超分子聚合物网络中异常扩散的分子解释,Macromolecules

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超分子聚合物网络中异常扩散的分子解释
Macromolecules ( IF 5.1 ) Pub Date : 2018-03-20 00:00:00 , DOI: 10.1021/acs.macromol.7b02465
Jorge Ramirez _{1,

2} , Thomas J. Dursch ₁ , Bradley D. Olsen ₁

Affiliation

最近的实验表明，具有不同结构（线性和分支）和不同性质的缔合相互作用（缔合蛋白结构域和金属-配体键）的各种缔合聚合物表现出无法解释的超扩散行为。在这里，未缠结的粗粒缔合星形聚合物的布朗动力学模拟用于建立解释该行为的链动力学的分子图。聚合物被概念化为具有有效Rouse扩散性的粒子，该粒子通过代表聚合物臂的无质量弹簧末端处的粘着物与附件的附件相互作用，从而与平均场背景进行交互。模拟结果揭示了分子尺度上远大于回转半径的三种扩散机理：受阻扩散，行走扩散，和分子跳跃，所有这些都很大程度上取决于聚合物浓度，臂长和缔合/解离速率常数。分子模型建立了超扩散结垢主要是由分子跳变引起的，分子跳变仅在附着动力学比悬挂链的弛豫时间慢时发生。比例关系可用于识别预期此行为的速率常数范围。网络中回路的形成通过减少必须跳开才能发生跳变步骤的臂的总数来促进这种超扩散缩放。仅当附着的动力学比悬挂的链的松弛时间慢时，才会发生这种情况。比例关系可用于识别预期此行为的速率常数范围。网络中回路的形成通过减少必须跳开才能发生跳变步骤的臂的总数来促进这种超扩散缩放。这仅在附着动力学比悬挂链的松弛时间慢时发生。比例关系可用于识别预期此行为的速率常数范围。网络中回路的形成通过减少必须跳开才能发生跳变步骤的臂的总数来促进这种超扩散缩放。

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A Molecular Explanation for Anomalous Diffusion in Supramolecular Polymer Networks

Recent experiments have revealed that a variety of associative polymers with different architecture (linear and branched) and different nature of the associating interaction (associative protein domains and metal–ligand bonds) exhibit unexplained superdiffusive behavior. Here, Brownian dynamics simulations of unentangled coarse-grained associating star-shaped polymers are used to establish a molecular picture of chain dynamics that explains this behavior. Polymers are conceptualized as particles with effective Rouse diffusivities that interact with a mean field background through attachments by stickers at the end of massless springs that represent the arms of the polymer. The simulations reveal three mechanisms of molecular diffusion at length scales much larger than the radius of gyration: hindered diffusion, walking diffusion, and molecular hopping, all of which depend strongly on polymer concentration, arm length, and the association/dissociation rate constants. The molecular model establishes that superdiffusive scaling results primarily from molecular hopping, which only occurs when the kinetics of attachment are slower than the relaxation time of dangling strands. Scaling relationships can be used to identify the range of rate constants over which this behavior is expected. The formation of loops in the networks promotes this superdiffusive scaling by reducing the total number of arms that must detach in order for a hopping step to occur.

更新日期：2018-03-20

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