The present paper discusses the development of the first and second order model for predicting the chemical etching variables, namely, etching rate, surface roughness and accuracy of advanced ceramics. The first and s...The present paper discusses the development of the first and second order model for predicting the chemical etching variables, namely, etching rate, surface roughness and accuracy of advanced ceramics. The first and second order etching rate, surface roughness and accuracy equations were developed using the Response Surface Method (RSM). The etching variables included etching temperature, etching duration, solution and solution concentration. The predictive models’ analyses were supported with the aid of the statistical software package – Design Expert (DE 7). The effects of the individual etching variables and interaction between these variables were also investigated. The study showed that predictive models successfully predicted the etching rate, surface roughness and accuracy readings recorded experimentally with 95% confident interval. The results obtained from the predictive models were also compared with Multilayer Perceptron Artificial Neural Network (ANN). Chemical Etching variables predictive by ANN were in good agreement with those with those obtained by RSM. This observation indicated the potential of ANN in predicting chemical etching variables thus eliminating the need for exhaustive chemical etching in optimization.展开更多
Si3N4/BN nanocomposite powders with the mi-crostructure of the micro-sized a-Si3N4 particles coated with nano-sized BN particles were synthesized via the chemical reaction of boric acid, urea, and a-Si3N4 powder in a ...Si3N4/BN nanocomposite powders with the mi-crostructure of the micro-sized a-Si3N4 particles coated with nano-sized BN particles were synthesized via the chemical reaction of boric acid, urea, and a-Si3N4 powder in a hydro-gen gas. The results of XRD, TEM, and selected area elec-tron diffraction showed that amorphous BN and a little amount of turbostratic BN(t-BN) were coated on Si3N4 parti-cles as the second phase after reaction at 1100℃. After re-heating the composite powders at 1450℃ in a nitrogen gas, the amorphous and turbostratic BN is transformed into h-BN. These nanocomposite powders can be used to prepare Si3N4/BN ceramic composites by hot-pressing at 1800℃, which have perfect machinability and can be drilled with normal metal tools.展开更多
以裂解产物为Si3N4和BN混合物的聚硅硼氮烷(polyborosilazane,PSBZ)为先驱体,通过先驱体浸渍裂解(precursor infiltration and pyrolysis,PIP)工艺,制备了三维编织石英纤维增强Si3N4和BN混合物(3DSiO2f/氮化物)复合材料。对材料的致密...以裂解产物为Si3N4和BN混合物的聚硅硼氮烷(polyborosilazane,PSBZ)为先驱体,通过先驱体浸渍裂解(precursor infiltration and pyrolysis,PIP)工艺,制备了三维编织石英纤维增强Si3N4和BN混合物(3DSiO2f/氮化物)复合材料。对材料的致密化、力学性能、热物理性能、微观形貌进行了分析和研究。因为先驱体与石英纤维浸润性好,陶瓷产率高,所以先驱体浸渍裂解法制备3D SiO2f/氮化物复合材料致密化较快。当浸渍-裂解4次后,材料的密度增加到1.71g/cm3,其室温～200℃的热导率小于1.2W/m·K,而其弯曲强度、弹性模量分别为130.2MPa,22.6GPa,此时断口有明显的纤维拔出现象,呈非脆性断裂。展开更多
文摘The present paper discusses the development of the first and second order model for predicting the chemical etching variables, namely, etching rate, surface roughness and accuracy of advanced ceramics. The first and second order etching rate, surface roughness and accuracy equations were developed using the Response Surface Method (RSM). The etching variables included etching temperature, etching duration, solution and solution concentration. The predictive models’ analyses were supported with the aid of the statistical software package – Design Expert (DE 7). The effects of the individual etching variables and interaction between these variables were also investigated. The study showed that predictive models successfully predicted the etching rate, surface roughness and accuracy readings recorded experimentally with 95% confident interval. The results obtained from the predictive models were also compared with Multilayer Perceptron Artificial Neural Network (ANN). Chemical Etching variables predictive by ANN were in good agreement with those with those obtained by RSM. This observation indicated the potential of ANN in predicting chemical etching variables thus eliminating the need for exhaustive chemical etching in optimization.
基金the National Natural Science Foundation of China (Grant No. 50072017)
文摘Si3N4/BN nanocomposite powders with the mi-crostructure of the micro-sized a-Si3N4 particles coated with nano-sized BN particles were synthesized via the chemical reaction of boric acid, urea, and a-Si3N4 powder in a hydro-gen gas. The results of XRD, TEM, and selected area elec-tron diffraction showed that amorphous BN and a little amount of turbostratic BN(t-BN) were coated on Si3N4 parti-cles as the second phase after reaction at 1100℃. After re-heating the composite powders at 1450℃ in a nitrogen gas, the amorphous and turbostratic BN is transformed into h-BN. These nanocomposite powders can be used to prepare Si3N4/BN ceramic composites by hot-pressing at 1800℃, which have perfect machinability and can be drilled with normal metal tools.
文摘以裂解产物为Si3N4和BN混合物的聚硅硼氮烷(polyborosilazane,PSBZ)为先驱体,通过先驱体浸渍裂解(precursor infiltration and pyrolysis,PIP)工艺,制备了三维编织石英纤维增强Si3N4和BN混合物(3DSiO2f/氮化物)复合材料。对材料的致密化、力学性能、热物理性能、微观形貌进行了分析和研究。因为先驱体与石英纤维浸润性好,陶瓷产率高,所以先驱体浸渍裂解法制备3D SiO2f/氮化物复合材料致密化较快。当浸渍-裂解4次后,材料的密度增加到1.71g/cm3,其室温～200℃的热导率小于1.2W/m·K,而其弯曲强度、弹性模量分别为130.2MPa,22.6GPa,此时断口有明显的纤维拔出现象,呈非脆性断裂。
