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Record W2333272809 · doi:10.1021/cs500918c

Nanocast LaNiO<sub>3</sub> Perovskites as Precursors for the Preparation of Coke-Resistant Dry Reforming Catalysts

2014· article· en· W2333272809 on OpenAlexafffund
Mahesh Muraleedharan Nair, Serge Kaliaguine, Freddy Kleitz

Bibliographic record

VenueACS Catalysis · 2014
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsCatalysisPerovskite (structure)LanioCarbon dioxide reformingMaterials scienceCokeMesoporous materialChemical engineeringHydrogenSpecific surface areaSyngasMethaneSteam reformingMesoporous silicaHydrogen productionChemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Dry reforming of methane is gaining great interest owing to the fact that this process efficiently converts two greenhouse gases (CH 4 and CO 2 ) into synthesis gas (CO + H 2 ), which can be further processed into liquid fuels and chemicals. Herein, a perovskite-derived nanostructured Ni/La 2 O 3 material is reported as an efficient and stable catalyst for this reaction. High-surface-area LaNiO 3 perovskite precursor is first synthesized by the method of nanocasting using ordered mesoporous silica SBA-15 as a hard template. The resulting nanostructured perovskite was found to possess high specific surface area as obtained from the BET method (150 m 2 g –1 ). The reduction behavior of the nanocast perovskite was monitored by performing the temperature-programmed reduction of hydrogen (TPR-H 2 ). It has been found that the complete destruction of perovskite structure occurs below 700 °C, leading to the formation of highly dispersed Ni 0 in La 2 O 3, as observed in the XRD pattern of the material after reduction. Similar behavior was observed for the LaNiO 3 perovskite synthesized using the conventional citrate process. However, the specific surface area of the former material was found to be much higher than that of the latter (50 m 2 g –1 ), which obviously resulted from the mesoporous architecture of the nanocast LaNiO 3 . It was found that the nanostructured Ni/La 2 O 3 obtained from the reduction of the nanocast LaNiO 3 exhibited high activity for the conversion of the reactant gases (CH 4 and CO 2 ) compared to the catalyst obtained from conventional perovskite, under the reaction conditions used in the present study. Particularly, no coke formation was observed for the mesoporous catalyst under the present conditions of operation, which in turn reflects the enhanced stability of the catalyst obtained from the nanocast LaNiO 3 . The improved performance of the nanostructured catalyst is attributed to the accessibility of the active sites resulting from the high specific surface area and the confinement effect leading to the stabilization of Ni nanoparticles.

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 integrity0.0000.001
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 head0.008
GPT teacher head0.247
Teacher spread0.239 · 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

Citations182
Published2014
Admission routes2
Has abstractyes

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