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Record W2289739551 · doi:10.1002/cjce.22457

Catalytic conversion of glycerol to acrolein over MCM‐41 by the grafting of phosphorus species

2016· article· en· W2289739551 on OpenAlexvenueno aff
Tianlin Ma, Jianfei Ding, Rong Shao, Zhi Yun

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsAcroleinChemistryGlycerolCatalysisMesoporous materialAdsorptionMCM-41Nuclear chemistryPhosphoric acidPyridineBrønsted–Lowry acid–base theoryFourier transform infrared spectroscopyInorganic chemistryCalcinationOrganic chemistryChemical engineering

Abstract

fetched live from OpenAlex

Abstract The gas‐phase dehydration of aqueous glycerol to acrolein was investigated using phosphorus‐containing MCM‐41 (HP‐MCM‐41) mesoporous molecular sieves, which were prepared via impregnation of phosphoric acid on the MCM‐41. The catalysts were characterized by XRD, nitrogen adsorption‐desorption, FTIR, NH 3 ‐TPD, and pyridine‐FTIR measurements. Nitrogen adsorption studies suggested that the uniform framework of MCM‐41 remained unchanged even after grafting phosphorus species on its surface. NH 3 ‐TPD analysis confirmed that moderate acidic sites had a positive effect on the formation of acrolein. Pyridine‐FTIR results indicated that MCM‐41 with grafted phosphorus species can noticeably enhance the percentage of Brønsted acid sites. Moreover, Brønsted acid sites facilitated the production acrolein selectively confirmed by catalytic results. The effects of H 3 PO 4 loading, calcination temperature, reaction temperature, and glycerol concentrations were also examined. The optimized 25HP‐MCM‐41 catalyst showed an 84 % selectivity of acrolein with glycerol conversion of 97 % at 320 °C.

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 score0.003
Threshold uncertainty score0.353

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 head0.004
GPT teacher head0.163
Teacher spread0.159 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

Explore more

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