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Enregistrement W2594579296

Catalytic effect of MgCl2 on cellobiose decomposition in hot-compressed water

2015· article· en· W2594579296 sur OpenAlexaboutno aff
Yun Yu, Zainun Mohd Shafie, Hongwei Wu

Notice bibliographique

RevueAsia Pacific Confederation of Chemical Engineering Congress 2015: APCChE 2015, incorporating CHEMECA 2015 · 2015
Typearticle
Langueen
DomaineEngineering
ThématiqueCatalysis for Biomass Conversion
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCellobioseChemistryHydrothermal circulationDecompositionLignocellulosic biomassCelluloseCatalysisOrganic chemistryFructoseChemical engineeringCellulase
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

There is an increasing interest in producing renewable biofuels and platform chemicals from hydrothermal processing of biomass-derived sugars in hot-compressed water (HCW). Sugar monomers (i.e., glucose and fructose) are known to be good feedstock for producing platform chemicals such as 5-hydroxymethylfurfural (5-HMF) via catalytic hydrothermal processing. Unfortunately, hydrothermal depolymerisation of biomass and cellulose mainly produces sugar oligomers with various degrees of polymerization as primary products [5, 6]. Hydrothermal decomposition of these sugar oligomers are poorly understood. Cellobiose as a dimer was used as a model compound to investigate the hydrothermal decomposition of sugar oligomers in recent studies. Under non-catalytic conditions, cellobiose hydrothermal decomposition mainly proceeds via isomerization reactions to produce cellobiulose (glucosyl-fructose, GF) and glucosyl-mannose (GM), while the contribution of hydrolysis reaction is small. As biomass contains abundant alkali and alkaline earth metallic (AAEM) species, and these species are soluble in high temperature water, these water-soluble AAEM species has a large influence on biomass hydrothermal conversion. Mg2+ and Ca2+ can act as Lewis acids to catalyse cellobiose hydrothermal decomposition by promoting isomerization reactions. However, the underlying catalytic mechanism is still unclear. This extended abstract further reports a mechanistic investigation into the roles of MgCl2 on the decomposition mechanisms of cellobiose at 200-250 degreesC and a pressure of 10 MPa. A continuous reactor system was employed, similar to that used in the previous studies. A series of cellobiose solutions (2.9 mM) with various MgCl2 concentrations of 8.7-87 mM (equivalent to a salt-tocellobiose molar ratio of 1-10) were prepared for experiments. The residence time of reactant solution was adjusted by the length of the stainless tube reactor and the flow rate of mixed stream. The effluent was cooled to room temperature in an ice water bath. The liquid products were analysed by a higher performance anion exchange chromatography (Dionex ICS-5000 with CarboPac PA20 analytic and guard columns) with pulsed amperometric detection and mass spectrometry (HPAEC-PAD-MS), using various standards purchased from Sigma-Aldrich and LC Scientific Inc (Canada). The detailed procedure for the HPAEC-PAD-MS analysis can be found elsewhere [14]. Total carbon contents of selected samples were also determined by a total organic carbon (TOC) analyser (Shimadzu TOCVCPH). It has been confirmed that the gas production from cellobiose decomposition is negligible, given that a carbon balance of 100% was achieved even at high temperatures. The cellobiose conversion was found to increase (buy not linearly) with an increase in MgCl2 concentration. The initial increase is large from 0 to 14.5 mM of MgCl2 concentration (equivalent to a salt-to-cellobiose molar ratio of 5) but further increase is limited when the MgCl2 concentration increases to 29 mM (equivalent to a salt-to-cellobiose molar ratio of 10). MgCl2 promotes both isomerization and hydrolysis reactions, as the yields of GF, GM and glucose all increase with MgCl2 concentration at low temperatures (i.e., <225 degreesC). However, at increased temperatures (i.e., 250 degreesC), the disappearance of three primary products also increases with MgCl2 concentration. As the MgCl2 concentration increases from 14.5 to 29 mM, the catalytic effect of MgCl2 on cellobiose primary decomposition is limited. However, increasing MgCl2 loading still significantly affects the secondary decomposition of GF, GM and glucose, leading to their rapid disappearance. As a result, the maximal yields of GF and GM are increased but the maximal glucose yield is reduced. The selectivities of GF and GM also increase but that of glucose decreases with increasing MgCl2 concentration, suggesting the promotion effect of MgCl2 on isomerization reactions becomes stronger at higher MgCl2 concentrations. However, such promotion effects become limited when the MgCl2 concentration further increases from 14.5 to 29 mM. Unlike GF and GM which have decreasing selectivities as cellobiose conversion increases, the glucose selectivity increases as cellobiose conversion increases, albeit becomes slower at a higher MgCl2 concentration due to secondary decomposition of glucose. The rate constant of cellobiose decomposition does not increase linearly with MgCl2 concentration, suggesting that the catalytic effect is not due to Mg2+. It seems that some other species play important roles to catalyse the cellobiose hydrothermal decomposition. Further analysis was then done to calculate the concentrations of all Mg-containing ions in the MgCl2 solution at various initial concentration and temperature conditions, such as Mg2+, MgCl+ and Mg(OH)+. It is interesting to find out that the rate constant of cellobiose decomposition is linearly proportional to the Mg(OH)+ concentration at various temperatures. Such a finding is important as it clearly indicates that Mg(OH)+ is the active species to catalyse the cellobiose decomposition in HCW, particularly the isomerization reactions. The promotion of hydrolysis reaction in the MgCl2 solution is due to the increased concentration of H+ from the hydrolysis of Mg2+ at increased concentrations.

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.

Comment cette classification a été obtenuedéplier

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)0,001
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: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,125
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
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 Opus0,007
Tête enseignante GPT0,232
Écart entre enseignants0,225 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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Même revueAsia Pacific Confederation of Chemical Engineering Congress 2015: APCChE 2015, incorporating CHEMECA 2015Même sujetCatalysis for Biomass ConversionTravaux en français237 207