多因素耦合作用下合成β-sialon材料的工艺优化

PROCESS OPTIMIZATION FOR SYNTHESIS OF βSIALON MATERIALS UNDER MULTI-VARIABLE COUPLING PARTICIPATION

以粘土矿物为主要原料,采用碳热还原氮化工艺制备出高品质βsialon陶瓷粉体,并对多因素耦合状态下材料合成的工艺优化,微结构与相组成以及热力学反应机理作了系统研究。理论分析与实验结果均表明:随着合成温度的增加,产物中物相经历了O′,X相(中间杂相)→β相→15R,12H的sialon多型体与Si3N4和AlN的一系列相转变,导致合成工艺的复杂性。正交设计实验结果分析表明:控制保温时间和合成温度,是获得高含量长柱状βsialon的有效途径;通过模式识别能快速寻找出性能优化区域,1500℃保温5h可以获得单一sialon相。结合逆映照与人工神经网络技术,可对所需要的新工艺参数进行预报。

High-quality β-sialon ceramic powders were synthesized by carbothermal reduction nitridation (CRN) using clay mineral as primary raw materials. The thermodynamic reaction mechanism, phase composition and microstructure of the materials, as well as the optimization of its process under multi-variable coupling participation were investigated. Both theoretical analysis and experimental results indicate that the phases in samples during heat treatment with the increase of sintering temperature will transform from any impurity phases including O' phase and X phase to β phase, and from β phase even to other high-temperature nitride phase involving 15 R, 12 H-sialon, and Si3N4, AlN. So it may result in the complexity in designing for optimal synthesized process. The analysis of orthogonal test indicates that the obtaining of high content of β-sialon with elongated grains depends significantly on both the holding time and sintering temperature. The optimizing zone of performance can be rapidly found by pattern recognition. The 100% sialon phase material is obtained by sintering at 1500°C for 5 h. Based on inverse mapping and artificial neural network, the newly required parameter and its relevant performance can reasonably be predicted.