CO2 Adsorption Enhancement via Modification of Porous Materials
Notice bibliographique
Résumé
CO2 separation from flue gas streams is an essential issue as it is the main anthropogenic greenhouse gas contributing to global warming. Commercially used methods for CO2 capture includes absorption in liquid amine solutions which has its own drawbacks such as pipeline corrosion, oxidative degradation of amines, foaming in the gas-liquid interface, high energy requirement for regeneration, and high maintenance costs. To overcome these problems, adsorption onto solid adsorbents is proposed as an alternative. Although microporous activated carbons and zeolites (e.g. 5A, 13X and Faujasite) have been previously utilized in CO2 capture, their relatively low adsorption capacity as well as sensitivity to humidity can limit their usage. One of the remedies to enhance adsorption capacity of solid adsorbent is anchoring amine via amine impregnation. Additionally, new classes of porous materials called Metal Organic Frameworks (MOFs) with exceptional capture performance hold promise in this regard. In the course of the current research, firstly activated carbons were synthesized from oil sands coke which is abundantly available in Alberta. Then the synthesized microporous activated carbons were impregnated with amines and the performance of amine impregnated activated carbons for CO2 adsorption was investigated to find suitable conditions for amine impregnation and CO2 adsorption. The application of MOF materials for CO2 capture was also studied and a new method was proposed to overcome problems associated with low MOF capture capacity at atmospheric pressure and temperature. Finally, a MOF–based microwave sensor was used to monitor the adsorption progress based on the change in dielectric properties of MOF materials. The first part of this study investigated the effect of different activation agents such as KOH and MgO on porosity and capture capacity of activated carbons prepared from oil sands coke. Research findings suggested that KOH activation results in a narrow pore size distribution in micropore range, while adding MgO template provides mesoporous activated carbons with almost twice CO2 adsorption capacity. Further investigations were completed to study the effect of amine impregnation on CO2 capture enhancement of activated carbons prepared from oil sands coke. The impact of different parameters such as impregnation ratio, amine type, humidity and adsorption temperature was evaluated. The results showed that secondary amine (Diethanolamine) provided more active sites with affinity for CO2 compared to tertiary (methyl diethaonlamine) and bulky amines (tetra ethylene pentamine). There is an optimum value in amine loading which results in maximum adsorption capacity, while exceeding this point causes a decrease in adsorption capacity possibly due to the blockage of accessible volume of pores. The optimum adsorption temperature for our research was discovered to be at 50 °C. Also, the adsorption capacity of tertiary amine (MDEA in our work) was found to be improved by almost 1.6 times in the presence of 20% water vapor in feed stream compared to dry condition. In the next step, a novel MOF material combined with carbon nanotube (CNT) membrane was introduced. This study focuses on: 1) synthesis of MOF (MOF-74) and MOF-CNT using solvothermal method, 2) enhancement of MOF-CNT interfacial interaction by plasma treatment, 3) testing the MOF and MOF-CNT for carbon dioxide adsorption. The generation of new functional groups on the surface of CNT through plasma treatment provided favorable chemical affinity and stability to bridge MOF crystals and produce near-defect free MOF-membranes. Additionally, single-component CO2 adsorption isotherms showed a large increase in CO2 uptake (maximum of 10.70 mmol CO2/g) for MOF-CNT-BP samples compared to the parent Mg-MOF-74 (maximum of 3.13 mmol CO2/g). Additionally, a new MOF material (MOF-199) was integrated with a microwave resonator sensor and its performance for CO2 monitoring was compared to a commercial zeolite 13X. During the adsorption, the dielectric properties of MOF changed which could be detected by a change in resonant frequency. Despite the lower adsorption capacity of MOF-199 for low CO2 concentrations (<45 %), it showed higher sensitivity than zeolite 13X, which can be related to the initial dielectric properties of the virgin adsorbent. The ability of the sensor to monitor low concentrations of CO2 amplifies its potential in applications where information is required on the adsorbent replacement time.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».