CAJ | 학술논문

为了获取铝电解碳素阴极材料的蠕变数据和Burgers 模型参数，在965℃及电解状态下，对现行工业中使用的3种铝电解碳素阴极材料(半石墨质、全石墨质和石墨化)进行单轴压缩蠕变实验，采用Burgers 模型对阴极材料黏弹性行为进行分析。利用Origin8.5软件对Burgers模型参数进行拟合，得到碳素阴极材料的黏弹性方程。结果表明：Burgers模型能较好地反映碳素阴极材料在单轴压缩应力作用下的黏弹特性，阴极材料石墨化程度越高， Burgers模型参数E 1、E 2、η2和η1值越大，材料的抗蠕变能力越强。在电解过程中，钠和电解质破坏阴极材料结构， Burgers模型参数E 1、E 2、η2和η1值变小，材料的抗蠕变能力变差。所获结果可为掌握阴极材料在外力作用下的蠕变规律、实现对电解槽生产运行过程中阴极变形的调控和电解槽寿命预测提供技术参考。
위료획취려전해탄소음겁재료적연변수거화Burgers 모형삼수，재965℃급전해상태하，대현행공업중사용적3충려전해탄소음겁재료(반석묵질、전석묵질화석묵화)진행단축압축연변실험，채용Burgers 모형대음겁재료점탄성행위진행분석。이용Origin8.5연건대Burgers모형삼수진행의합，득도탄소음겁재료적점탄성방정。결과표명：Burgers모형능교호지반영탄소음겁재료재단축압축응력작용하적점탄특성，음겁재료석묵화정도월고， Burgers모형삼수E 1、E 2、η2화η1치월대，재료적항연변능력월강。재전해과정중，납화전해질파배음겁재료결구， Burgers모형삼수E 1、E 2、η2화η1치변소，재료적항연변능력변차。소획결과가위장악음겁재료재외력작용하적연변규률、실현대전해조생산운행과정중음겁변형적조공화전해조수명예측제공기술삼고。
In order to obtain the creep data and Burgers model parameters for various industrial cathode products, uniaxial compression creep tests were carried out using a modified Rapoport equipment for carbon cathode materials under high temperature (965 ℃) and electrolysis conditions. The testing samples were taken from three typical industrial cathode blocks: semi-graphitic, full graphitic and graphitized carbon products. The viscoelasticity of the cathode materials was analyzed separately with Burgers model. After fitting the model parameters with Origin8.5 software, the constitutive equation of carbon cathode viscoelasticity was obtained. The results indicate that Burgers model can well reflect the viscoelasticity of the carbon cathodes. And the higher the graphitization of cathode materials is, the larger the Burgers model parameters E1, E2, η1 and η2 are, and the stronger the resistance to the creep deformation is. As the cathode material structure is damaged by the metallic sodium and the electrolyte, the Burgers model parameters E1, E2,η1 andη2 become smaller, and the resistance to the creep deformation of the cathode material gets worse. The obtained data will be useful for understanding the creep rule and better quality control in cathode deformation and the cell service life prediction in the production.