取向硅钢氮化与AlN形成的模拟计算
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摘要
本世纪30年代初Goss.N.P发现冷轧变压器硅钢片具有{110}<001>晶粒取向后,磁性能可大幅上升,立即引起人们的注意并开始广泛研究。因此,如何在取向硅钢中获得更多{110}<001>取向便成为研究热点。
     研究中发现{110}<001>织构是一个利用析出的第二相质点二次再结晶的问题。也就是说二次再结晶过程中,由于硅钢中沉淀析出弥散分布的第二相夹杂物有效抑制了初次再结晶的正常晶粒的生长,为{110}<001>取向晶粒的迅速长大提供了条件。因此,如何提高细小弥散的抑制剂数量便成为核心问题之一,而对于生产高牌号的取向硅钢,多数使用AlN+MnS抑制剂方案,如何提高取向硅钢二次再结晶之前抑制剂的数量便成为一个问题,近年来研究发现二次再结晶之前进行渗氮处理可以有效提高AlN生成量,因此本工作主要通过对各种国内外渗氮模型进行分析,建立适于取向硅钢渗氮过程的扩散及动力学模型。从气氛分解、吸附、扩散、渗入,形核几部分模型入手,辅以Fe-Al-Mn三元系合金参数、平衡状态的固溶积和经典形核理论,建立出计算结果与实验相吻合的模型。并对其进行简要误差分析(误差小于7.5×10-7g)。导出了不同温度下氮原子的有效扩散系数,建立了适用于取向硅钢渗氮计算的有效的扩散系数与温度间的关系及氮原子的扩散激活能。渗氮气氛一定的情况下,渗入氮含量随温度增加而增大。温度升高时,氮浓度梯度增加。利用所建模型可以有效对取向硅钢氮化过程中AlN扩散形核进行计算。
The finding of great enhancement in magnetic property of Cold-Rolling Orientated Silicon Sheet quickly allured flourish abroad research enthusiasm since there would be benefit to render{110}<001>texture in silicon steel sheet. So how to acquire more{110}<001>texture in silicon sheet is currently under academic spotlight.
     Recent research discover that the{110}<001>texture is a problem which should utilize second phase particles to control secondary recrystallization; to be in short, the key factor to restrain recrystallization is particles which precipitated from dispersion distribution inhibitors, the driving force coming along with this procedure. By consideration of the critical factor of inhibitor in manufacturing of silicon sheets, how to increase amount of inhibitor of AIN in fabrication of grain-oriented steel is coming as a crux. Many references state that nitrding process may enhance amount of AIN, but there are still too few relevant references to browse specific discussion in this affairs with numerical calculation. So the major in this thesis is taking analysis about nitrding models all round, construct proper model to cater our demand in diffusion kinetic, atmosphere decomposition, adsorption and nucleation interdisciplinary, getting a company with phrase diagram of the Fe-Al-Mn, decholesterinization volume and classic nucleation theory, by using above mentioned, we can induct agreeable model, testing and rejoining its error (error parameter less than 7.5×10-7g). It is also a convenient for us to inducing the effective diffusion coefficient in nitrogen and its connection between nitrogen coefficient and temperature along with the relation in diffusion activation energy. From that we concluded that with finite temperature, the amount of nitrogen increased with enhancing of temperature, the concentration gradient will be aggrandizing with slope. It would be very effective, if these models which were established in this thesis could be utilized and applied in manufacturing process due to nitrding process for silicon sheet.
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