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Preparation of ZrB_2-SiC Powders via Carbothermal Reduction of Zircon and Prediction of Product Composition by Back-Propagation Artificial Neural Network 被引量:1
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作者 LIU Jianghao DU Shuang +2 位作者 LI Faliang ZHANG Haijun ZHANG Shaoweia 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS 2018年第5期1062-1069,共8页
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 ... 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. 展开更多
关键词 ZrB2-SiC powders carbothermal reduction back-propagation artificial neural networks (BP-ANNs) composition prediction
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