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Record W2258601094 · doi:10.1021/acssuschemeng.5b01098

Effects of Reaction Parameters on the Glycidyl Etherification of Bark Extractives during Bioepoxy Resin Synthesis

2016· article· en· W2258601094 on OpenAlexafffund
Pei‐Yu Kuo, Luizmar de Assis Barros, Mohini Sain, Jimi Tjong, Ning Yan

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2016
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsEpichlorohydrinSodium hydroxideChemistryYield (engineering)EpoxyReactivity (psychology)MonomerCatalysisOrganic chemistryBark (sound)HydrolysisPolymer chemistryNuclear chemistryMaterials sciencePolymerComposite material

Abstract

fetched live from OpenAlex

This study outlines the influence of a series of reaction conditions on the yield and reactivity of the glycidyl etherification reaction of the bark extractive-based bioepoxy monomer (E-epoxy). To maximize the yield and epoxy content, the glycidylation reaction was examined with various substrates, solvents, catalysts, time periods, reaction temperatures, and sodium hydroxide/hydroxyl (NaOH/OHV) ratios. Spray-dried bark extractives were used as substrates due to their higher hydroxyl group content and lower molecular weight compared to the oven-dried bark extractives. A dioxane/water combination was selected from among four solvents based on the yield and epoxy equivalent weights of the final product, and tetrabutylammonium hydroxide was chosen as a ring-opening catalyst due to its effect of suppressing hydrolysis. Furthermore, a response surface methodology was applied to find the optimal reaction time, reaction temperature, and NaOH/OHV ratio of the E-epoxy monomer. The maximum extent of conversion with minimum epoxy equivalent weight was achieved after 4.5 h with an NaOH/OHV ratio of 3.4 at 80 °C. This work identifies the effects of reaction parameters on the yield and reactivity of E-epoxy and sheds new light on the glycidylation reaction between epichlorohydrin and renewable biomass.

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 score0.003
Threshold uncertainty score0.692

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 head0.003
GPT teacher head0.162
Teacher spread0.159 · 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

Citations27
Published2016
Admission routes2
Has abstractyes

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