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TEMPO Mediated Oxidation Optimization on Thermomechanical Pulp for Paper Reinforcement and Nanomaterial Film Production

2018· article· en· W2801409544 on OpenAlexafffund
David Myja, Éric Loranger, Robert Lanouette

Bibliographic record

VenueBioResources · 2018
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSodium hypochloritePulp (tooth)CelluloseNanomaterialsMaterials scienceSodium chloritePulp and paper industryPaper productionLigninChemical engineeringHypochloriteBleachChemistryComposite materialOrganic chemistryNanotechnology

Abstract

fetched live from OpenAlex

The 4-acetamido-TEMPO mediated oxidation system is well known on pure cellulose, but further investigation on more complex cellulose sources, such as thermomechanical pulp that is also composed of hemicelluloses and lignin, is needed. The reaction on wood pulp allows improvement in paper strength and nanofibril material production. However, the effects of the reaction parameters are not known enough to scale up the oxidation. With the help of two experimental designs, the chemical amounts, reaction temperature and time, sodium hypochlorite injection time, and nanofibril dispersion time were all studied. During the experiments, it was possible to observe pulp bleaching or delignification. Increasing the 4-acetamido-TEMPO amount promoted the pulp oxidation. In contrast, a large excess of sodium bromide and sodium hypochlorite was advantageous for pulp bleaching and delignification. High temperature favored the oxidation but delignification was induced by the oxidation. For the paper reinforcement, chemical amounts were optimized according to the end user needs. For nanomaterial production, both oxidation and delignification were needed. The reaction had to generate a significant delignification and increase pulp carboxyl content higher than 1600 mmol/kg to be able to produce nanofibril material. The results showed new leads on the various times required for future industrial implementation.

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 score0.013
Threshold uncertainty score0.385

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)0.0000.000

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 head0.021
GPT teacher head0.274
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

Citations11
Published2018
Admission routes2
Has abstractyes

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