Modeling Diffusion of Linear Hydrocarbons in Silica Zeolite LTA Using Transition Path Sampling

Abstract

The diffusivities of linear hydrocarbons (CH 4 , C 2 H 6 , C 2 H 4 , C 3 H 8 , C 3 H 6 , and C 4 H 10 ) in pure silica zeolite LTA (ITQ-29) are computed at 300 K and infinite dilution. To overcome the time scale problem arising from the slow diffusion process at room temperature, we used transition path sampling (TPS). The influence of framework flexibility on diffusion is investigated by combining TPS simulations with fully flexible molecular dynamics performed in the NpT ensemble. The ensemble of the collected reactive trajectories was used to characterize sets of transition states, and the corresponding configurations were analyzed to construct window size distributions during the molecular hopping events. The diffusion process is affected by framework flexibility, and the influence of framework flexibility on diffusion of propane and butane is much larger than for methane and ethane.

Enzymatic Kinetic Isotope Effects from First-Principles Path Sampling Calculations

“…The distribution of the order parameter in the windows W [ i ] is then calculated separately, $$Pfalse(\lambda ,t;ifalse)=\frac{false\int \mathrm{normald}{x}_0\rho false(x_{0}false)h_{\mathrm{R}}false(x_{0}false)h_{Wfalse[ifalse]}false(x_{t}false)\delta false[\lambda -\lambda false(x_{t}false)false]}{false\int \mathrm{normald}{x}_0\rho false(x_{0}false)h_{\mathrm{R}}false(x_{0}false)h_{Wfalse[ifalse]}false(x_{t}false)}$$ The full distribution function P (λ, t ) can then be obtained by matching the individual histograms P (λ, t;i ), using the overlapping regions of each window W [ i ] where available, to refine the matching. The correlation function can then be calculated by integration of the product region of this full histogram: $$Cfalse(t\prime false)={\int }_{{\lambda }_{\text{min}}}^{{\lambda }_{\text{max}}}\mathrm{normald}\lambda Pfalse(\lambda ,tfalse)$$ Variations of this method have previously been used to calculate rates in simpler systems; combined with umbrella sampling, it has been used to calculate the rate of sodium chloride dissociation at air–water 48 and organic–aqueous interfaces, 49 the rate of diffusion of hydrocarbons in a silica zeolite, 50 and the component of mechanical stress in the base-catalyzed hydrolysis of tetraglycine. 51 …”

Improved Hill–Sauer Force Field for Accurate Description of Pores in 8-Ring Zeolites

“…Hill and Sauer [17][18] developed one of the most widely used force fields for the simulation of pure silica zeolites. It is often used to compute properties of zeolites ranging from the simulation of diffusion process with flexible frameworks 2,[11][12][29][30] to spectroscopic and vibrational studies of zeolite materials 14,31 . Figure 2 shows the window size distribution in pure silica LTA computed using the HillSauer force field and also from first principles molecular dynamics at the DFT level using the PBE functional.…”

“…Molecular diffusion provides an example of this kind of problem. Although approximate methods exist that neglect coupling between diffusing molecules and flexible frameworks 11, 54-55 , quantitatively predicting the diffusion rates of molecules that are complex or large relative to pore openings intrinsically involves an interplay between molecules near pore mouths and deformations of the pores induced by these molecules 12,53 . Calculations based on classical force fields are well suited to analyze this situation.…”

“…Experiments and simulations[1][2][11][12] have shown that the minimum free diameter of the window in 8-ring zeolites is a critical dimension for important processes such as diffusion. Here, we define the minimal window size distribution as the ensemble average of the shortest O-O distance for each 8-ring window,…”

Methane decomposition for carbon nanotube production: Optimization of the reaction parameters using response surface methodology

“…One of the most important factors for selecting a precursor is its molecular structure. It has been reported that linear hydrocarbons (Boulfelfel et al, 2015) such as ethylene, methane, and acetylene decompose and convert into linear dimers/trimers of carbon by heat, and, therefore, result in straight hollow CNTs. In contrast, cyclic hydrocarbons such as xylene, benzene, cyclohexane, and fullerene yield semi-curved CNTs (Morjan et al, 2004).…”