Adsorption and Diffusion in Zeolites: A Computational Study by Franse J.J.M. PDF

By Franse J.J.M.

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This introduces a bias in the generation of the new configuration, which can be removed exactly by a modification of the acceptance/rejection rule. In such a multiple chain algorithm, it is essential to have a good load balance. This means 38 Recoil growth algorithm for chain molecules with continuous interactions that every processor is doing roughly the same amount of work. Therefore, the distribution in CPU time for the construction of a chain should be as small as possible. 2). Note that in CBMC, a chain is only discarded for numerical reasons when the Rosenbluth weight is in the order of the machine accuracy of the computer (roughly ¾ ¢ ½¼¹¿¼ for the computer used in this study).

For models direction with a probability proportional to its Boltzmann weight ¼ (even though it may be very small). Hence, in a naive with continuous interactions, implementation of the CBMC scheme, the growth of a trial configuration will be completed, no matter how small (see, however, ref. [114]). Of course, in the acceptance step, conformations with a very low weight will most likely be rejected. In contrast, in the RG scheme, unlikely configurations are weeded out at an early stage because, most likely, they will be “closed”.

This suggests that the Silicalite used by Rakhmatkariev et al. and Dubinin et al. may suffer from pore blocking. 6 the experimental isotherms for hexane of Stach et al. [124], Richard and Rees [128], and Sun et al. [131] are compared with the simulation results using the model of June et al. and the model developed in this work. 3) it was already clear that the model of June et al. would overestimate the adsorption significantly. Our model gives a better agreement with experiments. For heptane adsorption isotherms have been reported by Lohse and Fahlke [125], Rakhmatkariev et al.

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Adsorption and Diffusion in Zeolites: A Computational Study by Franse J.J.M.

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