竹材的超声波处理及生物酶催化聚合研究

王承, 傅佳佳*

化工新型材料 ›› 2020, Vol. 48 ›› Issue (7) : 256 -260.

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化工新型材料 ›› 2020, Vol. 48 ›› Issue (7) : 256-260. DOI: 10.19817/j.cnki.issn 1006-3536.2020.07.058
开发与应用

竹材的超声波处理及生物酶催化聚合研究

    王承, 傅佳佳*
作者信息 +

Ultrasonic treatment and enzymatic polymerization of bamboo

  • Wang Cheng, Fu Jiajia
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文章历史 +
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摘要

采用超声波-漆酶系统联合处理竹材制备高聚物,在超声波水浴、超声波萃取条件下依次加入漆酶,对煮沸预处理所得竹粉萃取原液进行催化,并探寻漆酶聚合液应用于纺织生产的可行性。结果表明,超声波萃取、超声波水浴处理120min后,漆酶酶活性分别降为初始值的82%和83.75%,剩余酶活性仍较高。同竹粉萃取原液相比,漆酶催化聚合所得反应液中OH含量明显下降,反应前后颜色变化明显。核磁共振氢谱分析表明,芳香族峰、烯丙基/OH峰区域明显减弱或消失,证实了竹材中萃取物的有效聚合。漆酶聚合物对棉织物和毛织物有一定的染色效果,后续应进一步增强漆酶的聚合效果,改善其在织物中的应用。

Abstract

Producing polymer from bamboo based on the ultrasonic-laccase system was mainly focused,and explored its application on textile industry.Laccase was used to catalyze the original bamboo extraction after boiling pretreatment through ultrasonic bath and ultrasonic probe respectively.The results shown that the residual enzyme activities of ultrasonic probe and ultrasonic bath treated for 120min decreased to 82% and 83.75% of the initial value,remaining a high value of the enzyme activity.Compared with the original bamboo extraction,the OH content in the laccase-catalyzed polymeric liquids decreased significantly with an obvious color changes after reaction.The 1H-NMR test indicated that the aromatic peak and the allyl/OH peak regions were obviously weakened or disappeared,confirming an efficient polymerization of the extracts.The polymers obtained had a certain dyeing effect on the cotton and wool fabric,and subsequent research can be further optimized to enhance the polymerization effect and improve its practical textile application.

关键词

竹材 / 超声波处理 / 漆酶 / 聚合物 / 纺织染色

Key words

bamboo / ultrasonic treatment / laccase / polymer / textile dying

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竹材的超声波处理及生物酶催化聚合研究[J]. 化工新型材料, 2020, 48(7): 256-260 DOI:10.19817/j.cnki.issn 1006-3536.2020.07.058

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基金资助

国家自然科学基金(31470509、31201134);“政府间国际科技创新合作”重点专项(2016YFE0115700);江苏省产学研前瞻性研究项目(BY2016022-23);江苏省研究生科研与实践创新计划项目(KYCX18_1837);江苏高校品牌建设工程资助项目(PPZY2015B147);中央高校基本科研业务费专项资金资助(JUSRP51622A);中国博士后科学基金资助项目(2019T120390);江苏省博士后科研资助计划(2018K018A)

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