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Record W2086947074 · doi:10.1002/app.26622

Removal of residual lignin of ethanol‐based organosolv pulp by an alkali extraction process

2007· article· en· W2086947074 on OpenAlexaff
Meiyun Zhang, Yongjian Xu, Kecheng Li

Bibliographic record

VenueJournal of Applied Polymer Science · 2007
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsOrganosolvKappa numberLigninPulp (tooth)Extraction (chemistry)ChemistryAlkali metalEthanolAqueous solutionMaterials scienceNuclear chemistryPulp and paper industryChromatographyChemical engineeringComposite materialOrganic chemistryKraft paperKraft processDentistry

Abstract

fetched live from OpenAlex

Abstract Organosolv pulps usually have high kappa number. This research investigated an alkaline extraction method prior to bleaching for reducing the kappa number of organosolv pulp. Ethanol wheat straw pulp with a kappa number of 58.2 was extracted with 1% NaOH solution. The results show that the ethanol pulp has a large amount of lignin particles on the fiber surface. After 1 min alkali extraction, the kappa number of the ethanol pulp is reduced by 60%, to 22.2, and both the number and the size of the lignin particles on the fiber surface are significantly reduced. In comparison with a further ethanol washing/extraction, the alkali extraction is much more effective in terms of lignin removal. X‐ray photoelectron spectroscopy results show that a thin layer of lignin remained on the fiber surface after alkli extraction, but this did not reduce the internal bond strength. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007

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)0.000
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 score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.260
Teacher spread0.252 · 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

Citations27
Published2007
Admission routes1
Has abstractyes

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