Structure-transport relationships in disordered solids using integrated rate of gas sorption and mercury porosimetry

The influence of pore structure on water flow in rocks from the Beibu gulf oil field in China

“…Moreover, the mercury injection in throats always increases, but the incremental mercury injection in pores only corresponds to a narrower pressure range ( fig.2a). This means that samples of Well B have fewer pores being controlled by throats [12][13][14][15][16]. However, the mercury injection characteristics of the well W samples were different with uptake being controlled by pore bodies during early mercury injection, then as pressure increased the total mercury injection was controlled by pore throats (fig.2b).…”

Hyperpolarised xenon MRI and time-resolved X-ray computed tomography studies of structure-transport relationships in hierarchical porous media

“…Hence, it is critical to know how the individual levels in the hierarchical structure of the catalysed DPF affect mass transport. Previous work [8] has used mercury entrapped, following intrusion to different pressures, to progressively block off different ranges of pore sizes within a macro/meso-porous catalyst pellet, and then their relative importance to mass transport was assessed via comparisons of the uptake of nitrogen gas before and after their loss. However, in order to prevent contamination with mercury vapour it must be frozen in place (mpt -38.8 ºC), and thus the method is unsuitable for studying structure-transport relationships at other conditions.…”

Quantitative imaging of gas adsorption equilibrium and dynamics by X-ray computed tomography

“…the outlet of the column), the approach described above necessarily provides average properties, thereby yielding parameter values that may lump effects arising from localised phenomena within the adsorbent column (Knox James et al 2016). Deviations from the expected averaged behaviour may be due to the inherent variability of the size, shape and composition of the formulated adsorbent particles (Nepryahin et al 2016;Martin et al 2017); sorbent deactivation (Cheah et al 1994); packing heterogeneities (Johnson et al 2017); and flow maldistribution (Kwapinski et al 2004;Sharma et al 2020). Quite possibly, the two parameters that are mostly affected by these physical non-idealities are the mass and heat transfer coefficients as well as the axial dispersion coefficient, as these are often used as adjustable parameters to match the experimental breakthrough curves (Knox James et al 2016).…”