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Enregistrement W2950131908

Tall oil production process and characterization

2017· dissertation· en· W2950131908 sur OpenAlex

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Notice bibliographique

RevueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Langueen
DomaineEngineering
ThématiqueHydrocarbon exploration and reservoir analysis
Établissements canadiensnon disponible
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaNorthern Ontario Heritage Fund Corporation
Mots-clésCharacterization (materials science)Production (economics)Process (computing)Manufacturing engineeringProcess engineeringEngineeringComputer scienceMaterials scienceEconomicsNanotechnology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Existing kraft pulp mills have seen the necessity to branch out from traditional pulp and paper products to alternative value-added products such as bioenergy and biomaterials as a result of increasing competition in the forest products industry and the need for divergence from fossil fuels. Consequently, by-products from kraft pulp mills, including tall oil from extractives and modified lignin from black liquor, have seen a rise in valorization recently.
\nIn this study, tall oil soap was received from a kraft pulp mill and transformed via acidification to crude tall oil. The reaction conditions of water content, reaction pH, reaction time, along with the application of settling additives were varied in order to determine optimized conditions. Optimized conditions without the use of settling additives were 100 wt.% H2O, pH of 2.5 ? 3.0, reaction time of 20 min, and incorporated industrially accepted values of reaction temperature (90 ? 100 ?C) and settling time (2 h).
\nWhen employing settling additives, both anionic and cationic polymers were tested. The InfinityTM PS 3040 Pulp Processing Aid was an anionic polymer with the charge density -4.73 mmol/g and a molecular weight of 7.00 x 104 g/mol. When employed at a dry basis dosage of 0.0185 wt.% (0.05 wt.% wet basis), it produced crude tall oil with a 57.1 wt.% yield and an acid number of 142 mg KOH/g oil, based on the initial amount of raw soap added. These were increased compared to crude tall oil produced with no additive with a yield of 52.9 wt.% and acid number of 137 mg KOH/g oil. The second settling additive was xylan-AETAS-APS, a cationic xylan copolymer with a charge density of 3.81 mmol/g and molecular weight of 1.26 x 105 g/mol. The yield of crude tall oil was optimized with a dry dosage of 0.01109 wt.% (0.03 wt.% wet dosage), at 53.7 wt.%. A maximum acid number of 138 mg KOH/g oil was achieved with a dry dosage of 0.00729 wt.% (0.02 wt.% wet). Finally, an H-lignin copolymer, DMC-HL10, with a cationic charge density of 3.47 mmol/g and a preliminary molecular weight of approximately 32,000 g/mol was employed. With a dry dosage of 0.0037 wt.% (0.01 wt.% wet), a crude tall oil yield of 53.1 wt.% and acid number of 136 mg KOH/g oil were produced. Ultimately, analysis of variance (ANOVA) and Statistical Package for the Social Sciences (SPSS) analysis determined that no statistical optimal conditions were present.
\nThe waste lignin from the tall oil production process was also characterized by charge density, solubility, CHNS, and molecular weight analysis, in order to determine if sulfonation with sulfuric acid during tall oil production had occurred. It was found that the anionic charge density increased from approximately 0 with unmodified kraft lignin to 0.2 ? 0.4 mmol/g depending on the production process of tall oil. There was an increase in solubility from approximately 0 g/L to over nearly 2 g/L and an increase in sulfur content from as low as 0.23 wt.% to a maximum of 2.1 wt.%. Molecular weight of tall oil lignin was found to be approximately 1,700 g/mol, i.e. lower than those of unmodified kraft lignin (up to 25,000 g/mol) and lignosulfonates (up to 150,000 g/mol). Thus, it can be inferred that sulfonated kraft lignin may be produced from waste tall oil lignin, but further studies must be conducted before determining potential implementation in industrial processes such as dispersion and flocculation.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,920
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,232
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle