分析多组分和多相聚合物系统 1H 自旋扩散 NMR 的数值模拟方法

IF 1.8 3区 化学 Q4 CHEMISTRY, PHYSICAL
Xuran Jin , Wei Chen
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引用次数: 0

摘要

报告了一种基于 Levenberg-Marquardt 算法和伪二维扩散模型的质子自旋扩散核磁共振数值模拟方法,即 ,。该方法用于精确量化多相聚合物体系中相间的动力学异质性。数值模拟方法可测量各组分的自旋晶格弛豫时间()、质子密度()、薄片厚度()和自旋扩散系数()。采用伪二维扩散模型模拟质子自旋扩散的建立/衰减曲线,同时计算岛状结构的横向比例(-ratio)。这种方法成功地应用于各种聚合物体系,如半结晶聚合物(聚ε-己内酯,PCL)、嵌段共聚物(苯乙烯-丁二烯-苯乙烯三嵌段共聚物,SBS)和塑化半聚合物(聚乙烯醇,PVA)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Numerical simulation method for analyzing 1H spin diffusion NMR for Multicomponent and multiphase polymer systems

A Numerical simulation method for analyzing 1H spin diffusion NMR for Multicomponent and multiphase polymer systems

A Numerical simulation method for analyzing 1H spin diffusion NMR for Multicomponent and multiphase polymer systems

A numerical simulation method, namely, SDNMR-WEBFIT, is reported for simulating proton spin diffusion NMR based on the Levenberg-Marquardt algorithm and a pseudo-2D diffusion model. This method is used for the precise quantification of dynamics heterogeneity of the interphase within multiphase polymer systems. The numerical simulation method provides measurements of spin-lattice relaxation time (T1), proton density (ρH), lamellar thickness (d), and spin diffusion coefficient (D) for each component. The pseudo-2D diffusion model is employed to simulate the proton spin diffusion build-up/decay curves, simultaneously calculating the lateral fraction of island-like structures (x-ratio). Such approach was successfully applied to various polymer systems, such as semi-crystalline polymer (Poly(ε-caprolactone), PCL), block copolymers (Styrene-butadiene-styrene triblock copolymer, SBS), and plasticized semi-polymers (Polvinyl alcohol, PVA).

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来源期刊
CiteScore
5.30
自引率
9.40%
发文量
42
审稿时长
72 days
期刊介绍: The journal Solid State Nuclear Magnetic Resonance publishes original manuscripts of high scientific quality dealing with all experimental and theoretical aspects of solid state NMR. This includes advances in instrumentation, development of new experimental techniques and methodology, new theoretical insights, new data processing and simulation methods, and original applications of established or novel methods to scientific problems.
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