Diffusion of n-paraffins in offretite-erionite type zeolites

Cavalcante, Célio L.; Eić, Mladen; Ruthven, Douglas M.; Occelli, Mario L.

doi:10.1016/0144-2449(94)00061-v

Cited by 58 publications

(46 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 9. Diffusion coefficients as a function of chain length at various temperatures in ERI-type zeolite: (a) silica simulation results; (b) experimental results of Gorring on a potassium-exchanged OFF/ERI intergrowth, 2 Cavalcante et al, 12 and Magalhães et al 13 Error bars on the simulation data are only shown when larger than the symbol size.…”

Section: Resultsmentioning

confidence: 99%

“…We note that the maximum in the frequency factor corresponds to the minimum of the activation energy and the maximum in the diffusion constant. 2 Cavalcante et al, 12 and Magalhães et al 13 Error bars on the simulation data are only shown when larger than the symbol size.…”

Section: Resultsmentioning

confidence: 99%

“…We note that the original cracking data of Chen was performed using H-ERI. The actual samples used by Gorring 2 , Cavalcante et al, 12 and Magalhães et al were rather different in composition of cations and intergrowth ratio. However, in some forms of the ERI-type zeolite 48 and the Ca/ Na form of the LTA-type zeolite, 40 the ions are known to be located in the cages and not in the windows.…”

Section: The Window Effect Reexaminedmentioning

confidence: 99%

“…The available experimental data on zeolites with window effects is contradictory and very scattered. There exists systematic data for n-alkanes up to C 14 on potassium-exchanged OFF/ERI intergrowths, 2 for ones up to C 12 on proton-exchanged CHA-type zeolites, 3 and for a few selected alkanes on various types of ERI/OFF intergrowths by Cavalcante et al 12 and Magalhães et al 13 Lattice intergrowths and defects, cations, and associated aluminum atoms create strong disorder, increase the hopping activation energy, inhibit the mobility of sorbates, and slow the diffusion process. Factors such as the existence of several different energetically favorable cation sites complicate the diffusion process.…”

Section: The Window Effect Reexaminedmentioning

confidence: 99%

“…Thus, agreement among microscopic (pulsed field gradient NMR, quasi-elastic neutron scattering), mesoscopic (micro-FTIR), and macroscopic (membrane permeation, uptake methods, zero-length column, frequency response) techniques is rare. As compared to Cavalcante et al 12 and Magalhães et al, 13 Gorring used too much sample in his mass uptake measurements and changed his sorbate concentration too drastically, so his data were prone to the intrusion of heat transfer and extracrystalline mass-transfer phenomena. The discrepancy between the experiments motivated us to develop a molecular simulation method that would allow us to study the adsorption and diffusion and shed some light on the experimental dispute.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Computer Simulation of Incommensurate Diffusion in Zeolites: Understanding Window Effects

2003

View full text Add to dashboard Cite

Dedicated molecular simulation techniques afford the study of the abnormal adsorption and diffusion of linear alkanes in ERI-, CHA-, and LTA-type zeolites. The exceptionally slow diffusion rates required the development of a combination of rare-event transition-state theory techniques and the configurational-bias Monte Carlo algorithm. The diffusion coefficients computed by this novel method agree well with the nondisputed rates determined experimentally for LTA-type sieves. The computed rates corroborate the nonmonotonic variation of the diffusion rate with alkane chain length published by Gorring, that is, the rate increases by orders of magnitude when the molecular and cage shape are no longer commensurate, so a molecule ends up stretched across a cage tethered at opposite windows. The simulations corroborate this "window effect" for both ERIand CHA-type sieves and suggest that it is characteristic for all sieves with windows approximately 0.4 nm across. They predict that it also occurs for LTA-type sieves provided that the n-alkane is long enough to exceed the diameter of the LTA-type supercage.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: The Window Effect Reexaminedmentioning

confidence: 99%

Section: The Window Effect Reexaminedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Computer Simulation of Incommensurate Diffusion in Zeolites: Understanding Window Effects

2003

View full text Add to dashboard Cite

show abstract

Diffusion and Adsorption in Porous Solids

Kärger¹,

Ruthven²

2002

Handbook of Porous Solids

View full text Add to dashboard Cite

Modeling of Transport and Accessibility in Zeolites

Calero¹

2010

Zeolites and Catalysis

View full text Add to dashboard Cite

IntroductionModeling plays an important role in the field of zeolites and related porous materials. The use of molecular simulations allows the prediction of adsorption and diffusion coefficients in these materials and also provides important information about the processes taking place inside the porous structures at the molecular level [1-10]. Hence, molecular modeling is a very good complement to experimental work in the understanding of the molecular behavior inside the pores.Despite the great interest and the applicability of zeolites, there are still many facets of the molecular mechanisms for a given reaction inside their pores that are poorly understood. These mechanisms are important for (i) the way the zeolite adsorbs, diffuses, and concentrates the adsorbates near the specific active sites; (ii) the interactions between the zeolite and the adsorbates and the effect on the electronic properties of the system; (iii) the chemical conversion at the active site; and (iv) the way the zeolite disperses the final product. Detailed knowledge on the molecular mechanisms involved will eventually lead to an increase in the reaction efficiency.This chapter focuses on molecular modeling of transport and accessibility in zeolites. It describes how simulations have contributed to a better understanding of these materials and provides a summary of the state of the art as well as of current challenges. The chapter is organized as follows. First, common models and potentials are briefly described. This is followed by a general overview on current simulation methods to compute adsorption, diffusion, free energies, surface areas, and pore volumes. The chapter continues with some examples on applications of molecular modeling to processes of interest from the industrial and environmental point of view. Finally, the chapter closes with a summary and some remarks on future challenges.

show abstract

Diffusion of n-paraffins in offretite-erionite type zeolites

Cited by 58 publications

References 19 publications

Computer Simulation of Incommensurate Diffusion in Zeolites: Understanding Window Effects

Computer Simulation of Incommensurate Diffusion in Zeolites: Understanding Window Effects

Diffusion and Adsorption in Porous Solids

Modeling of Transport and Accessibility in Zeolites

Contact Info

Product

Resources

About