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Record W4400900256 · doi:10.1016/j.carbpol.2024.122529

Effect of incubation conditions of cellulase hydrolysis on mechanical pulp fibre morphology

2024· article· en· W4400900256 on OpenAlexafffund
Mariana Frias, Santiago Reynoso, Shriya Rambhia, Gloria Noki, James C. Olson, Boris Stoeber, Heather L. Trajano

Bibliographic record

VenueCarbohydrate Polymers · 2024
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaMitacsBritish Columbia Institute of TechnologyFPInnovationsBC HydroAlberta Newsprint CompanyUniversity of Victoria
KeywordsCellulasePulp (tooth)HydrolysisChemistryIncubationEnzymatic hydrolysisCellulosePulp and paper industryComposite materialMaterials scienceBiochemistry

Abstract

fetched live from OpenAlex

The mechanical pulp industry is diversifying through the manufacture of high-value paper products, such as microfibrillated cellulose. However, the development of fibre quality is still energy-intensive. Enzymatic hydrolysis is hypothesized to promote fibre cutting, greater fibrillation, and reduce refining energy costs. Despite potential benefits, there is little understanding of the mechanisms behind fibre development during enzymatic hydrolysis of mechanical pulp. This work investigates how incubation pH and temperature during enzymatic hydrolysis impact the refining of mechanical pulp short fibres. Incubation with endoglucanase at pH 5 and 60 °C increased fibre cutting by approximately 20 %. Fibrillation was negatively affected at this condition, resulting in increased slim fines formation with refining. Incubation at pH 8 and 80 °C promoted >15 % reduction in fibre length, despite such conditions being associated with low enzyme activity. The pH variation modified the sedimentation height of the fibres and the conductivity of suspensions, indicating a change in fibre surface charge. Fibre morphology changes were induced by enzyme hydrolysis conducted at conditions representative of the full range of pH and temperature observed in mechanical pulp mills.

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 score0.003
Threshold uncertainty score0.611

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)0.0010.000

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 head0.012
GPT teacher head0.294
Teacher spread0.283 · 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

Citations3
Published2024
Admission routes2
Has abstractyes

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