Application of Modified Calcium Sulfate Whisker in Methyl Vinyl Silicone Rubber Composites

2012 ◽  
Vol 20 (5) ◽  
pp. 453-462 ◽  
Author(s):  
Wang Jincheng ◽  
Tang Lijuan ◽  
Wu Ding ◽  
Guo Xi ◽  
Hao Wenli
2012 ◽  
Vol 125 (5) ◽  
pp. 3456-3462 ◽  
Author(s):  
Hua Zou ◽  
Shani Yan ◽  
Yebin Sun ◽  
Liqun Zhang ◽  
Ming Tian

RSC Advances ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 452-461
Author(s):  
Yi Han ◽  
Xian Zhou ◽  
Li Lei ◽  
Huiqun Sun ◽  
Zhiyuan Niu ◽  
...  

In order to improve the utilization of nanoscale zero-valent iron (nZVI) in activating persulfate (PS), a composite material of nZVI/CSW with nZVI supported on calcium sulfate whiskers (CSWs) was synthesized in this study.


2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Young-Doo Kwon ◽  
Seong-Hwa Jun ◽  
Ji-Min Song

Most machines and instruments constantly require elastomeric materials like rubber for the purposes of shock absorption, noise attenuation, and sealing. The material properties and accurate lifetime prediction of rubber are closely related to the quality of machines, especially their durability and reliability. The properties of rubber-like elastomers are influenced by ambient conditions, such as temperature, environment, and mechanical load. Moreover, the initial properties of rubber gaskets must be sustained under working conditions to satisfy their required function. Because of its technical merits, as well as its low cost, the highly accelerated life test (HALT) is used by many researchers to predict the long-term lifetime of rubber materials. Methyl vinyl silicone rubber (VMQ) has recently been adopted to improve the lifetime of automobile radiator gaskets. A four-parameter method of determining the recovery ability of the gaskets was recently published, and two revised methods of obtaining the recovery were proposed for polyacrylate (ACM) rubber. The recovery rate curves for VMQ were acquired using the successive zooming genetic algorithm (SZGA). The gasket lifetime for the target recovery (60%) of a compressed gasket was computed somewhat differently depending on the selected regression model.


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