Conformational Distributions near and on the Substrate during Surface-Initiated Living Polymerization: A Lattice-Based Kinetic Monte Carlo Approach,Macromolecules

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Conformational Distributions near and on the Substrate during Surface-Initiated Living Polymerization: A Lattice-Based Kinetic Monte Carlo Approach
Macromolecules ( IF 5.1 ) Pub Date : 2020-06-04 , DOI: 10.1021/acs.macromol.0c00585
Francisco J. Arraez ₁ , Paul H. M. Van Steenberge ₁ , Dagmar R. D’hooge _{1,

2}

Affiliation

One of the challenges in the field of surface-initiated polymerization (SIP) is gaining access to conformational distributions allowing one to quantify the degree of brush/mushroom character during synthesis. Here, we put forward a novel kinetic Monte Carlo (kMC) tool to be successful in this respect, focusing on chain-to-chain deviations on and near the surface accounting for varying reaction probabilities and combining conventional kMC modeling with a modified version of the bond fluctuation model. The potential of the tool is illustrated for living SIP addressing the effect of shielding on the efficiency of surface initiation and propagation. It is shown that at higher reaction times shielding for propagation leads to the increased formation of hindered shorter chains, causing the formation of a bimodal number chain-length distribution (CLD) for tethered chains compared to the always unimodal number CLD for free larger chains near the surface. Moreover, it can be evaluated at any synthesis time if an individual chain possesses a mushroom, brushlike, or brush conformation. It is demonstrated that an optimal (average) initiator surface coverage exists, leading to a sufficiently high chain grafting density and a maximization of the brush character provided that an initiator with the correct (surface) initiation reactivity is selected. The developed tool is important for the multiangle design of future SIP processes focusing on optimization in reaction time, control over CLD, and conformational features in view of the desired application.

中文翻译：

表面引发的活性聚合过程中基质附近和基质上的构象分布：基于晶格的动力学蒙特卡洛方法

表面引发聚合（SIP）领域的挑战之一是获得构象分布，以使人们能够量化合成过程中刷子/蘑菇形特征的程度。在这里，我们提出了一种新颖的动力学蒙特卡洛（kMC）工具，该工具在这方面是成功的，着眼于表面上和表面附近的链间偏差，以考虑变化的反应概率，并将传统的kMC建模与该模型的修改版本结合起来债券波动模型。说明了该工具用于实时SIP的潜力，解决了屏蔽对表面引发和传播效率的影响。结果表明，在较高的反应时间，对传播的屏蔽导致受阻较短链的形成增加，与系留在表面附近的较大自由链的始终单峰数CLD相比，可导致拴链的双峰数链长分布（CLD）形成。而且，如果单个链具有蘑菇状，刷状或刷状构象，则可以在任何合成时间进行评估。已经证明，存在最佳的（平均）引发剂表面覆盖率，如果选择了具有正确的（表面）引发反应性的引发剂，则会导致足够高的链接枝密度和最大的刷涂特性。所开发的工具对于未来SIP工艺的多角度设计非常重要，该设计着眼于所需应用的优化反应时间，CLD控制和构象特征的优化。

更新日期：2020-06-23

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