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Record W1968721842 · doi:10.1021/jf903616y

Lignin Extraction from Straw by Ionic Liquids and Enzymatic Hydrolysis of the Cellulosic Residues

2010· article· en· W1968721842 on OpenAlexaff
Dongbao Fu, Giuseppe Mazza, Yukihiro Tamaki

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2010
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsLigninIonic liquidCelluloseChemistryStrawExtraction (chemistry)Cellulosic ethanolBiorefineryEnzymatic hydrolysisHemicelluloseCellulaseBioproductsHydrolysisLignocellulosic biomassOrganic chemistryChromatographyBiofuelRaw materialBiotechnologyCatalysisInorganic chemistry

Abstract

fetched live from OpenAlex

Lignocellulose is a promising starting material for bioproducts, ranging from biofuels to specialty chemicals; however, lignocellulose is resistant to enzymatic degradation. Overcoming this resistance is therefore an important priority for the development of the lignocellulosic biorefinery concept. In this work, 1-ethyl-3-methylimidazolium acetate ([emim]Ac) was selected from six ionic liquid candidates for the extraction of lignin from triticale and wheat straw and flax shives. Lignin extractability, composition, and cellulose enzymatic digestibility of the residues after extraction by [emim]Ac were determined at various temperatures (70-150 degrees C) and time intervals (0.5-24 h). The optimal result (52.7% of acid insoluble lignin in triticale straw) was obtained at 150 degrees C after 90 min, yielding >95% cellulose digestibility of the residue. Little cellulose was extracted, and the extracted lignin was recovered by acid precipitation. Selective extraction of lignin by ionic liquids is a potentially efficient technique for the comprehensive utilization of lignocellulose.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 source (direct Gemma or distilled Codex), 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

Citations314
Published2010
Admission routes1
Has abstractyes

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