(Peer-Reviewed) Effect of SiC Particle Size on Properties of SiC Porous Ceramics
Xiaohong Xu 徐晓虹, Xing Liu 刘星, Jianfeng Wu 吴建锋, Sitong Ma, Shaoheng Liu, Tiantian Chen
State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan, 430070, China
中国 武汉 武汉理工大学 硅酸盐建筑材料国家重点实验室
Abstract
We used different SiC particle size as raw materials and via reaction bonding technique to prepare porous SiC membrane supports. The phase composition, microstructure, bending strength, open porosity, and pore size distribution were investigated as a function of SiC particle size and firing temperature. It is found that the reduction of SiC particle size not only dramatically enhances the bending strength of porous SiC membrane supports, but also slightly reduces the firing temperature duo to smaller SiC particle with higher specific surface area and higher reaction activity.
Besides, the open porosity and pore size distribution are dependent on the firing temperature, but insensitive to the SiC particle size due to the pore related characters mainly controlled by the binder. The bending strength increases with the increasing of the firing temperature and with the decreasing of SiC particle size. When the firing temperature was 1 500 °C and SiC average particle size was 447.75 µm, the optimal performance were achieved, the bending strength was 15.18 MPa, the open porosity was 36.02 %, the pore size distributed at 3.09–112.47 µm, and the mean pore size was 14.16 µm.
A 4096-element 3D-integrated Si-SiN optical phased array for high-power coherent LiDAR
Han Wang, Weimin Xie, Xin Yan, Jiaqi Li, Youxi Lu, Ping Jiang, Feng Li, Kai Jin, Xu Yang, Jiali Jiang, Keran Deng, Weishuai Chen, Jing Luo, Li Jin, Junbo Feng, Kai Wei
Opto-Electronic Technology
2026-03-20
High-speed and large-capacity visible light communication for 6G: advances and perspectives
Nan Chi, Zhilan Lu, Fujie Li, Haoyu Zhang, Yunkai Wang, Xinyi Liu, Zhiwu Chen, Zhe Feng, Zhuoran Hu, Zhixue He, Ziwei Li, Chao Shen, Junwen Zhang
Opto-Electronic Technology
2026-03-20
Holotomography-driven learning unlocks in-silico staining of single cells in flow cytometry by avoiding fluorescence co-registration
Daniele Pirone, Giusy Giugliano, Michela Schiavo, Annalaura Montella, Martina Mugnano, Vincenza Cerbone, Maddalena Raia, Giulia Scalia Ivana Kurelac, Diego Luis Medina, Lisa Miccio Mario Capasso, Achille Iolascon, Pasquale Memmolo, Pietro Ferraro
Opto-Electronic Science
2026-02-25