Quantification of Random Pore Structures of Porous Adsorbents

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Abstract
The structure of pore spaces in typical catalyst particles could often be described as being “not so much fabricated as thrown together”. Thus whilst for certain materials, such as zeolites, the microstructures are well defined and have a precise geometry, most materials when used in typical particulate form are at least partly composed of chaotically configured pore spaces. These random pore structures can be important in determining an adsorbent's performance, so it is necessary to define them quantitatively. A heirarchy of approaches based upon developments from simple stochastic pore networks is described. A stochastic pore network is one in which simple pore segments form interconnecting networks within which pores can be either randomly or partly randomly distributed. Such stochastic networks can be characterised by mercury porosimetry and low-temperature gas adsorption. Interconnectivity and randomness affect the degree of hysteresis for both these techniques. For 3-D random pattern stochastic networks, it is possible to interpret sectioned SEM images using ‘random’ slices of particles subject to low melting point alloy visual porosimetry in order to arrive at measures of random pore structure. This ‘image analysis’ approach is being extended to 3-D image reconstruction of SEM sections using fractal surfaces in conjunction with randomly tortuous pores.