烟草科技2025，Vol.58Issue(4)：11-19,9.DOI:10.16135/j.issn1002-0861.2024.0802
基于高分辨CT扫描和深度学习的典型烟草提取物精制滤膜的三维构效关系
Three-dimensional structure-property relationships for filter membranes used to refine tobacco extracts based on high-resolution CT scanning and deep machine learning
摘要
Abstract
To clarify the structure-property relationships between the three-dimensional structure of filter membranes to achieve the targeted refinement of tobacco extracts,the structural changes of typical filter membranes before and after tobacco filtration were quantitatively examined and calculated.By combining the analysis of the active components in the tobacco extracts,the microstructure of the filter membranes and their mechanisms of separation and refinement of tobacco extracts were dissected.Dynamic light scattering(DLS)and gas chromatography-mass spectrometry(GC-MS)analyses were used to characterize the changes in particle sizes and components of the tobacco extracts before and after membrane separation.High-resolution CT scanning technique was used for structural characterization of the filter membranes.In addition,the deep learning technique was combined with the U-Net neural network algorithm to quantitatively calculate the structural parameters of the filter membranes.The results showed that:1)Compared with PA membrane,PTFE membrane could retain more solid phase materials and nicotine from tobacco extracts.2)The calculations by intelligent segmentation showed that the porosity of PA membrane decreased by 4.4％,the thickness increased by 0.6 mm,and the average fiber diameter decreased by 154.73 μm after filtration,which was caused by membrane fiber squeezing due to membrane pore blockage.3)The PTFE membrane with a pore size of 0.22 μm had an average fiber diameter of 1 694.0 μm and a porosity of 42.7％,which were smaller than those of the PA membrane.The dense fiber alignment of the PTFE membrane resulted in greater retention of solid phase materials.A quantitative method to analyze the three-dimensional structure of the filter membranes was proposed by integrating the microstructural characterization of the filter membrane with deep learning and correlating it with the component changes in the extract sample before and after filtration,which provided a theoretical reference for targeted filter separation of tobacco extracts.关键词
膜分离/烟草提取物/高分辨CT扫描/U-Net神经网络/深度学习/孔隙率/构效关系Key words
Membrane separation/Tobacco extract/High-resolution CT scanning/U-Net neural network/Deep learning/Porosity/Structure-property relationship分类
轻工业引用本文复制引用
管明婧,陈韦剑,李鲁,付硕,姜余婷,宋晓辉,张劲,周顺,张晓宇,王孝峰,曹芸,田慧娟,丁乃红,李延岩..基于高分辨CT扫描和深度学习的典型烟草提取物精制滤膜的三维构效关系[J].烟草科技,2025,58(4):11-19,9.基金项目
中国烟草总公司加热卷烟研制重大专项项目"颗粒型加热卷烟产品生产关键控制技术及效能提升研究"[110202201046(XX-05)] （XX-05）
安徽中烟工业有限责任公司科研项目"加热卷烟用增香胶囊的开发及应用研究"(2022155)、"加热不燃烧烟草制品用特种复合滤棒开发及应用研究"(2020130). （2022155）
