Catalytic Upgrading of Low Cost Carbon Resources Under Methane Environment
Notice bibliographique
Résumé
The heavy reliance on fossil fuels raises concerns about economic stability and environmental impact, making it desirable to find a renewable energy source that is cost competitive with traditional fuels. Catalytic conversion of low cost carbon resources such as biomass into biofuels and valuable chemicals has the potential of alleviating the dependence on fossil fuels. However, due to high oxygen content of biomass, the upgraded products are highly oxygenated and disadvantageous. The presence of oxygenated compounds, such as alcohols, carboxylic acids, phenolics, and furans, results in the products with low energy density, poor quality as well as incompatibility infrastructure. Hydrodeoxygenation is an efficient method to improve the quality of biomass-derived products by oxygen elimination. However, it requires high operating pressure and substantial consumption of expensive and unavailable hydrogen, which makes this process unpractical and economically unfeasible in a large scale. Methane, as the main component in natural gas that is an abundant natural resource present in Canada, is an ideal alternative to hydrogen for the valorization of bio-derived products. Methane (CH4) with the highest H/Ceff ratio could benefit the formation of hydrocarbon products with higher energy density and reduce the coke formation. The activation of methane can provide hydrogen atoms for the deoxygenation of oxygenated chemical compounds, and methyl moieties to form the aromatic hydrocarbons, thus improve the quality and yield of liquid products. Due to the complexity of biomass, several model compounds including ethanol, acetic acid, phenol, furfural, cellulose and lignin representing different functional groups, are selected to investigate the technical feasibility of catalytic co-conversion of bio-based compounds and methane to valuable aromatic hydrocarbons. Mechanistic investigations such as liquid and solid-state 1H, 2H and 13C NMR combined with experimental analyses evidence methane incorporation into aromatic products. Various catalyst characterizations including XRD, TEM, DRIFT, NH3-TPD, XPS, and XAS, are employed to reveal the relationship between the physicochemical properties of the catalyst and its excellent performance. The mechanistic understanding provides valuable insights into the catalytic chemistry of biomass valorization with methane, and the rational design of catalysts for cost-efficient utilizations of biomass and natural gas resources.
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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) | 0,001 | 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 ».