MétaCan
Menu
Back to cohort
Record W2168640154 · doi:10.1002/cjce.22167

Kinetics of liquid phase alkylation of benzene with dodecene over mordenite

2015· article· en· W2168640154 on OpenAlexvenueno aff
Waqas Aslam, Mohammad M. Hossain, M. Abdul Bari Siddiqui, Basim Abussaud, S. Al‐Khattaf

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryBenzeneAlkylationIsomerizationKineticsProtonationPhysical chemistryCatalysisActivation energyOrganic chemistry

Abstract

fetched live from OpenAlex

This paper presents the kinetics investigation of liquid phase alkylation of benzene with dodecene using mordenite having Si/Al = 20. The models are developed based on physicochemical characterization of the catalyst and a laboratory scale fixed bed reactor data. The FTIR analysis shows that approximately 90 % of the acidic sites are Brønsted acid type while the remaining 10 % are Lewis acid type. The kinetic experiments are conducted with 6:1 molar ratio of benzene to dodecene at four different temperature levels between 80 to 140 °C. The product analysis shows that the main alkylation product is 2‐phenyldodecane. At lower temperature, the concentration of dodecene isomers is significant. On the other hand at higher temperature linear alkylbenzene isomers are the dominating products. The kinetic models are formulated considering simultaneous dodecene isomerization and benzene alkylation. The reaction rate parameters are estimated by fitting of the experimental data implemented in MATLAB. The adequacy of the estimated model parameters are verified by thermodynamic consistency and statistical fitting indicators. The activation energy for protonation of 1‐dodecene to 2‐dodecene found to be significantly lower (34 kJ/mol) than that of the 2‐dodecene to 3‐dodecene reaction (51 kJ/mol). The activation energies of surface alkylations of benzene to 2‐phenyldodecane and 3‐phenyldodecane are 49 kJ/mol and 66 kJ/mol, respectively.

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 score0.010
Threshold uncertainty score0.278

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 head0.013
GPT teacher head0.208
Teacher spread0.195 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicZeolite Catalysis and SynthesisFrench-language works237,207