Comparative study of acid- and alkali-catalyzed 1,4-butanediol pretreatment for co-production of fermentable sugars and value-added lignin compounds
Notice bibliographique
Résumé
BACKGROUND: Organosolv pretreatment is one of the most efficient methods for delignification and boosting biomass saccharification. As compared to typical ethanol organosolv pretreatments, 1,4-butanediol (BDO) organosolv pretreatment is a high-boiling-point solvent pretreatment, which can generate low pressure in the reactor during high temperature cooking that improves the operation safety. Although several studies showed that organosolv pretreatment can lead to effective delignification and enhancement in glucan hydrolysis, there has been no studies on acid- and alkali-catalyzed BDO pretreatment, as well as their comparison on promoting biomass saccharification and lignin utilization. RESULTS: It was shown that BDO organosolv pretreatment was more effective in removing lignin from poplar as compared with typical ethanol organosolv pretreatment under the same pretreatment conditions. HCl-BDO pretreatment with 40 mM acid loading led to 82.04% of original lignin removed from biomass, as compared to the lignin removal of 59.66% in HCl-Ethanol pretreatment. Besides, acid-catalyzed BDO pretreatment was more effective in improving the enzymatic digestibility of poplar than alkali-catalyzed BDO pretreatment. As a result, HCl-BDO with acid loading of 40 mM provided a good enzymatic digestibility of cellulose (91.16%) and the maximum sugar yield of 79.41% from original woody biomass. The linear correlations between physicochemical structure (e.g., fiber swelling, cellulose crystallinity, crystallite size, surface lignin coverage and cellulose accessibility) changes of BDO pretreated poplar and enzymatic hydrolysis were plotted to figure out the main factors that influenced biomass saccharification. Moreover, acid-catalyzed BDO pretreatment mainly brought about the phenolic hydroxyl (PhOH) groups formation in lignin structure, while alkali-catalyzed BDO pretreatment mostly led to the lower molecular weight of lignin. CONCLUSIONS: Results indicated that the acid-catalyzed BDO organosolv pretreatment could significantly improve enzymatic digestibility of the highly recalcitrant woody biomass. The great enzymatic hydrolysis of glucan resulted from increased cellulose accessibility, which mostly associated with the higher degree of delignification and hemicellulose solubilization, as well as the more increase in fiber swelling. Besides, lignin was recovered from the organic solvent, which could be used as natural antioxidants. The formation of phenolic hydroxyl groups in lignin structure and the lower molecular weight of lignin contributed to its greater radical scavenging capacity.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».