阳离子改性纤维在造纸法加热不燃烧烟草薄片中的应用研究
Application of Cationic Modified Fibers in Heat-not-burn Reconstituted Tobacco by Papermaking Composite Method
王克彦 1罗冲 2陈顺辉 2王保会 2田云增 2李锦 2闫瑛 2李斌 3张展 3张俊岭 2温洋兵1
作者信息
- 1. 天津科技大学,天津市制浆造纸重点实验室,天津,300457
- 2. 河南卷烟工业烟草薄片有限公司,河南许昌,461100
- 3. 中国烟草总公司郑州烟草研究院,河南郑州,450001
- 折叠
摘要
本研究利用阳离子改性纤维具有正电荷和高保水值的特点,与漂白木浆复合抄造制备加热不燃烧烟草薄片基片,以提升基片的吸收性能.结果表明,阳离子改性纤维的添加能有效降低基片的紧度,提升其对涂布液的吸收性能,增加加热不燃烧烟草薄片对涂布液的负载率.未添加阳离子改性纤维的加热不燃烧烟草薄片涂布负载率达121.69%,而阳离子改性纤维添加量为100%的加热不燃烧烟草薄片涂布负载率达215.58%,与前者相比增加了93.89个百分点.选择添加量为60%(相对于绝干木浆总质量)的阳离子改性纤维用于加热不燃烧烟草薄片基片制备,其基片紧度为0.45 g/cm3,孔隙率达 70.90%,透气度 17.92 µm/(Pa·s),制备的加热不燃烧烟草薄片对涂布液的负载率达154.67%,并具有良好的吸食口感.
Abstract
In this study,cationic modified fibers with positive charge and higher water retention value were used to prepare heat-not-burn re-constituted tobacco sheet substrate,by composite papermaking with bleached wood pulp to improve the absorption performance of the sub-strate.The results showed that the dosage of cationic modified fibers could effectively reduce the tightness of the substrate,improve its ab-sorption performance to the coating solution,and increase the loading ratio of the heat-not-burn reconstituted tobacco to the coating solution.The coating loading ratio of heat-not-burn reconstituted tobacco was 121.69%without cationic modified fiber.Howere,the coating loading ratio of heat-not-burn reconstituted tobacco could reached 215.58%with the doasge of cationic modified fiber was 100%,which increased 93.89 percentage points.The cationic modified fiber was selected to prepare the tobacco sheet substrate with the dosage of 60%.The sub-strate's tightness was 0.45 g/cm3,the porosity was 70.90%,and the air permeability was 17.92 µm/(Pa·s).The loading rate of the prepared heat-not-burn reconstituted tobacco to the coating solution was 154.67%,and the heat-not-burn reconstituted tobacco had good taste.
关键词
阳离子改性纤维/加热不燃烧烟草薄片/吸收性能Key words
cationic modified fibers/heat-not-burn reconstituted tobacco/absorption properties引用本文复制引用
基金项目
河南卷烟工业烟草薄片有限公司合作项目(2021410010340055)
出版年
2024
国家科技期刊平台
NSTL
万方数据