Zeolite simulation techniques

The configuration-bias Monte Carlo (CB-MC) technique (112) has also been extensively applied to characterize the sorption of alkanes, principally in silicalite (111, 156, 168-171) but also in other zeolites (172-174). Smit and Siepmann (111, 168) presented a thorough study of the energetics, location, and conformations of alkanes from n-butane to n-dodecane in silicalite at room temperature. A loading of infinite dilution was simulated, based on a united-atom model of the alkanes and a zeolite simulation box of 16 unit cells. Potential parameters were very similar to those used in the MD study of June et al. (85). As expected, the static properties (heat of adsorption, Henry s law coefficient) determined from the CB-MC simulations are therefore in close agreement with the values of June et al. The... 

The zeolite crystal is modeled here as a finite, two-dimensional rectangular grid of intersecting channels. The adsorption and the desorption of molecules take place at border sites only according to the characteristics of zeolites, and the diffusion of the sorbed molecules in the channels is modeled as a random walk process. The reaction occurB in sorbed phase. The simulation technique was described elsewhere [2, 3], and the simulation results are calculated as the follows ... 

Cation exchanged zeolites are successfully applied as catalysts or selective sorbents in separation technologies. " For both catalytic and sorption processes a concerted action of polarizing cations and basic oxygen atoms is important. In addition, transition metal cation embedded in zeolites exhibit peculiar redox properties because of the lower coordination in zeolite cavities compared to other supports." " Therefore, it is important to establish the strength and properties of active centers and their positions in the zeolite structure. Various experimental methods and simulation techniques have been applied to study the positions of cations in the zeolite framework and the interaction of the cations with guest molecules.Here, some of the most recent theoretical studies of cation exchanged zeolites are summarized. 

An important aspect of this study is that it has applied modeling and simulation techniques that are now routinely available. Zeolite structural chemistry includes many more complicated systems. Ongoing work is, for example, probing cation placement in zeolite X with Si Al 1.26 that entails placement of 86 cations in a unit cell of volume 15,600 A with 576... 

We shall concentrate on computational studies of the interaction between the methanol molecule and the acidic proton of the bridging (A1 0-H Si) hydroxyl group in zeolites to exemplify the contribution of simulation techniques in understanding chemical reactivity of zeolites. This interaction is the initial step of the industrially important conversion of methanol to gasoline. Therefore, understanding this primary step at the microscopic level has a direct impact on our understanding (and possibly rationalization) of the process. Before considering the results of calculations, let us outline the experimental information available for these systems. 

The adsorption behavior of diazines in X and Y zeolites has been studied by infrared spectroscopy (IR), temperature-programmed desorption (TPD), and simulation techniques. The studies showed that the interaction is determined by a donation of electron density from the nitrogen atoms of the probe molecules to the Lewis-acidic cations. The individual nature of the adsorption strongly depends on the Si/Al ratio of the zeolites, the kind of extraframework cation, and the positions of heteroatoms in the probe molecules. 

Molecular dynamics (MD) simulations have been used to simulate non-equilibrium binary diffusion in zeolites. Highly anisotropic diffusion in boggsite provides evidence in support of molecular traffic control. For mixtures in faujasite, Fickian, or transport, diffusivities have been obtained from equilibrium MD through appropriate correlation functions and used in macroscopic models to predict fluxes through zeolite membranes under co- and counterdiffusion conditions. For some systems, MD cannot access the relevant time scales for diffusion, and more appropriate simulation techniques are being developed. 

The size, location, and structure of platinum clusters in H-mordenite were modeled by molecular mechanics energy minimization and molecular dynamics simulation techniques [96G1]. It was suggested that the relative stability of monoatomic platinum sites in aluminosilicate mordenites is related to the specific aluminum insertion in T sites of the framework structure. The structural features of the platinum cluster confined to the 12-ring main channel are almost independent of the total Pt content and strongly dependent upon the surrounding zeolite structural field. 

The interactions between the extra-framework cations Na, K, and Ca and the framework of heulandite-type zeolites have been studied by using an atomistic simulation technique [98C1]. The calculations showed that the Ml (= A2) position is the most favored position for Na K, and Ca ions. Substitution of A1 at the T2 site was favored for Na cations, which is in agreement with experiments. 

Jackson and Catlow [12-13] studied the stabilities of various zeolites using the static lattice energy simulation technique. In addition, the energetic distribution of non-framework cations and the relative stabilities as a function of Si/Al ratio in faujasite, zeolite A and silicalite were also studied. Reliable interatomic potentials necessary for such calculations were derived empirically in collaboration with Sanders [14]. These potentials and related force fields commonly used in zeolite computational studies are discussed later in this section. The adsorption of various molecules in zeolites leading to... 

