The Experimental Study On Determination Methods Of Coating Weight For Lightweight Coated Paper

With the development of paper industry, more and more attentions have been paid to lightweight coated paper (LWC), since it has many advantages including high-quality, effective-cost and low-drammage, so the amount of import is large. Some institutions, such as customs want to classify the imported LWC and the related tax ratios, so they need to test and analyze the coating weight of LWC imported. However, so far there have been no mature and reliable methods to determine the coating weight of LWC both at home and abroad. It is important to determine the coating weight of LWC.In this paper, the determination methods of coating weight of LWC was studied, two parts including pigments and binder content, respectively, were determined, since they are the two main components of the coating layer. Thermogravimetric analysis (TGA) and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) instrument were used to determine the content of pigment. The weight-loss in TG curve could be used to calculate the content of mineral pigment. The surface infrared spectra of LWC with different calcium carbonate contents in the coating layer were measured by using an ATR-FTIR. The specific absorption peaks of calcium carbonate at 876 cm-1 was then chosen and the peak areas were calculated by using the relative software of OMNIC. So the relation between different calcium carbonate contents and the relative peak areas could be obtained. Two different models for predicting the calcium carbonate content in the coating layer of LWC were established by applying the polynomial curve fitting (PCF) and generalized regression neural network (GRNN), respectively. The results showed that calcium carbonate content calculated by TGA was affected by the filling in base paper of LWC, and the error was large (about 10%). Calcium carbonate content determined by ATR-FTIR was accurate, and the GRNN model had a better predicting effect than the PCF model since it had the minimum error (the maximum error was-3.32%).The surface infrared spectra of LWC with different styrene-butadiene latex (SB-latex) contents in the coating layer were measured by using an ATR-FTIR instrument. The specific absorption peaks at 2922 cm-1,1028 cm-1,756 cm-1, and 699 cm-1 were then chosen and the peak areas were calculated, respectively, by using the relative software of OMNIC. So the relation between different content of SB-latex and the relative peak areas at four spectra could be obtained. Three different models for predicting the SB-latex content in the coating layer of LWC were established by applying the PCF, partial least-squares regression (PLS regression), and GRNN, respectively. The results showed that the ATR-FTIR information in the coating layer of LWC could be used to determine the SB-latex content in the coating layer. The predicting effect of these three models were all good, and among these three methods of predicting the content of SB-latex in the coating layer, the GRNN model had the best predicting effect since it had the minimum error (the maximum error was-3.39%).