The control of porosity at nano scale in resorcinol formaldehyde carbon aerogels

Organic aerogels were synthesized by sol–gel polymerization of resorcinol (R) with formaldehyde (F) catalyzed by sodium carbonate (C) followed by vacuum drying. The influence of the resorcinol/sodium carbonate ratio (R/C) on the porous structure of the resultant aerogels was investigated. The nitrogen adsorption–desorption measurements show that the aerogels possess a well developed porous structure and mesoporosity was found to increase with increasing the R/C ratio. Carbon aerogels were obtained by carbonization of RF aerogels. The carbonization temperature impacts the microstructure of the aerogels by pore transformations during carbonization probably due to the formation of micropores and shrinkage of the gel structure. The results showed that a temperature of 1073 Kis more effective in the development of the pore structure of the gel. Activated carbon aerogels were obtained from the CO2 activation of carbon aerogels. Activation results in an increase in the number of both micropores and mesopores, indicative of pore creation in the structure of the carbon. Activation at higher temperatures results in a higher degree of burn off and increases the pore volume and the surface area remarkably without change of the basic porous structure, pore size, and pore size distribution.

Preparation of controlled porosity carbon-aerogels for energy storage in rechargeable lithium oxygen batteries

Porous carbon aerogels are prepared by polycondensation of resorcinol and formaldehyde catalyzed by sodium carbonate followed by carbonization of the resultant aerogels in an inert atmosphere. Pore structure of carbon aerogels is adjusted by changing the molar ratio of resorcinol to catalyst during gel preparation and also pyrolysis under Ar and activation under CO2 atmosphere at different temperatures. The prepared carbons are used as active materials in fabrication of composite carbon electrodes. The electrochemical performance of the electrodes has been tested in a Li/O2 cell. Through the galvanostatic charge/discharge measurements, it is found that the cell performance (i.e. discharge capacity and discharge voltage) depends on the morphology of carbon and a combined effect of pore volume, pore size and surface area of carbon affects the storage capacity. A Li/O2 cell using the carbon with the largest pore volume (2.195cm3/g) and a wide pore size (14.23 nm) showed a specific capacity of 1290mAh g-1.

How Porosity and Permeability Vary Spatially With Grain Size, Sorting, Cement Volume, and Mineral Dissolution In Fluvial Triassic Sandstones: The Value of Geostatistics and Local Regression

Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.