Pore-filling model computer simulation

Computer Simulation of Pore-filling Model of Bojan and Steele (1998),... 

Because of its diatomic nature and permanent quadrupole moment, the physisorp-tion of nitrogen at 77 K presents special problems. The application of DFT is facilitated if the molecules are assumed to be spherical, which was the approach originally adopted by Seaton et al. (1989) and also by Lastoskie et al. (1993). The analytical procedures already outlined in Chapter 7 (Section 7.6) do not depend on the meniscus curvature and are in principle applicable to both capillary condensation and micropore filling. The non-local version of the mean field theory (NLDFT), which was used by Lastoskie, gave excellent agreement with computer simulation when applied to the carbon slit pore model. However, as pointed out earlier, these computational procedures are not entirely independent since they involve the same model parameters. 

The principal drawback of the DFT method is that it is computationally intensive relative to the classical adsorption models, although it is still much less compute-intensive than full Monte Carlo molecular simulation. A semianalytic adsorption model that retains computational efficiency while accounting for gas-solid potential interactions in micropores was originally proposed by Horvath and Kawazoe [12], In the Horvath-Kawazoe or HK method, a pore filling correlation is obtained by calculating the mean heat of adsorption (/> required to transfer an adsorbate molecule from the gas phase to the condensed phase in a slit pore of width // ... 

These authors assumed simple structures for porosity and simulated pore-filling mechanisms to create theoretical isotherms. Monte Carlo computer simulations were reported for the adsorption of argon at 90 K in different pores modeled as perfectly flat graphitic planes assembled to form rectangular cross-sections so allowing four layers of argon in the full pore (Figure 3.23). 

Fig. 2.9.13 Qu asi two-dimensional random ofthe percolation model object, (bl) Simulated site percolation cluster with a nominal porosity map of the current density magnitude relative p = 0.65. The left-hand column refers to simu- to the maximum value, j/jmaK. (b2) Expedited data and the right-hand column shows mental current density map. (cl) Simulated NMR experiments in this sample-spanning map of the velocity magnitude relative to the cluster (6x6 cm2), (al) Computer model maximum value, v/vmax. (c2) Experimental (template) for the fabrication ofthe percolation velocity map. The potential and pressure object. (a2) Proton spin density map of an gradients are aligned along the y axis, electrolyte (water + salt) filling the pore space...

The computational procedures now used in the application of density functional theory and molecular simulation for the prediction and analysis of physisorption isotherms are based on the statistical mechanics of confined fluids [14]. These important advances are described in several chapters of this book and therefore the present introductory remarks are confined to a few general comments. Whichever computational procedure is adopted [39, 40], it is first necessary to define a 3-D model of the pore structure within a sohd of known and uniform composition [14]. It has been customary to assume that the pores of different width are aU of the same shape (e.g., slits in activated carbons). Further assumptions made by many investigators are that the filling or emptying of each group of pores can occur independently and reversibly, that the internal surface is uniform and that the solid-fluid and fluid-fluid interactions can be expressed in terms of standard potential functions [14],... 

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