MétaCan
Menu
Back to cohort
Record W3013967411 · doi:10.1021/acssuschemeng.9b07226

Enhancing Enzyme-Mediated Hydrolysis of Mechanical Pulps by Deacetylation and Delignification

2020· article· en· W3013967411 on OpenAlexafffund
Jie Wu, Richard P. Chandra, Kwang Ho Kim, Chang Soo Kim, Yunqiao Pu, Arthur J. Ragauskas, Jack Saddler

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaKorea Institute of Science and Technology
KeywordsCorn stoverChemistryLigninHemicelluloseCelluloseHydrolysisXylanStoverEnzymatic hydrolysisOrganic chemistryAdsorptionNuclear chemistryAgronomy

Abstract

fetched live from OpenAlex

Alkaline induced deacetylation of the hemicellulose combined with subsequent mechanical refining enhanced the enzyme-mediated hydrolysis of pretreated corn stover. The addition of either NaOH (80 °C) or mild KOH (25 °C) to corn stover prior to mechanical refining led to greater than 80% deacetylation with the NaOH treatment also solubilizing low-molecular-weight lignin that was enriched in β-O-4 linkages with more than 25% and 13% of the total and surface lignin removed, respectively. The influence of deacetylation and delignification were further enhanced when NaOH was supplemented with 3% Na2SO3, resulting in 100% deacetylation, 34% delignification, and a >20% increase in the hydrolysis yield of the substrate xylan. A milder KOH treatment resulted in the retention of more than 95% of the lignin within the cellulose rich, water-insoluble fraction with no apparent change in the surface lignin. However, both methods resulted in enhanced xylan hydrolysis when treated with xylanases, suggesting that deacetylation had enhanced accessibility to the xylan present in the pretreated of corn stover. It was apparent that cellulose accessibility was also enhanced by partial delignification, as NaOH treatment resulted in a 65% and 43% increase in the Water Retention Value and Directed Orange dye adsorption, respectively.

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 categoriesMeta-epidemiology (narrow)
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 score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.161
Teacher spread0.158 · 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.

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

Citations29
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueACS Sustainable Chemistry & EngineeringSame topicLignin and Wood ChemistryFrench-language works237,207