The molar mass distribution (MMD), which is also known as the molecular weight distribution (MWD), is a key molecular property for a polymerization process, as it determines polymer strength and polymeric material deformation. Several MMD and related chain length distribution (CLD) representations are however used interchangeably, often leading to biased conclusions. Herein it is highlighted how the most interesting simulated CLD/MMD representations, i.e., the number, mass, z-based, and logarithmic CLD/MMD, can be translated into each other and how they need to be corrected to facilitate comparison with experimental size exclusion chromatography traces. Their relevance is highlighted by including case studies with increasing complexity in polymer products, addressing first linear, then branched, and ultimately crosslinked systems. For illustration purposes, the case studies are restricted to chain-growth polymerization, including free radical polymerization, cationic ring-opening polymerization, and free radical-induced grafting. All model parameters are taken from literature and kinetic Monte Carlo tools are utilized. Guidelines are also provided for both the experimentalist and modeler to maximize the reliability of CLD/MMD reporting in future kinetic studies.

中文翻译：

---

在链增长聚合中转换模拟的链长和摩尔质量分布以进行实验比较和机理分析

摩尔质量分布（MMD），也称为分子量分布（MWD），是聚合过程的关键分子性质，因为它决定了聚合物强度和聚合物材料变形。但是，可以互换使用几种MMD和相关的链长分布（CLD）表示形式，通常会得出有偏差的结论。本文重点介绍了如何将最有趣的模拟CLD / MMD表示形式（即数量，质量，基于z和对数的CLD / MMD）相互转换，以及如何进行校正以方便与实验尺寸进行比较排除色谱痕迹。通过包括案例研究来突出它们的相关性，这些案例研究的聚合物产品的复杂性不断提高，首先解决的是线性，分支和最终交联的系统。为了说明的目的，案例研究仅限于链增长聚合，包括自由基聚合，阳离子开环聚合和自由基诱导的接枝。所有模型参数均取自文献，并使用了动力学蒙特卡洛工具。还为实验人员和建模人员提供了指南，以在将来的动力学研究中最大程度地提高CLD / MMD报告的可靠性。