苎麻新型酶-化学联合脱胶工艺研究
Research on a new enzymatic and chemical combined degumming process for ramie
姜楠 1王强 1段旬妍 2钱佳炜 1余圆圆 1周曼 1王平 1王程 3徐苏捷3
作者信息
- 1. 江南大学 纺织科学与工程学院,江苏 无锡 214122
- 2. 黄冈华辰艾麻纺织品有限公司,湖北 黄冈 438000
- 3. 浙江灏宇科技有限公司,浙江 杭州 312369
- 折叠
摘要
苎麻生物酶脱胶具有节能环保、作用条件温和等优势,但单独生物酶处理得到的精干麻存在残胶率偏高,针对这一不足,从强化螯合剂预处理和碱氧后处理角度出发,以残胶率、蓝光白度、束纤维强度、柔软度和润湿性等为评价指标考察苎麻酶法脱胶效果提升.结果表明:在优化螯合剂预处理(螯合剂 5 g/L,90℃保温 1h,浴比1∶15)和碱氧后处理(氢氧化钠 4 g/L,TF-122H稳定剂 3g/L,硅酸钠 2g/L,双氰胺 1 g/L,30%过氧化氢 2 mL/L,98℃保温 2h,浴比 1∶15)条件下,苎麻纤维残胶率可以降至 4.29%,白度达到 63.20%,束纤维强度达到3.55 cN/dtex.与传统化学脱胶工艺相比,新工艺制得的精干麻蓝光白度相近,而束纤维强度、柔软度和润湿性都明显高于传统工艺,残胶率略高.
Abstract
The enzymatic degumming of ramie has advantages such as energy conservation,environmental protection,and mild operating conditions,but there is a disadvantage of high residual gum rate in fine dried hemp.This article starts from the perspective of strengthening chelator pretreatment and alkaline oxygen post-treatment,and evaluates the improvement of ramie enzymatic degumming effect using residual gum rate,blue light whiteness,bundle fiber strength,softness,and wettability as evaluation indicators.The results show that under optimized conditions of chelator pretreatment(chelator 5 g/L,90℃insulation for 1 h,bath ratio 1∶15)and alkaline oxygen post-treatment(sodium hydroxide 4 g/L,TF-122H stabilizer 3 g/L,sodium silicate 2 g/L,dicyandiamide 1 g/L,30%hydrogen peroxide 2 mL/L,98℃insulation for 2 h,bath ratio 1∶15),the residual gum rate of ramie fiber can be reduced to 4.29%,whiteness can reach 63.20%,and bundle fiber strength can reach 3.55 cN/dtex.Compared with the traditional chemical degumming process,the new process produces a similar blue light whiteness for fine and dry hemp,while the strength,softness,and wettability of the bundle fibers are significantly higher than those of the traditional process,but the residual glue rate is slightly higher.
关键词
苎麻纤维/酶脱胶/预处理/碱氧后处理/精干麻Key words
ramie fiber/enzymatic degumming/pretreatment/alkaline oxygen post-treatment/degummed ramie引用本文复制引用
基金项目
国家重点研发计划项目(2021YFC2104000)
出版年
2024
NETL
NSTL
万方数据