Mechanical properties and thermal conductivity of a temperature resistance hollow glass microspheres/borosilicate glass buoyance material

被引:46
作者
Ren, Sue [1 ]
Liu, Jiachen [1 ]
Guo, Anran [1 ]
Zang, Wenjie [1 ]
Geng, Haitao [1 ]
Tao, Xin [1 ]
Du, Haiyan [1 ]
机构
[1] Tianjin Univ, Sch Mat Sci & Engn, Minist Educ, Key Lab Adv Ceram & Mech Technol, Tianjin 300072, Peoples R China
来源
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING | 2016年 / 674卷
基金
中国国家自然科学基金;
关键词
Hollow glass microspheres; Borosilicate glass; Mass ratio; Thermal conductivity; Mechanical properties; Temperature resistance; MATRIX COMPOSITES; POROUS ZIRCONIA; CERAMICS; FOAMS; MICROSPHERES; STRENGTH;
D O I
10.1016/j.msea.2016.08.014
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
A temperature resistance buoyancy material was fabricated through a tert-butyl alcohol gelcasting process with borosilicate glass (BG) and hollow glass microspheres (HGMs) as the matrix and filler, respectively. The effects of the mass ratio of HGMs to BG and sintering temperature on the microstructure, thermal conductivity, and mechanical properties of the composite were studied. The results show that HGMs were bonded together by the BG, and the sample sintered at 750 degrees C exhibited a broad pore size distribution, from several microns to more than one hundred microns. The thermal conductivity experimental values of all the samples were less than that of Hashin-Shtrikman upper bound (HS+) prediction but agreed well with that predicted from effective medium percolation theory. The relationship between compressive strength and relative density was predicted by the Gibson-Ashby model, with the calibration factor phi below 0.7. Young's modulus values obtained from the experiment were below that of HS+ prediction. The modulus values of the four types of samples sintered at 650 degrees C agreed well with the Pabst model prediction, while the values of the samples sintered at 700 degrees C and 750 degrees C were distributed in a zone between Ashby-Gibson model and HS+ prediction. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:604 / 614
页数:11
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