نبذة مختصرة : Over the past decades, mesoporous silica has emerged as a new material with interesting physical and chemical properties, such as high surface-to-volume ratio, stability, and the feasibility of surface functionalization, amongst others. Mesoporous silica provides an opportunity to improve conventional commercial catalyst supports, and sorbent due to its low-cost synthesis. In this research field, investigations on various materials prepared by different techniques as potential support have been reported. The main objective of the studies was to produce highly stable mesoporous materials for energy and environmental applications using simple and low-cost synthesis. In this thesis, we utilized the sol-gel and self-templating processes in synthesizing three types of highly porous silica nanomaterials, mainly aerogels (SiO2 AG), xerogel (SiO2 XG), and nanosheets (SiO2 NS). SiO2 AG and SiO2 XG were synthesized using the sol-gel method, while SiO2 NS was synthesized using the soft-templating hydrothermal technique. SiO2 AG, SiO2, XG, and SiO2 NS are explored as catalyst support for low-temperature carbon monoxide (CO) oxidation and compared to commercial Fumed Silica. The synthesized materials are investigated as metal support materials (M/SiO2) for environmental applications such as CO oxidation and carbon dioxide (CO2) adsorption. The morphology of the synthesized materials was investigated experimentally using several characterization techniques such as X-ray Diffraction (XRD), X-ray Photo-electron Spectroscopy (XPS), Transmission Electron Microscopy (TEM), Thermo-Gravimetry-Differential Scanning Calorimetry (TGA-DSC), gas adsorption by Brunauer–Emmett–Teller (BET) method, Fourier Transform Infra-Red spectroscopy (FTIR), UV-Vis spectroscopy, and Temperature Programmed Reduction (TPR) for understanding the surface chemistry of supports. The M/SiO2 was subjected to a detailed study of the morphology before, during, and after the low-temperature CO oxidation reaction under various pretreatment and reaction parameters ...
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