轻涂纸涂层中羧基丁苯胶乳含量的测定  

Determination of the SB-latex Content in Coating Layer of Light Weight Coated Paper

作　　者：赵焕[1] 洪义梅[1] 佟放[1] 刘苇[1] 丁笑天[1] 侯庆喜[1] 

机构地区：[1]天津科技大学天津市制浆造纸重点实验室,天津300457

出　　处：《中国造纸》2013年第7期6-12,共7页China Pulp & Paper

基　　金：天津市科技创新体系及条件平台建设项目(10SYSYJC-28000)的支持

摘　　要：采用衰减全反射傅里叶变换红外光谱(ATR-FTIR)对涂有不同羧基丁苯胶乳含量的轻涂纸表面进行测定,选取羧基丁苯胶乳在波数为2922 cm-1、1028 cm-1、756 cm-1和699 cm-14处特征吸收峰并使用红外光谱软件计算其峰面积,由此得到不同胶乳含量与这4处吸收峰峰面积之间的关系;分别采用多项式曲线拟合(PCF)、偏最小二乘回归(PLS regression)和广义回归神经网络(GRNN)进行建模,并对3种模型的预测效果进行比较。结果表明,轻涂纸涂层中的ATR-FTIR信息可以用来测定轻涂纸涂层中的羧基丁苯胶乳含量,3种预测模型中,GRNN方法具有最佳的预测效果,偏差最小(最大偏差为-3.39%)。In this paper,the styrene-butadiene latex（SB-latex） contents in the coating layer of light weight coated（LWC） paper were measured by using an attenuated total reflectance-Fourier transform infrared spectroscopy（ATR-FTIR）.The peak areas under the specific absorption peaks at 2922 cm-1,1028 cm-1,756 cm-1,and 699 cm-1 were calculated,by using the relative software.So the relation between different contents of SB-latex and the peak areas under those four peaks was obtained.Three different models for predicting the SB-latex content in the coating layer of LWC paper were established by applying the polynomial curve fitting（PCF）,partial least-squares regression（PLS regression）,and generalized regression neural network（GRNN）,respectively.The results showed that the attenuated total reflectance-Fourier transform infrared spectral information of the coating layer of LWC paper can be used to determine the SB-latex content in the coating layer.Among these three methods of predicting the content of SB-latex in the coating layer,the GRNN model has the best predicting effect since it has the minimum error,i.e.,the maximum error is-3.39%.

关 键 词：轻涂纸 羧基丁苯胶乳 ATR-FTIR PCF PLS GRNN 

分 类 号：TS727.3[轻工技术与工程—制浆造纸工程]