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Cavity Energetic Sizing Algorithm Applied in Polymeric Membranes for Gas Separation

机译:用于气体分离的聚合物膜中应用的腔高能施胶算法

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Polymeric membranes demonstrate the fastest emerging field in membrane gas separation since it has huge reproducibility for large scale production and low cost fabrication. To date, many research works have emerged to propose different polymeric materials for membrane synthesis and fabrication in order to enhance gas separation performance. It has been suggested that the underlying factor that distinguishes the difference in separation efficiency among varying polymer is the amount of free volume formed throughout the polymeric matrix. Therefore, in current work, through adaptation of atomistic models by a combination of molecular dynamics and Monte Carlo or commonly known as the Cavity Energetic Sizing Algorithm (CESA), the cavity size distributions of several commonly adapted polymeric membranes for gas separation have been determined. The accuracy of the simulated molecular structure has been verified by comparing the simulated and measured experimental density. It is found from the study that that the CESA algorithm is capable of capturing the free volume distribution within the polymeric matrix, with the higher free volume polymeric membrane inheriting higher average cavity size [PTMSP (10.30A) >PPO (4.86A) >Matrimid~R 5218 (4.01A) >PSF (3.25A)]. In addition, the higher free volume polymers, which exhibit shift towards the larger cavity sizes, also reveal higher gas permeability for gas molecules. The sieving capability of the polymer is also demonstrated to be correlated with the kinetic diameter of the gas penetrants as compared to the cavity size. In future work, the methodology is proposed to be employed as a preliminary step to predict polymeric membrane morphology in order to evaluate the feasibility of any polymers before being applied in gas separation.
机译:聚合物膜展示膜气体分离中最快的出现场,因为它具有大规模生产和低成本制造的巨大再现性。迄今为止,已经出现了许多研究作品,提出了用于膜合成和制造的不同聚合物材料,以提高气体分离性能。已经表明,区分不同聚合物之间分离效率差异的潜在因子是在整个聚合物基质中形成的自由体积的量。因此,在当前工作中,通过分子动力学和蒙特卡罗的组合或通常称为腔体能量施胶算法(CESA)的组合来改编原子型模型,已经确定了几种常用的气体分离的常用聚合物膜的腔尺寸分布。通过比较模拟和测量的实验密度来验证模拟分子结构的准确性。从研究中发现,CESA算法能够捕获聚合物基质内的自由体积分布,具有更高的自由体积聚合物膜遗传较高的平均腔尺寸[PTMSP(10.30A)> PPO(4.86A)>基质蛋白〜R 5218(4.01A)> PSF(3.25A)]。另外,较高的自由体积聚合物,其朝向较大的腔体尺寸的变化,也揭示了气体分子的更高的透气性。与腔尺寸相比,聚合物的筛分能力也与气体渗透剂的动力学直径相关。在将来的工作中,提出了方法作为预测聚合物膜形态的初步步骤,以便在施加气体分离之前评估任何聚合物的可行性。

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