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Record W2162375225 · doi:10.1002/btpr.1563

An integrated process for removing the inhibitors of the prehydrolysis liquor of kraft‐based dissolving pulp process via cationic polymer treatment

2012· article· en· W2162375225 on OpenAlexaff
Abrar Saeed, Pedram Fatehi, Yonghao Ni

Bibliographic record

VenueBiotechnology Progress · 2012
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsLakehead UniversityUniversity of New Brunswick
Fundersnot available
KeywordsDissolving pulpFurfuralChemistryCationic polymerizationAcetic acidLigninKraft paperCelluloseChitosanPulp (tooth)FlocculationKraft processPulp and paper industryOrganic chemistryPolymerChemical engineeringCatalysis

Abstract

fetched live from OpenAlex

The prehydrolysis liquor (PHL) of the kraft-based dissolving pulp production process contains various amounts of hemicelluloses that can be utilized in the production of value-added products. In this work, a new process was proposed for removing the inhibitors of PHL via employing a flocculation concept to facilitate the utilization of hemicelluloses. Lignin, lignocelluloses/cationic polymer complexes, and possibly ethanol are the main products of this process. This process has been experimentally evaluated with an industrially produced PHL and cationic polymers. The results showed that 16% of lignin, 19% of acetic acid, 43% of furfural, and insignificant amount of sugars were removed from PHL via pretreating PHL with acid and lime at pH 7. Furthermore, by adding 0.4-0.5 mg g(-1) polydiallyldimethylammonium chloride (PDADMAC) or chitosan to the pretreated PHL, 12-14% acetic acid, 40-50% furfural, 5-6% monomeric sugars, and 25% oligomeric sugars were removed from the PHL. The complexes made from these components may be applied as organic fillers in various industries. Alternatively, by adding 1.2 or 1.4 mg g(-1) PDADMAC or chitosan to the pretreated PHL, 30 or 35% of lignin was removed, respectively, which induced complexes that could be used as a fuel source. The composition of the complexes formed was also determined in this work.

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 score0.169
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.252
Teacher spread0.242 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

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