Before we can discuss in detail the simulation of adsorption and diffusion in zeolites using atomistic simulation we must ensure that the methods and potentials are appropriate for modelling zeolites. The work of Jackson and Catlow reviewed in the previous section shows the success of this approach. Perhaps the most critical test is to apply lattice dynamics and model the effect of temperature as any instability will cause the calculation to fail. Thus we performed free energy minimization calculations on a range of zeolites to test the methodology and applicability to zeolites. As noted in Section 2.2, the extension of the static lattice simulation technique to include the effects of pressure and temperature leading to the calculations of thermodynamic properties of crystals and the theoretical background to this technique have been outlined by Parker and Price [21], and this forms the basis of the computer code PARAPOCS [92] used for the calculations. 

The above example, the adsorption of chain molecules in the pores of a zeolite, is used to illustrate the problems that may occur if one uses conventional simulation techniques for more complex systems. Similar problems may occur in the simulation of phase equilibria of chain molecules, simulations of polymers, or liquid crystals. For many of these systems it is relatively straightforward to implement the force fields to simulate these systems however, the simulation times required to determine reliable equilibrium properties may be prohibitively long. These simulation times may even be so extreme that it cannot be expected that increasing computer power will be of any help. To be able to perform simulations on complex systems it is therefore important to develop novel algorithms that are orders of magnitude more efficient than the conventional algorithms. In this article such algorithms are discussed. 

In the previous chapter, we have focussed on adsorption of pure linear and branched cdkcines on Silicalite and found that our model is able to reproduce experimental data very well. Here, we will use the same model and simulation technique to study mixtures. In figures 5.1-5.4, the mixture isotherms of C4, C5, Cg, and C7 isomers are presented. We focus on a mixture of a linear alkane and the 2-methyl isomer with a 50%-50% mixture in the gas phase. Details about these simulations can be found in chapter 4. For all mixtures we see the following trends. At low pressure the linear and branched alkanes adsorb independently. The adsorption of the two components is proportional to the Henry coefficients of the pure components. At a total mixture loading of 4 molecules per unit cell the adsorption of the branched alkanes reaches a maximum and decreases with increasing pressure. For C5, Cg and C7 mixtures, the branched alkane is completely removed from the zeolite. The adsorption of the linear alkanes however increases with increasing pressure till saturation is reached. 

In chapter 4, we discuss the adsorption of linear and branched alkanes in the zeolite Silicalite. We have used the simulation techniques described in the previous chapters for this. Silicalite has a three dimensional channel structure which consists of straight and zigzag channels that cross at the intersections (see figures 1.1 en 4.1). To compute the adsorption behavior, we have fitted a force field which is able to reproduce the Henry coefficient (adsorption isotherm at low pressure) and the heat of adsorption. From CBMC simulations it turns out that linear alkanes can occupy all channels of Silicalite. For u-Cg en u-C/, the length of the molecule is almost identical to the length of the zigzag channel. In literature, this process is called commensurate freezing and causes an inflection in the adsorption isotherm of these molecules. This effect has also been observed experimentally. 

Many experimental and, more recently, simulation methods have been put to use to try to localise the cations in faujasite (figure 1) in different situations hydrated or dehydrated zeolites, zeolites saturated with organic molecules, e.g. benzene, toluene, xylene. The four techniques that are described below have been used in more than 90% of all published works to detect and localise extraframework cations in faujasite type zeolites. 

Molecular sieve technology, 14 82 Molecular sieve zeolites, 14 98. See also Zeolite entries processes for, 16 832t Molecular simulations complexity of, 16 747-748 sampling techniques for,... 

The five years since last considering specifically recent developments in X-ray and neutron diffraction methods for zeolites [1] have witnessed substantial progress. Some techniques, such as high resolution powder X-ray diffraction using synchrotron X-rays, have blossomed from earliest demonstrations of feasibility to widespread and productive application. Others, such as neutron powder diffraction, have shown steady progress. For still others, notably microcrystal diffraction, a variety of circumstances have contributed to extended gestation periods. Additionally, opportunities scarcely considered earlier (such as single crystal Laue diffraction, and certain developments in computer simulations that complement diffraction work) now command broad attention and warrant the commitment of substantial further investment. 

For the detailed study of reaction-transport interactions in the porous catalytic layer, the spatially 3D model computer-reconstructed washcoat section can be employed (Koci et al., 2006, 2007a). The structure of porous catalyst support is controlled in the course of washcoat preparation on two levels (i) the level of macropores, influenced by mixing of wet supporting material particles with different sizes followed by specific thermal treatment and (ii) the level of meso-/ micropores, determined by the internal nanostructure of the used materials (e.g. alumina, zeolites) and sizes of noble metal crystallites. Information about the porous structure (pore size distribution, typical sizes of particles, etc.) on the micro- and nanoscale levels can be obtained from scanning electron microscopy (SEM), transmission electron microscopy ( ), or other high-resolution imaging techniques in combination with mercury porosimetry and BET adsorption isotherm data. This information can be used in computer reconstruction of porous catalytic medium. In the reconstructed catalyst, transport (diffusion, permeation, heat conduction) and combined reaction-transport processes can be simulated on detailed level (Kosek et al., 2005). 

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