Comparison of Detection Methods of Pore Characteristic of Inkjet Paper Coating

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Abstract:

nkjet paper coating is a porous coating getting from a mixture of pigments, adhesives and a small amount of additives by way of coating and drying. Coating structure is defined as the coating thickness, porosity, pore size and its distribution, the surface and internal distribution of coating components. In which, pore characteristic (such as porosity, pore shape, pore size and its distribution) play an important role in the decision of absorption and spreading of ink droplet on inkjet paper. The commonly used detection methods of coating microstructure include image analysis and various physical detection methods. This paper selected 4 inkjet papers, and the two image analysis methods (SEM and AFM) were used to measure the pore characteristic of the testing coating, and characteristics of the two methods were analyzed and compared. And AFM observation method is more suitable for testing pore characteristics of inkjet paper coating, as it could provide more information on the microscopic morphology and coating composition. In the study of the structure of the coating surface, SEM and AFM have their own strengths and complement each other.

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Advanced Materials Research (Volumes 430-432)

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898-904

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January 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Junjie Ji, Yunzhi Chen: Shanghai Paper Vol. 38 (2007), pp.42-46, in Chinese.

Google Scholar

[2] Juanling Sui, Shan Sun: Mining & Metallurgy Vol. 13 (2004), pp.95-98, in Chinese.

Google Scholar

[3] Yaowen Chen, Yuejuan Lin, Haidan Zhang, et. al: Chinese journal of stereology and image analysis Vol. 11 (2006), pp.53-58, in Chinese.

Google Scholar

[4] Rodgers M. R., Yash AR. F. D.: Proceedings of SPIE on Integrated Circuit Metrology, Inspection, and Process Control VI. Vol. 1673 (1992), pp.544-551.

Google Scholar

[5] Bin Liu, Fanqiang Meng, Yongchun Shang: Coating Industry Vol. 2 (2000), pp.58-64, in Chinese.

Google Scholar

[6] Baoyu Wang, Beihai He, Junrong Li, et. al: Paper Science& Technology Vol. 29 (2010), pp.58-64, in Chinese.

Google Scholar

[7] Yu Chen, Ronghua Yan, Yunfei Liu, et. al: Chemical Engineering Vol. 59(2008), pp.2676-2679, in Chinese.

Google Scholar

[8] Cuiyan Liu: Computer and Information Vol. 4 (2009), pp.84-86, in Chinese.

Google Scholar

[9] Cheng H D, Jiang X H, Wang J L, Color image segmentation based on homogram threshold and region merging, Pattern Recognition. 35 (2002) 373-393.

DOI: 10.1016/s0031-3203(01)00054-1

Google Scholar

[10] Cheng H D, Li J: Pattern Recognition Vol. 36 (2003), pp.1545-1562, in Chinese.

Google Scholar

[11] Cuicui Jiang, Ming Li: Computer and Information Vol. 6 (2010), pp.68-70, in Chinese.

Google Scholar

[12] Hui Li, Xiaojian Ji, Yinpeng Wang, et. al: China Surface Engineering Vol. 22 (2009), pp.25-28, in Chinese.

Google Scholar

[13] F.H. Shea, K.L. Tungb, L.X. Konga: Robotics and Computer-Integrated Manufacturing Vol. 24 (2008), p.427–434.

Google Scholar

[14] Jinglei Tai, Guangxue Chen, Qifeng Chen, et. al: ICIS2010 The 31st International Congress on Imaging Science, Beijing. 5 (2010), pp.264-267.

Google Scholar