroscopyScanning electron microscopeTemperature-programmed reductionCoprecipitationIrradiationNuclear chemistryOxideAnalytical Chemistry (journal)Chemical engineeringInorganic chemistryOrganic chemistryCrystallographyMaterials science

Abstract

fetched live from OpenAlex

A series of Co/Fe hydrotalcite‐like samples were prepared by the traditional co‐precipitation method and treated under microwave irradiation at different temperatures, powers, and for various durations. The resulting samples have been calcined to obtain the nano‐oxide catalysts. Characterization by different physicochemical techniques including X‐ray diffraction (XRD), scanning electron microscopy (SEM), temperature programmed reduction by hydrogen (H 2 ‐TPR), and X‐ray photoelectron spectrometry (XPS) was carried out. The nanocatalysts were also tested in the total oxidation of propene. Comparing both conventional and microwave synthesis, a significant improvement in the catalytic activity was found for the samples prepared with microwave treatment. A minimum of irradiation time, power, and temperature (1 min, 40 W, and 40 °C) is enough to get higher surface area, larger pore size, smaller crystallite size, and a higher amount of reducible species than those for the non‐irradiated solid. All these factors are responsible for the enhancement of the catalytic activity.

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)0.001
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 score0.001
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.228
Teacher spread0.219 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Inorganic ChemistrySame topicLayered Double Hydroxides Synthesis and ApplicationsFrench-language works237,207