Supramolecular fibers composed of monomers that self-assemble directionally via noncovalent interactions are ubiquitous in nature, and of great interest in chemistry. In these structures, the constitutive monomers continuously exchange in-and-out the assembly according to a well-defined supramolecular equilibrium. However, unraveling the exchange pathways and their molecular determinants constitutes a nontrivial challenge. Here, we combine coarse-grained modeling, enhanced sampling, and machine learning to investigate the key factors controlling the monomer exchange pathways in synthetic supramolecular polymers having an intrinsic dynamic behavior. We demonstrate how the competition of directional vs. nondirectional interactions between the monomers controls the creation/annihilation of defects in the supramolecular polymers, from where monomers exchange proceeds. This competition determines the exchange pathway, dictating whether a fiber statistically swaps monomers from the tips or from all along its length. Finally, thanks to their generality, our models allow the investigation of molecular approaches to control the exchange pathways in these dynamic assemblies.

中文翻译：

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通过控制缺陷来控制动态超分子聚合物中的交换途径

由单体组成的超分子纤维通过非共价相互作用定向自组装，在自然界中无处不在，并且在化学中引起了极大的兴趣。在这些结构中，组成单体根据明确定义的超分子平衡在组件内外不断交换。然而，解开交换途径及其分子决定因素是一项重大挑战。在这里，我们结合粗粒度建模、增强采样和机器学习来研究控制具有内在动态行为的合成超分子聚合物中单体交换途径的关键因素。我们展示了定向与定向的竞争是如何进行的。单体之间的非定向相互作用控制着超分子聚合物中缺陷的产生/消失，从那里进行单体交换。这种竞争决定了交换途径，决定了纤维是从尖端还是从整个长度统计交换单体。最后，由于它们的普遍性，我们的模型允许研究分子方法来控制这些动态组装中的交换途径。