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Record W2590717530 · doi:10.21967/jbb.v2i1.103

Integration of hemicellulose recovery and cold caustic extraction in upgrading a paper-grade bleached kraft pulp to a dissolving grade

2017· article· en· W2590717530 on OpenAlexvenueno aff
Chen Gong, Yu Shi, Jianping Ni, Xiaobo Yang, Yan-Zhao Liu, Chao Tian

Bibliographic record

VenueJournal of Bioresources and Bioproducts · 2017
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsDissolving pulpHemicellulosePulp and paper industryPulp (tooth)Kraft paperKraft processCelluloseKappa numberDissolutionChemistrySoda pulpingCaustic (mathematics)Extraction (chemistry)SoftwoodChromatographyMaterials scienceOrganic chemistryMathematicsEngineeringDentistry

Abstract

fetched live from OpenAlex

In this study, a hemicellulose recovery process was integrated with a cold caustic extraction (CCE) process in upgrading paper-grade bleached kraft pulp to dissolving grade. Under the conditions of 15% NaOH, 10% pulp consistency, 30℃ and 1 h, a paper-grade softwood bleached kraft pulp was purified to a dissolving-grade pulp with 97.57% α-cellulose and 1.67% pentosan contents. The spent liquor from the cold caustic extraction process was sequentially extracted with ethanol to precipitate and recover the dissolved hemicelluloses, followed by evaporation to recover the ethanol. After the recovery of hemicelluloses and ethanol, the spent liquor can be reused as the caustic solution for the CCE process without compromising the resulting pulp properties. The results demonstrated that it is feasible to integrate hemicellulose production with the cold caustic extraction process of dissolving pulp production, based on the concept of biorefinery.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.025
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.032
GPT teacher head0.311
Teacher spread0.279 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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