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Record W2508370869 · doi:10.1021/acssuschemeng.5b00098

Production of Water-Soluble Hardwood Kraft Lignin via Sulfomethylation Using Formaldehyde and Sodium Sulfite

2015· article· en· W2508370869 on OpenAlexafffund
Mohan K.R. Konduri, Pedram Fatehi

Bibliographic record

VenueACS Sustainable Chemistry & Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsLakehead University
FundersFPInnovationsNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for Innovation
KeywordsLigninChemistrySodium sulfiteKraft processKraft paperBlack liquorHardwoodSulfiteFormaldehydeLignosulfonatesOrganic chemistryPulp and paper industrySodiumBotany

Abstract

fetched live from OpenAlex

Kraft lignin can be extracted from black liquor (i.e., spent liquor) of a kraft pulping process to produce value-added chemicals, but its limited water solubility hampers its end-use applications. The main objective of this study was to investigate the sulfomethylation of kraft lignin to produce water-soluble kraft lignin with an anionic charge density. In this work, hardwood kraft lignin was modified with formaldehyde and sodium sulfite under alkali conditions. The optimum conditions for sulfomethylation were 0.5 M NaOH (aq), 0.9 mol/mol sodium hydroxymethyl sulfonate/lignin at 100 °C for 3 h, and 20 g/L lignin concentration. The resulting lignin had a charge density of −1.60 mequiv/g and sulfonate group content of 1.48 mmol/g. The molecular weight, structure, thermal behavior, and elemental analyses of the product were also assessed. The modified lignin was used as a cement dispersant, and the dispersibility of cement was increased from 60 to 155 mm by adding 1.2 wt % of sulfomethylated lignin to cement. Unmodified lignin did not change the dispersibility of cement.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.189
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations128
Published2015
Admission routes2
Has abstractyes

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Same venueACS Sustainable Chemistry & EngineeringSame topicLignin and Wood ChemistryFrench-language works237,207