预测和定制梳状聚合物涂层纳米级渗透率的一般方法。

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Nicole Drossis, Marc A Gauthier, Hendrick W de Haan
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引用次数: 0

摘要

梳状聚合物,如聚(低聚乙二醇单甲醚)甲基丙烯酸酯(pOEGMA),用于在蛋白质上生产分子筛选涂层。在实验中观察到的筛分特性的机制和现象最近被模拟表征。这些结果是位阻、微环境效应和修饰的蛋白质动力学之间相互作用的结果。特别是空间位阻,预计会随着系统几何参数(蛋白质大小、聚合物大小、接枝密度等)的变化而发生很大的变化。在这项工作中,梳状聚合物涂层的立体和尺寸选择性渗透特性在一个非常广泛的参数空间中进行了系统的探索,以获得分子筛分的通用和预测性观点,用于不同维度的系统。当考虑三种不同的机制时,数据的所有特征都可以被理解:i)无相互作用,ii)弱相互作用,iii)相邻聚合物链之间的强相互作用。提出了调整涂层性能以调整分子筛尺寸阈值的主要和次要考虑因素。相应的定性物理图和定量分析为理解分子筛分提供了一个强有力的框架,这将加速未来涂料的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A General Approach to Predict and Tailor the Nanoscale Permeability of Comb-Shaped Polymer Coatings.

Comb-shaped polymers such as poly(oligoethylene glycol monomethyl ether) methacrylate) (pOEGMA) are used to produce molecular sieving coatings on proteins. The mechanisms and phenomena implicated in the experimentally observed sieving properties have been recently characterized by simulation. These result from an interplay between steric hindrance, microenvironmental effects, and modified protein dynamics. Steric hindrance, in particular, is expected to vary considerably as a function of the geometric parameters of the system (protein size, polymer size, grafting density, etc.). In this work, the steric and size-selective permeability characteristics of comb-polymer coatings are systematically explored across a very broad parameter space to gain a universal and predictive view of molecular sieving, for application to systems with different dimensions. All features of the data can be understood when three distinct regimes are considered: i) no-interactions, ii) weak-interactions, and iii) strong-interactions between adjacent polymer chains. Primary and secondary considerations are provided for tuning coating properties to adjust the size threshold of molecular sieving. The corresponding qualitative physical pictures and quantitative analyses give a robust framework to understand molecular sieving that will accelerate the development of future coatings.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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