Preparation of ZrB_2-SiC Powders via Carbothermal Reduction of Zircon and Prediction of Product Composition by Back-Propagation Artificial Neural Network  

作　　者：LIU Jianghao DU Shuang LI Faliang ZHANG Haijun ZHANG Shaoweia 刘江昊;DU Shuang;LI Faliang;张海军;张少伟(The State Key Laboratory of Refractories and Metallurgy, Wuhan University of Science and Technology;Refractory Co., Ltd,Wuhan Iron and Steel (Group) Corp.;College of Engineering, Mathematics and Physical Sciences, University of Exeter)

机构地区：[1]The State Key Laboratory of Refractories and Metallurgy,Wuhan University of Science and Technology,Wuhan 430081,China [2]Re-fractory Co.,Ltd,Wuhan Iron and Steel（Group）Corp.,Wuhan 430080,China [3]College of Engineering,Mathematics and Physical Sciences,University of Exeter,Exeter EX4 4QF,UK

出　　处：《Journal of Wuhan University of Technology(Materials Science)》2018年第5期1062-1069,共8页武汉理工大学学报（材料科学英文版）

基　　金：Funded by National Natural Science Foundation of China(Nos.51502212,51672194 and 51472184);Hubei Province Natural Science Foundation of China(No.2018CFB760);Program for Innovative Teams of Outstanding Young and Middle-aged Researchers in the Higher Education Institutions of Hubei Province(No.T201602);Key Program of Natural Science Foundation of Hubei Province(No.2017CFA004)

摘　　要：Phase pure ZrB2-SiC composite powders were prepared after 1 450℃/3 h via carbothermal reduction route,by using ZrSiO4,B2O3 and carbon as the raw materials.The influences of firing temperature as well as the type and amount of additive on the phase composition of final products were detailedly investigated.The results indicated that the onset formation temperature of ZrB2-SiC was reduced to 1 400℃by the present conditions,and oxide additive（including CoSO4·7H2O,Y2O3 and TiO2）was effective in enhancing the decomposition of raw ZrSiO4,therefore accelerating the synthesis of ZrB2-SiC.Moreover,microstructural observation showed that the as-prepared ZrB2 and SiC respectively had well-defined hexagonal columnar and fibrous morphology.Furthermore,the methodology of back-propagation artificial neural networks（BP-ANNs）was adopted to establish a model for predicting the reaction extent（e g,the content of ZrB2-SiC in final product）in terms of various processing conditions.The results predicted by the as-established BP-ANNs model matched well with that of testing experiment（with a mean square error in 10^（-3） degree）,verifying good effectiveness of the proposed strategy.Phase pure ZrB2-SiC composite powders were prepared after 1 450℃/3 h via carbothermal reduction route,by using ZrSiO4,B2O3 and carbon as the raw materials.The influences of firing temperature as well as the type and amount of additive on the phase composition of final products were detailedly investigated.The results indicated that the onset formation temperature of ZrB2-SiC was reduced to 1 400℃by the present conditions,and oxide additive（including CoSO4·7H2O,Y2O3 and TiO2）was effective in enhancing the decomposition of raw ZrSiO4,therefore accelerating the synthesis of ZrB2-SiC.Moreover,microstructural observation showed that the as-prepared ZrB2 and SiC respectively had well-defined hexagonal columnar and fibrous morphology.Furthermore,the methodology of back-propagation artificial neural networks（BP-ANNs）was adopted to establish a model for predicting the reaction extent（e g,the content of ZrB2-SiC in final product）in terms of various processing conditions.The results predicted by the as-established BP-ANNs model matched well with that of testing experiment（with a mean square error in 10^（-3） degree）,verifying good effectiveness of the proposed strategy.

关 键 词：ZrB2-SiC powders carbothermal reduction back-propagation artificial neural networks （BP-ANNs） composition prediction 

分 类 号：TB383.3[一般工业技术—材料科学与工程]