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Record W2467208031 · doi:10.1021/acs.jchemed.5b00849

Application of Heterogeneous Copper Catalyst in a Continuous Flow Process: Dehydrogenation of Cyclohexanol

2016· article· en· W2467208031 on OpenAlexaff
Marek Gliński, Urszula Ulkowska, Ewa M. Iwanek

Bibliographic record

VenueJournal of Chemical Education · 2016
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCyclohexanolDehydrogenationCalcinationCatalysisCopperChemistryEnvironmentally friendlyHeterogeneous catalysisInorganic chemistryChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

In this laboratory experiment, the synthesis of a supported solid catalyst (Cu/SiO 2 ) and its application in the dehydrogenation of cyclohexanol performed under flow conditions was studied. The experiment was planned for a group of two or three students for two 6 h long sessions. The copper catalyst was synthesized using incipient wetness impregnation of the silica support with copper(II) nitrate trihydrate as the precursor of the active phase. It was then dried, calcined, and reduced. Each step of the synthesis was characterized by color change. The catalytic reaction was performed as a continuous process in a flow reactor, and the postreaction mixture was analyzed using gas chromatography. The laboratory experiment showed practical aspects of heterogeneous catalysis and encouraged students to seek alternative, environmentally friendly methods of organic compound synthesis.

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 integrity0.0000.000
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 head0.005
GPT teacher head0.242
Teacher spread0.238 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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