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Record W2318590132 · doi:10.1021/sc500564g

Biomass Fractionation after Denaturing Cell Walls by Glycerol Thermal Processing

2015· article· en· W2318590132 on OpenAlexaff
Wei Zhang, Justin R. Barone, Scott Renneckar

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Food and Agriculture
KeywordsCelluloseLigninBiopolymerChemistryGlycerolAnhydrousHemicelluloseXylanFractionationArabinoseXyloseStarchBiomass (ecology)PolymerChemical engineeringPolysaccharideOrganic chemistryFermentation

Abstract

fetched live from OpenAlex

Denaturing biopolymers allows the transformation of highly organized natural structures into industrially relevant materials such as extruded starch or gelatin. This approach was used to fractionate wood into its biopolymer constituents by treating wood particles in polymer processing equipment at high temperatures in the presence of anhydrous glycerol. Nine severities were studied to assess the impact of time and temperature during processing. After processing, the biomass was stripped of its lignin and xylan by subsequent extractions without addition of added catalysts, leaving a relatively pure cellulose fraction, 84% glucan, as found in chemical pulps. Additionally, 41% of the lignin and 68% of the xylan was recovered in a dry powdered form. The hemicellulose side-chain carbohydrates such as arabinose and galactose were water extracted, while the majority of the mannan remained with the cellulose fiber. High temperature processing for short times in a benign solvent provides significant disruption of the cell wall, while anhydrous glycerol prevents significant degradation of the majority of the biopolymers into oligomers.

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 score0.010
Threshold uncertainty score0.960

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 communication0.0000.001
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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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

Citations26
Published2015
Admission routes1
Has abstractyes

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