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Synthesis and properties of ultrafine YAG powder via low-temperature microwave hydrothermal method
Yue Liu,Jieguang Song,Lin Chen,Huihui Luo,Guojian Lin,Peng Chen,Chenhui Wei,Jingjing Liu 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.4
Yttrium aluminum garnet (YAG) has good optical properties and has been widely used in engineering. The preparation ofconventional YAG powder is costly due to its high synthesis temperature, so lowering the synthesis temperature is the mosteffective way to save cost. The ultrafine oxide composite powder was rapidly synthesized using the microwave hydrothermalmethod at a low temperature. The effect of temperature and its performance. Differential thermal analysis and XRD phaseanalysis showed the mixed solution of Al(NO3)3 and Y(NO3)3 at pH=9 and C(Al3+)=0.42 mol·L−1. SEM, zeta potential, andparticle size analysis revealed that the microwave hydrothermal reaction temperature was 170 oC, and the high-purityultrafine YAG powder was calcined at 928 oC, which was lower than conventional calcination temperature. The synthesizedultrafine spherical YAG powder had a small particle size and a uniform distribution.
Preparation and properties of coated silica/aluminum cermet materials via powder metallurgy method
Jieguang Song,Yue Liu,Chunxiao Wu,Xueqing Yang,Huihui Luo,Chunyan He,Chengbin Li,Haizhen Yang 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.2
Cermet is a combination of metal and ceramic, it exhibits some special properties, so it is one of the most widely usedengineering materials. In this paper, the properties of encapsulated SiO2/Al cermet were prepared by powder metallurgymethod. Results showed that the density of SiO2/Al cermet is increased with an increasing Al content. When the Al contentis high, and the high temperature is sintered, the liquid phase can fully bond the surrounding SiO2 particles to form a relativelycontinuous and dense structure, thereby obtaining a high microstructure density. When the SiO2:Al ratio is increased from 1:1to 1:3, the hardness is gradually increased. The hardness and density of the sample are gradually increased with an increasingmolding pressure. The surface hardness of the cermet is increased first and then decreased with an increasing sinteringtemperature. When the SiO2:Al ratio is 1:3, the holding time is 10 min under molding pressure of 15 MPa, and the sinteringtemperature is 900 °C for 1 h, the surface hardness of the obtained coated SiO2/Al cermet is high, the value is 175.2 HV.
Lu Yi,Wu Jiachuan,Hu Minhui,Zhong Qinghua,Er Limian,Shi Huihui,Cheng Weihui,Chen Ke,Liu Yuan,Qiu Bingfeng,Xu Qiancheng,Lai Guangshun,Wang Yufeng,Luo Yuxuan,Mu Jinbao,Zhang Wenjie,Zhi Min,Sun Jiachen 거트앤리버 소화기연관학회협의회 2023 Gut and Liver Vol.17 No.6
Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.
Jieguang Song,Yue Liu,Chunxiao Wu,Xueqing Yang,Yipeng Gong,Jianzhen Huang,Chunyan He,Huihui Luo,Aixia Chen 한양대학교 세라믹연구소 2020 Journal of Ceramic Processing Research Vol.21 No.1
Cermet application is extensive because it retains the characteristics of ceramic materials and has the advantages of metalmaterials. In this paper, alumina/aluminum cermet materials were prepared through powder metallurgy method. Theinfluence of raw material formula on the properties of alumina/aluminum cermet was investigated on the basis that ceramicmaterials have good wear resistance and high thermal conductivity. Results show that when the mass ratio of alumina toaluminum is 1:3, the prepared cermet samples have excellent properties, highest density, and uniform distribution ofaluminum and alumina. MgO addition exhibits better effect, higher degree of densification, and renders higher hardness andstrength for the sample as compared with SiO2 and Y2O3 addition. The sintered cermet with composite powder prepared viaprecipitation has better properties and higher densities and surface hardness than that prepared via the ball mill method. Therelative density was 97.1%, surface hardness was 875 HV, and electric resistance was 0.0169 Ω·m.