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Record W1969661058 · doi:10.2202/1542-6580.2100

A Study of Direct Hydration of Dihydromyrcene to Dihydromyrcenol Using Cation Exchange Resins as Catalyst

2010· article· en· W1969661058 on OpenAlexaff
Yong Liu, Zheng Zhou, Gaodong Yang, Youting Wu, Zhibing Zhang

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2010
Typearticle
Languageen
FieldChemistry
TopicZeolite Catalysis and Synthesis
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsCatalysisSolventActivation energyBatch reactorKineticsChemistryReaction rateReaction rate constantChemical kineticsMolar ratioIon-exchange resinAtmospheric temperature rangeChemical engineeringInorganic chemistryThermodynamicsPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A study of direct hydration of dihydromyrcene (DHM) with H2O to produce dihydromyrcenol (DHMOH) has been carried out using cation exchange resins as catalysts in a batch stirred-tank reactor. The effect of different parameters such as agitating speed, catalyst type, catalyst loading, molar ratio of the reactants and solvent, temperature and solvent on the conversion of DHM were investigated to obtain the optimal conditions of the reaction. The kinetics of hydration process was studied in the temperature range from 333.15 K to 353.15 K. A pseudo-homogeneous kinetics model was used to explain the reaction rate and the reaction rate constants and the reaction activation energy were determined.

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)0.001
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 score0.001
Threshold uncertainty score0.591

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.266
Teacher spread0.253 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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