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Obtaining the Kinetic Function of Depolymerization from Evolving Molecular Weight Distribution Data-An Inverse Problem

机译:从不断发展的分子量分布数据获得解聚的动力学功能-一个反问题

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Depolymerization of macromolecules is generally regarded as a first order process with a kinetic function that depends on the molecular weights of the fragmenting molecule and fragmentation products. This article describes a computation scheme for obtaining the kinetic function from observed molecular weight distribution (MWD) data. The integro-differential equation used by most investigators to compute MWD with some assumed kinetic function is reformulated as an inverse problem in which the kinetic function is treated as the unknown to be extracted from evolving MWD data. A numerical procedure based on two consecutive applications of Tikhonov regularization is developed to solve this inverse problem. It gives the kinetic function as the solution of a set of linear algebraic equations. Implementation of this procedure is described in full and its performance is assessed by applying it to simulated MWD data. A number of issues associated with discretization and regularization are discussed.
机译:大分子的解聚通常被认为是具有动力学功能的一级过程,该动力学功能取决于片段化分子和片段化产物的分子量。本文介绍了一种从观察到的分子量分布(MWD)数据获得动力学函数的计算方案。大多数研究者用来计算具有某些假定动力学函数的MWD的积分微分方程被重新构造为反问题,其中动力学函数被视为未知数,可以从不断发展的MWD数据中提取。基于Tikhonov正则化的两个连续应用的数值程序被开发来解决这个反问题。它给出动力学函数作为一组线性代数方程的解。完整描述了此过程的实现,并将其应用于模拟的MWD数据来评估其性能。讨论了与离散化和正则化相关的许多问题。

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