Influence Mechanism of Micro Grain-boundary Parameters to the Electrical Properties of ZnO Varistor

ZnO varistors exhibit excellent nonlinear voltage–current characteristics and substantial energy capacity, enabling them to absorb impulse energy during power system overvoltages and thus protect the electrical equipment. The nonlinear behavior of ZnO varistors is attributed to the double Schottky barrier structure at their grain boundaries. The parameters of these micro-grain boundaries play a decisive role in determining the macroscopic electrical performance of ZnO varistors. However, few studies have investigated the influence of micro grain-boundary structural parameters on the macroscopic electrical properties of ZnO varistors. This study utilizes a Voronoi network and an improved grain boundary partitioning model to simulate and calculate how micro grain-boundary parameters, such as grain donor density, grain boundary surface state density, and grain boundary partitioning parameters, affect the macroscopic electrical properties of ZnO varistors. The development process of high-performance ZnO varistors is considered a multi-variable and multi-objective problem. The optimization targets and variables are classified based on whether any optimization variable has similar influences on the optimization targets and whether the variable affects both types of optimization targets equally. This classification reveals the influence mechanism of micro grain boundaries on electrical properties. By reasonably classifying optimization variables and objectives, this study simplifies complex multi-variable and multi-objective problems. It formulates step-by-step optimization strategies based on the characteristics of classified variables and objectives, thus improving the performance of ZnO varistors. This approach considerably enhances varistor performance at the microscopic physical layer, which is crucial for the development of high-performance varistors.