Optimization of Electrospinning Parameter by Employing Genetic Algorithm in order to Produce Desired Nanofiber Diameter

S. Saehana, Ferry Iskandar, M. Abdullah, Khairurrijal
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引用次数: 6

Abstract

A numerical simulation of optimization all of electrospinning processing parameters to obtain smallest nanofiber diameter have been performed by employing genetic algorithm (GA). Fitness function in genetic algorithm methods, which was different for each parameter, was determined by simulation approach based on the Reneker’s model. Moreover, others genetic algorithm parameter, namely length of population, crossover and mutation were applied to get the optimum electrospinning processing parameters. In addition, minimum fiber diameter, 32 nm, was achieved from a simulation by applied the optimum parameters of electrospinning. This finding may be useful for process control and prediction of electrospun fiber production. In this paper, it is also compared between predicted parameters with some experimental results. Keywords—Diameter, Electrospinning, GA, Nanofiber.
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采用遗传算法优化静电纺丝参数,以获得理想的纳米纤维直径
采用遗传算法对静电纺丝工艺参数进行了优化,以获得最小的纳米纤维直径。遗传算法中的适应度函数对每个参数都是不同的,采用基于Reneker模型的仿真方法确定。此外,还利用种群长度、交叉和变异等遗传算法参数,得到了纺丝工艺的最佳参数。采用静电纺丝的最佳工艺参数,模拟得到了最小纤维直径为32 nm的纤维。这一发现对电纺丝生产过程的控制和预测有一定的指导意义。本文还将预测参数与部分实验结果进行了比较。关键词:直径;静电纺丝;GA;
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