Qin Jieyao, Lu Mingxi, Li Bin, Li Xiaorui, You Guangming, Tan Linjian, Zhai Yikui, Huang Meilin, Wu Yingzhu
School of Textile Materials and Engineering, Wuyi University, Jiangmen 529020, China.
College of Innovation and Entrepreneurship, Wuyi University, Jiangmen 529020, China.
Polymers (Basel). 2023 Feb 8;15(4):842. doi: 10.3390/polym15040842.
To accelerate the industrialization of bicomponent fibers, fiber-based flexible devices, and other technical fibers and to protect the property rights of inventors, it is necessary to develop fast, economical, and easy-to-test methods to provide some guidance for formulating relevant testing standards. A quantitative method based on cross-sectional in-situ observation and image processing was developed in this study. First, the cross-sections of the fibers were rapidly prepared by the non-embedding method. Then, transmission and reflection metallographic microscopes were used for in-situ observation and to capture the cross-section images of fibers. This in-situ observation allows for the rapid identification of the type and spatial distribution structure of the bicomponent fiber. Finally, the mass percentage content of each component was calculated rapidly by AI software according to its density, cross-section area, and total test samples of each component. By comparing the ultra-depth of field microscope, differential scanning calorimetry (DSC), and chemical dissolution method, the quantitative analysis was fast, accurate, economical, simple to operate, energy-saving, and environmentally friendly. This method will be widely used in the intelligent qualitative identification and quantitative analysis of bicomponent fibers, fiber-based flexible devices, and blended textiles.
为加速双组分纤维、纤维基柔性器件及其他工业用纤维的产业化进程,并保护发明人的知识产权,有必要开发快速、经济且易于测试的方法,为制定相关测试标准提供一些指导。本研究开发了一种基于横截面原位观察和图像处理的定量方法。首先,采用非包埋法快速制备纤维横截面。然后,使用透射和反射金相显微镜进行原位观察,并采集纤维的横截面图像。这种原位观察能够快速识别双组分纤维的类型和空间分布结构。最后,通过人工智能软件根据各组分的密度、横截面积和各组分的总测试样本,快速计算出各组分的质量百分比含量。通过与超景深显微镜、差示扫描量热法(DSC)和化学溶解法进行比较,该定量分析具有快速、准确、经济、操作简单、节能和环保等优点。该方法将广泛应用于双组分纤维、纤维基柔性器件和混纺织物的智能定性识别和定量分析。