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压力耦合灌注旋转纺丝法制备聚合物纤维直径的过程建模

Process Modeling for the Fiber Diameter of Polymer, Spun by Pressure-Coupled Infusion Gyration.

作者信息

Hong Xianze, Harker Anthony, Edirisinghe Mohan

机构信息

Department of Mechanical Engineering, University College London (UCL), Torrington Place, London WC1E 7JE, U.K.

Department of Physics and Astronomy, University College London (UCL), Gower Street, London WC1E 6BT, U.K.

出版信息

ACS Omega. 2018 May 21;3(5):5470-5479. doi: 10.1021/acsomega.8b00452. eCollection 2018 May 31.

DOI:10.1021/acsomega.8b00452
PMID:31458751
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6641922/
Abstract

Several new spinning methods have been developed recently to mass produce polymeric fibers. Pressure-coupled infusion gyration is one of them. Because the fiber diameter plays a pivotal role for the mechanical, electrical, and optical properties of the produced fiber mats, in this work, polyethylene oxide is used as a model polymer, and the processing parameters including polymer concentration, infusion (flow) rate, working pressure, and rotational speed are chosen as variables to control fiber diameters spanning the micro- to nanoscale. The experimental process is modeled using response surface methodology, both in linear and nonlinear fitting formats, to allow optimization of processing parameters. The successes of the fitted models are evaluated using adjusted and Akaike information criterion. A systematic description of the experimental process could be obtained according to the model in this study. From the analysis of variance, it is concluded that the polymer concentration of the solution and the working pressure affected the fiber diameters more strongly than other parameters.

摘要

最近开发了几种新的纺丝方法来大规模生产聚合物纤维。压力耦合灌注旋转法就是其中之一。由于纤维直径对所生产纤维毡的机械、电学和光学性能起着关键作用,在这项工作中,聚环氧乙烷被用作模型聚合物,并且选择包括聚合物浓度、灌注(流速)、工作压力和转速在内的加工参数作为变量,以控制跨度从微米到纳米级的纤维直径。实验过程采用响应面法进行建模,包括线性和非线性拟合形式,以实现加工参数的优化。使用调整后的 和赤池信息准则评估拟合模型的成功程度。根据本研究中的模型,可以获得对实验过程的系统描述。从方差分析得出结论,溶液的聚合物浓度和工作压力对纤维直径的影响比其他参数更强。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/311dddd16c2f/ao-2018-00452m_0008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/8fde007b17b2/ao-2018-00452m_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/311dddd16c2f/ao-2018-00452m_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/db1fd2599997/ao-2018-00452m_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/15aef20384c2/ao-2018-00452m_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/f7f72d8d3cb4/ao-2018-00452m_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/9042d29c05fb/ao-2018-00452m_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/2816b27e910c/ao-2018-00452m_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/5f5242434265/ao-2018-00452m_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/8fde007b17b2/ao-2018-00452m_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/75aa/6641922/311dddd16c2f/ao-2018-00452m_0008.jpg

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