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A parallelizable block cellular automaton for the study of diffusion of binary mixtures containing CO_2 in microporous materials

机译:用于研究含CO_2的二元混合物在微孔材料中扩散的可并行块胞自动机

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摘要

We applied a method based on a block cellular automaton (BCA) algorithm to the study of diffusion of various binary mixtures adsorbed in a model microporous material, such as zeolite ZK4. Our aim was to test the capability of our model to cope with systems in which more than one species is present, using a set of parameters based on heuristic considerations from the molecular dynamics (MD) results present in the literature. A rigorous methodology for the assignment of suitable adsorption energies and diffusion activation barriers for our BCA has not been developed yet, nonetheless the results were quite interesting at this stage and we obtained a good qualitative agreement with MD data in the literature. The mixtures we investigated contain CO_2, which causes the so-called segregation-effect, a strong suppression of self-diffusivity of co-adsorbed species. This effect gives rise to relevant problems in the application of some well established and robust methods, while our model proved to be able to reproduce both the common features and the segregation anomaly in the trends of diffusion.
机译:我们将基于块细胞自动机(BCA)算法的方法应用于研究吸附在模型微孔材料(例如沸石ZK4)中的各种二元混合物的扩散。我们的目标是使用一组基于文献中分子动力学(MD)结果启发式考虑的参数,测试模型处理存在多个物种的系统的能力。尚未开发出为我们的BCA分配合适的吸附能和扩散活化势垒的严格方法,尽管如此,在该阶段的结果还是很有趣的,并且我们在文献中获得了与MD数据良好的定性一致性。我们研究的混合物中含有CO_2,这会导致所谓的偏析效应,即强烈抑制共吸附物质的自扩散性。这种效果在一些成熟可靠的方法的应用中引起了相关的问题,而我们的模型被证明能够再现扩散趋势中的共同特征和偏析异常。

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