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Record W2979818675 · doi:10.3390/catal9100851

Application of Phase Transfer Catalysis in the Esterification of Organic Acids: The Primary Products from Ring Hydrocarbon Oxidation Processes

2019· article· en· W2979818675 on OpenAlexaff
Hui Wang, Hongfei Lin, Xiaohu Li, Rui Ren, Jianglong Pu, Haiping Zhang, Ying Zheng, Jianshe Zhao, Siauw Ng, Hui Zhang

Bibliographic record

VenueCatalysts · 2019
Typearticle
Languageen
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsWestern UniversityUniversity of New Brunswick
Fundersnot available
KeywordsBenzoic acidChemistryCatalysisPhthalic acidAdipic acidOrganic chemistryCetane numberRing (chemistry)Diesel fuelBiodiesel

Abstract

fetched live from OpenAlex

For enhancing the cetane number (CN) of diesel fraction, the selective oxidative ring opening method was applied to upgrade ring hydrocarbons. Organic acids, one of the main products from this oxidative reaction, being esterified by the phase transfer catalysis (PTC) approach were studied. Adipic acid, benzoic acid, and phthalic acid were used as model compounds. Reaction time, reaction temperature, the amount of water, and the amount of catalyst in the esterification process were investigated and optimized using orthogonal experimental design method. The kinetics of esterification process was then conducted under the optimal condition. The types of catalysts and organic acids, the amount of catalyst and water were also investigated. The PTC esterification was one rate controlling reaction on the interface between the aqueous phase and the oil phase. Hydrophobicity is a key factor for converting benzoic acid, adipic acid, and phthalic acid to the corresponding esters. It was found that around 5–8% water is the optimal quantity for the given reaction system. Two cases of esterification processes of PTC were proposed.

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 score0.017
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.210
Teacher spread0.202 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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