l -丙交酯聚合动力学分析及多目标优化

Geetu P Paul, Virivinti Nagajyothi
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引用次数: 0

摘要

-生物聚合物已成为传统石化聚合物的合适替代品,缓解了我们对环境的担忧。作为聚烯烃的替代品,聚乳酸(PLA)已被确定为一种具有良好生物降解能力的聚合物。丙交酯开环聚合(ROP)是一种高效的聚合方法。以2-乙基己酸锡(II)盐为催化剂,醇为助催化剂,采用均匀搅拌间歇式反应器,建立了经过验证的基于矩的丙交酯ROP动力学模型,求解了多目标优化问题(MOOP)。MOOP由三个相互冲突的目标函数组成:时间最小化、PDI最小化和数平均分子量(Mn)最大化。以目标函数范围的质量平衡方程为约束条件,采用决策变量对工艺性能进行分析。优化问题不包含单个解,而是包含多个同等重要的解(帕累托前沿),这些解被称为非支配解,该帕累托前沿是使用Deb, 2001开发的非支配排序遗传算法-II (NSGA II)获得的。一些帕累托前沿点显示出比实验数据更好的结果。与实验数据不同的建模和优化方面可以直接应用于实际的大型工厂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Kinetic Analysis and Multi Objective Optimization of L-Lactide Polymerization
- Biopolymers have emerged as an appropriate replacement for conventional petrochemical polymers consoling our environmental concern. As an alternative to polyolefin, polylactic acid (PLA) has been identified as a capable biodegradable polymer. Lactide ring opening polymerization (ROP) has been demonstrated to be an efficient polymerization method. A well validated moment based kinetic model for lactide ROP referring with homogeneously well stirred batch reactor using 2-ethylhexanoic acid tin (II) salt as the catalyst and an alcohol as co-catalyst has been utilized to formulate the multi objective optimization problem (MOOP). The MOOP is composed of three conflicting objective functions: minimization of time, minimization of PDI and maximization of number average molecular weight (Mn). Decision variables have been implemented to analyse the process performance with the mass balance equation for objective function ranges as constraints. The optimization problem does not contain a single solution but rather contains several equally important solutions (Pareto front) which are called as non-dominated solutions and this Pareto front is obtained by using non-dominated sorting genetic algorithm-II (NSGA II) developed by Deb, 2001. Some of the Pareto front points showed better outcomes rather than the experimental data. The distinct aspect of modeling and optimization from experimental data can be applied directly in the actual large-scale plants.
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