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Record W2275605462 · doi:10.14288/1.0059080

Isomerisation of cyclopropane in a flow reactor

2011· article· en· W2275605462 on OpenAlexaff
Brian R. Davis

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsIsomerizationCyclopropaneFlow (mathematics)ChemistryCatalysisPhysicsMechanicsOrganic chemistry

Abstract

fetched live from OpenAlex

Three aspects of the isomerization reaction of cyclopropane to propylene were explored, in order to evaluate the suitability of this rearrangement for use as a model reaction in studying the effects of pore diffusion on the rates of chemical change in porous solids. First, kinetic data for this reaction were extended from 555°C to 620°C, with good agreement being obtained with data of others at temperatures below 555°C For the results of this work, as well as for all other published results, the first order homogeneous rate constant at infinite pressure can be represented by log₁₀ k =15.38 [formula omitted] (T in degrees Kelvin) with an accuracy of ± 15% over the temperature range 470°- 620°C. Second, the isomerization was shown to proceed homogeneously in the presence of Pyrex surfaces, even with 60-fold changes in-the surface to volume ratio. Third, the only side reaction of any importance was the decomposition of propylene, which was found to be about 20-50 times slower than the cyclopropane isomerization. These results indicate that the cyclopropane reaction is a satisfactory one for the purposes of studying diffusion controlled processes, but the propylene pyrolysis may restrict the range of desirable experimental conditions.

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 score0.006

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)0.0020.000

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 head0.011
GPT teacher head0.163
Teacher spread0.151 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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