偏高岭土
材料科学
陶瓷
喷嘴
表面粗糙度
烧结
收缩率
表面光洁度
复合材料
墨水池
机械工程
工程类
粉煤灰
作者
Ming Wu,Fuchu Liu,Yuxiao Lin,Miao Wang,Shilin Zhou,Chi Zhang,Yingpeng Mu,Guangchao Han,Liang Hao
标识
DOI:10.1016/j.cjmeam.2023.100098
摘要
Kaolin/metakaolin-insulating ceramic components fabricated using direct ink writing (DIW) have important application prospects in architecture and aerospace. The accuracy of the entire process including the forming and sintering accuracy of ceramics greatly limits the application scope, and high-accuracy ceramic samples can meet the usage requirements in many scenarios. The orthogonal experiment was designed with four process parameters, including nozzle internal diameter, filling rate, printing layer height/nozzle internal diameter, and printing speed, to investigate the evolution of the DIW forming accuracy, sintering shrinkage rate and surface roughness of metakaolin-based ceramics with different process parameters. The influence of each process parameter and its mechanism were analyzed to obtain the DIW parameters for high-accuracy metakaolin ceramics. Multiple linear regression models between the dimensional change rate, surface roughness, and process parameters of the ceramic samples were established and validated. The results show that comprehensively considering the forming accuracy of the ceramic green bodies, sintering shrinkage rate and surface roughness, the optimal DIW process parameters were a 0.41 mm nozzle internal diameter, 100% filling rate, 50% printing layer height/nozzle internal diameter, and a 15 mm/s printing speed. Multiple linear regression models were developed for the process parameters and the printing accuracy, sintering shrinkage rate and surface roughness. The error rates between the theoretical results obtained by substituting the optimal process parameters into the multiple linear regression models and the actual results obtained by printing the samples with the optimal parameters were extremely small, all less than 0.8%. This verified the correctness and predictability of the multiple linear regression models. This work provides a reference basis for rapid fabrication of high-accuracy ceramics via DIW and accuracy prediction with different process parameters.
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