多分散Polymer网络的选择透过率调节
Tuning the Selective Permeability of Polydisperse Polymer Networks
摘要：
我们研究的渗透性和选择性（“渗透选择性”）的模型膜制成的多分散聚合物网络的分子渗透剂的运输，使用粗粒度，隐式溶剂的计算机模拟。通过计算膜内的平衡渗透剂分配比$\mathcal K$和渗透剂扩散率$D_\text{in}$，使用溶液-扩散模型$\mathcal P = {\mathcal K}D_\text{in}$、$\textit{i.e.}$在线性响应水平上确定渗透率$\mathcal P$。我们改变两个关键参数，即单体-单体相互作用，它控制网络的膨胀和崩溃的程度，和单体-渗透剂相互作用，它调整渗透剂的吸收和微观能量景观的扩散运输。分配比$\mathcal K$的结果覆盖四个数量级，是非单调的参数，这是很好地解释了二阶维里扩展的自由能转移一个渗透剂从散装到聚合物介质。我们发现，在多分散网络中的渗透剂扩散率$D_\text{in}$，在高度有序的膜结构相比，表现出相对简单的指数衰减，并遵守众所周知的自由体积和Kramers的逃逸标度律。因此，最终得到的渗透率$\mathcal P$类似于分配的定性功能行为（包括最大化和最小化）。然而，分区和扩散是反相关的，产生大量的量化取消，控制和微调的网络密度和相互作用合理化我们的标度律。因此，我们最终证明，即使是很小的变化，半个$k_\text{B}T$的助溶剂网络相互作用，$\textit{e.g.}$，修改渗透选择性的膜几乎一个数量级。
英文摘要：
We study the permeability and selectivity (`permselectivity') of model membranes made of polydisperse polymer networks for molecular penetrant transport, using coarse-grained, implicit-solvent computer simulations. The permeability $\mathcal P$ is determined on the linear-response level using the solution-diffusion model, $\mathcal P = {\mathcal K}D_\text{in}$, $\textit{i.e.}$, by calculating the equilibrium penetrant partition ratio $\mathcal K$ and penetrant diffusivity $D_\text{in}$ inside the membrane. We vary two key parameters, namely the monomer-monomer interaction, which controls the degree of swelling and collapse of the network, and the monomer-penetrant interaction, which tunes the penetrant uptake and microscopic energy landscape for diffusive transport. The results for the partition ratio $\mathcal K$ cover four orders of magnitude and are non-monotonic versus the parameters, which is well interpreted by a second-order virial expansion of the free energy of transferring one penetrant from bulk into the polymeric medium. We find that the penetrant diffusivity $D_\text{in}$ in the polydisperse networks, in contrast to highly ordered membrane structures, exhibits relatively simple exponential decays and obeys well-known free-volume and Kramers' escape scaling laws. The eventually resulting permeability $\mathcal P$ thus resembles the qualitative functional behavior (including maximization and minimization) of the partitioning. However, partitioning and diffusion are anti-correlated, yielding large quantitative cancellations, controlled and fine-tuned by the network density and interactions as rationalized by our scaling laws. As a consequence, we finally demonstrate that even small changes of penetrant-network interactions, $\textit{e.g.}$, by half a $k_\text{B}T$, modify the permselectivity of the membrane by almost one order of magnitude.
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