MétaCan
Menu
Back to cohort
Record W2331767721 · doi:10.1021/ef301717x

Investigation of the Effects of Ionic Liquid 1-Butyl-3-methylimidazolium Acetate Pretreatment and Enzymatic Hydrolysis of Typha capensis

2012· article· en· W2331767721 on OpenAlexaff
Idi Guga Audu, Nicolas Brosse, Lyne Desharnais, Sudip Kumar Rakshit

Bibliographic record

VenueEnergy & Fuels · 2012
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsLakehead University
FundersFord Foundation
KeywordsChemistryHydrolysisIonic liquidLigninSodium hydroxideEnzymatic hydrolysisHemicelluloseSulfuric acidCelluloseOrganic chemistrySolventChromatographyCatalysis

Abstract

fetched live from OpenAlex

Pretreatment of Typha capensis (TC) with ionic liquid (IL) 1-butyl-3-methylimidazolium acetate [BMIM(OAc)] shows that the structural integrity-like degree of polymerization, polydispersity index, and lignin were altered, providing easy access to enzymes, and improved its digestibility to fermentable sugars. Hydrolysis of pretreated samples by a pre-optimized mixture of cellulose enzymes achieved an optimal reducing sugar yield (RSY) of 82.4 g/100 g after 6 h of pretreatment incubation. Because the costs of ILs are high, pre-hydrolysis and recycling are used to improve the economics. Pre-hydrolysis steps using sodium hydroxide followed by IL treatment were found to be better than sulfuric acid pre-hydrolysis followed by IL. Pre-hydrolysis treatment with alkali reduced pretreatment time from 6 h to 15 min, and total solid (TS) was increased from 5 to 10% without significant reduction in the glucose and RSYs. During solvent recycling, about 10% of initial lignin at each cycle was being accumulated into the liquid stream containing the IL, with minimal traces of carbohydrates. Treatment of the recycled IL at 10th and 15th cycles enabled recovery of about 93% of the IL-soluble lignin released into the liquid stream and improved the effectiveness of pretreatment. The investigation reveals the possibility of improving IL pretreatment outcome by increasing the TS through NaOH pre-hydrolysis. With the possible recycling of the IL up to 15 cycles, the overall costs of using this procedure are considerably reduced.

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 score0.002
Threshold uncertainty score0.004

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 integrity0.0000.001
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 head0.180
Teacher spread0.174 · 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

Citations16
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueEnergy & FuelsSame topicBiofuel production and bioconversionFrench-language works237,207