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轨迹延伸的动力蒙特卡洛模拟用于通过密集的聚合物膜评估纯和气体混合物的扩散性

Subhadeep Dasgupta¹, Arun K S¹, K Ganapathy Ayappa²

¹Department of Physics, Indian Institute of Science, Bangalore 560012, India.

The journal of physical chemistry. B

|November 7, 2023

概括

延长轨迹的动力蒙特卡罗 (TEKMC) 模拟可以改善碳分子选 (CMS) 膜性能评估. 使用混合物扩散数据,而不是纯气体数据,准确地预测CMS膜选择性,超过罗伯逊极限.

科学领域:

材料科学材料科学材料科学
化学工程是化学工程的重要组成部分.
计算化学计算化学

背景情况:

精确评估碳分子选 (CMS) 膜性能需要可靠的扩散系数来估计透性.
实现高选择性和透性对于最佳的CMS膜材料至关重要.
气体通过膜扩散的亚扩散模式阻碍了精确的扩散系数提取.

研究的目的:

通过扩展分子动力学 (MD) 轨迹来改进CMS膜中扩散景观的采样.
准确确定CMS膜中的纯二氧化碳和混合物扩散率.
评估使用混合物扩散率数据对CMS膜选择性预测的影响.

主要方法:

实施轨迹延长动力蒙特卡洛 (TEKMC) 技术,将MD轨迹从ns延长到μs时间尺度.
在6FDA/BPDA-DAM前体聚合物化中的纯CO2自我扩散系数的计算.
扩展TEKMC以评估二进制CO2/CH4和CO2/N2混合物中的混合物扩散率.
从大规范蒙特卡洛 (GCMC) 模拟中整合气体溶解度.

主要成果:

在CMS膜中,纯二氧化碳的自我扩散系数随着压力 (1-20 bar) 的增加而线性增加.
在CO2/CH4中,二氧化碳混合物的扩散系数明显高于纯气的扩散系数.
使用混合物扩散率的 permselectivity 预测超过了纯气体数据的预测,超过了 CO2/N2 混合物的罗伯森极限.

结论:

TEKMC模拟为评估CMS膜性能提供了一种可靠的方法.
使用混合物扩散率数据对于准确的选择性评估至关重要,特别是对于超越像罗宾逊极限这样的既定性能基准.
这种方法有助于设计和选择用于高效气体分离的先进材料.

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