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Record W2901395959 · doi:10.1002/cjce.23398

Gaseous catalytic condensation reaction of methyl propionate and formaldehyde in a fluidized bed reactor

2018· article· en· W2901395959 on OpenAlexvenueno aff
Bin Li, Xiang Qi, Ming Xie, Guangyuan Wang, Bo Wang, Le Zhang, Lihong Shen

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2018
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsnot available
FundersNatural Science Foundation of Hebei Province
KeywordsCatalysisAldol condensationFormaldehydeFluidized bedBifunctionalChemistrySelectivityReaction ratePropionateCondensationChemical engineeringNuclear chemistryMaterials scienceInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

ABSTRACT A one‐step aldol condensation reaction of methyl propionate and formaldehyde to produce methyl methacrylate is a promising environmentally sustainable strategy. In this work, the aldol condensation reaction was firstly conducted in a fluidized bed reactor using different types of catalysts. Zirconium and cesium‐loaded SiO2 and Al2O3 acid‐base bifunctional catalysts were prepared by wetness impregnation. Experimental results demonstrated the 15 % Cs‐0.05 %Zr/SiO2 (100–200 mesh) catalyst exhibited excellent catalytic performance. The effects of the supports, reaction temperature, carrier gas flow rate, and feed rate were investigated and optimized. When the flow rate of carrier gas (N2) was 280 cm3/min and the feed rate was 0.6 cm3/min, the methyl propionate conversion was 25.2 % and the methyl methacrylate selectivity could reach 86.1 %. Although the catalytic activity of the 15 %Cs‐0.05 %Zr/SiO2 catalyst dropped with reaction time on stream due to carbon deposition on the surface of catalyst, its activity was restored by a simple regeneration method.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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

Citations15
Published2018
Admission routes1
Has abstractyes

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