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Record W2466527199 · doi:10.1002/cjce.22563

Decomposition of cyclohexyl hydroperoxide over bimetallic mesoporous materials containing cobalt and chromium

2016· article· en· W2466527199 on OpenAlexvenueno aff
Lixia Li, Zhaowei Wu, Lulu Guo, Xia Yuan

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersNatural Science Foundation of Hunan ProvinceNational Natural Science Foundation of China
KeywordsBimetallic stripCatalysisCobaltDecompositionCyclohexanolChromiumCyclohexanoneMesoporous materialTriethanolamineChemistryHydrothermal circulationMesoporous silicaInorganic chemistryMaterials scienceChemical engineeringOrganic chemistryAnalytical Chemistry (journal)

Abstract

fetched live from OpenAlex

Abstract Bimetallic mesoporous Co‐Cr‐TUD‐1 and its counterparts Co‐TUD‐1 and Cr‐TUD‐1 were synthesized by a direct hydrothermal treatment (DHT) method with triethanolamine as a template. The products were characterized by many techniques. Results show that Co and Cr are incorporated into the framework of TUD‐1. The catalytic behaviours of the samples were tested in decomposition of cyclohexyl hydroperoxide (CHHP). Co‐Cr‐TUD‐1 (Si/(Co + Cr) = 25) shows the highest catalytic efficiency with a CHHP conversion of 96.9 % and total selectivity of cyclohexanone and cyclohexanol of 95.9 %, which outperforms Co‐TUD‐1 and Cr‐TUD‐1 and indicates a synergistic effect between Co and Cr in Co‐Cr‐TUD‐1. The catalysts are mainly heterogeneous as shown in various experiments, while the catalytic performances of recovered catalysts declined modestly, indicating non‐negligible amounts of Co and Cr are leached after some cycles.

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 score0.002

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 integrity0.0000.000
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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

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