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Record W4388289758 · doi:10.1016/j.jobab.2023.11.001

A process insight into production of ethyl levulinate via a stepwise fractionation

2023· article· en· W4388289758 on OpenAlexvenueno aff
Yan Ma, Hongxiao Wang, Ziyang Wu, Weihong Tan, Guodong Feng, Jianchun Jiang

Bibliographic record

VenueJournal of Bioresources and Bioproducts · 2023
Typearticle
Languageen
FieldEngineering
TopicCatalysis for Biomass Conversion
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsFractionationChemistryBambooBiomass (ecology)CatalysisCelluloseMicrocrystalline celluloseEthanolOrganic chemistryBiofuelRaw materialBiotechnologyMaterials science

Abstract

fetched live from OpenAlex

Ethyl levulinate (EL) is a key biomass-derived compounds due to its socio-economic benefits for the synthesis of commodity chemicals. Herein, we proposed an efficient one-step bamboo conversion to EL in ethanol, and a novel stepwise fractionation to purify EL and lignocellulose degradation products. A proton acid, due to its high catalytic efficiency, yielded 26.65% EL in 120 min at 200 °C. The productions of ethyl glucoside and 5-ethoxymethylfurfural were analyzed in terms of by-products formation. To the best of our knowledge, there is no single report on catalyst for one step synthesis of EL directly from bamboo, as well as a stepwise fractionation to purify EL. Due to similar physiochemical properties in each fraction, the platform molecules could broaden a new paradigm of bamboo biomass utilization for renewable energy and value-added biochemicals. In addition, glucose, ethyl glucoside, corn starch, and microcrystalline cellulose were also investigated as substrates, so that the reaction intermediates of this one-pot procedure were identified and a possible reaction mechanism was 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 score0.047
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.217
Teacher spread0.210 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

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