可动位错引起的电场击穿形核理论
Theory of electric field breakdown nucleation due to mobile dislocations
摘要：
描述了一种模型，其中在高压系统中的电击穿是由阴极中的移动位错种群的随机波动引起的。在这个模型中，位错密度通常是波动的，由于外场的影响，位错密度以有限的概率发生临界转变。有人建议，一旦发生这种转变，移动位错密度将增加确定性，导致电击穿。模型参数化是通过显微镜分析的OFHC铜阴极样品从欧洲核子研究中心CLIC项目，允许创建和耗尽率的移动位错估计作为一个函数的初始物理条件的材料和所施加的电场。我们发现的平均击穿时间和准稳态概率分布的移动位错密度的解析表达式，并验证这些结果，使用Gillespie算法。一个最小二乘算法是用来拟合这些结果与现有的实验数据的依赖性的击穿率上施加的电场的强度和温度。的物理模型的一些假设的变化的影响被认为是，并提出了一些额外的实验来验证该模型，其中包括检查的温度和脉冲长度的影响，以及随时间变化的电场，对击穿率。最后，该模型的应用进行了讨论，包括使用准静态概率分布预测故障，并应用该模型的预测，以改善阴极材料的调理过程。
英文摘要：
A model is described, in which electrical breakdown in high-voltage systems is caused by stochastic fluctuations of the mobile dislocation population in the cathode. In this model, the mobile dislocation density normally fluctuates, with a finite probability to undergo a critical transition due to the effects of the external field. It is suggested that once such a transition occurs, the mobile dislocation density will increase deterministically, leading to electrical breakdown. Model parametrization is achieved via microscopic analysis of OFHC Cu cathode samples from the CERN CLIC project, allowing the creation and depletion rates of mobile dislocations to be estimated as a function of the initial physical condition of the material and the applied electric field. We find analytical expressions for the mean breakdown time and quasistationary probability distribution of the mobile dislocation density, and verify these results by using a Gillespie algorithm. A least-squares algorithm is used to fit these results with available experimental data of the dependence of the breakdown rate on the applied strength of the electric field and on temperature. The effects of the variation of some of the assumptions of the physical model are considered, and a number of additional experiments to validate the model are proposed, which include examining the effects of the temperature and pulse length, as well as of a time-dependent electric field, on the breakdown rate. Finally, applications of the model are discussed, including the usage of the quasistatic probability distribution to predict breakdowns, and applying the predictions of the model to improve the conditioning process of the cathode material.
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