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<p>The persistent reliance on conventional ZnO–Bi₂O₃ varistor systems has increasingly revealed fundamental limitations that constrain their deployment in modern power infrastructure, particularly concerning thermal volatilization, environmental sustainability, and operational temperature ceilings. This comprehensive review systematically evaluates emerging non-bismuth metal oxide varistor architectures, providing a critical comparative framework across praseodymium-, barium-, tin-, and tungsten-oxide-based ceramic platforms. Through rigorous analysis of structure–property relationships, we establish quantitative performance boundaries for each material class, demonstrating that praseodymium-doped ZnO systems achieve nonlinearity coefficients exceeding 60 while extending thermal tolerance to 170&#xa0;°C—a 36% improvement over bismuth-based counterparts. Our investigation reveals that SnO₂-based compositions deliver breakdown field strengths of 300–800&#xa0;V/mm coupled with suppressed leakage currents, whereas BaTiO₃ ferroelectric varistors exhibit superior frequency-dependent stability for alternating current applications. The WO₃ platform enables precisely controlled low-voltage switching thresholds unattainable in conventional systems. Advanced processing methodologies, including spark plasma sintering and controlled-atmosphere protocols, are critically assessed for their impact on microstructural homogeneity and reproducibility. Through correlation matrix analysis, we identify inherent performance trade-offs—notably the inverse relationship between breakdown voltage and nonlinearity coefficient—and establish rational design criteria for application-specific optimization. Integration of density functional theory predictions with machine learning-assisted materials screening demonstrates predictive accuracy exceeding 90% for electrical property estimation. This synthesis of compositional engineering, nanostructural manipulation, and computational guidance provides a unified framework for next-generation varistor development, addressing both regulatory compliance demands and the specialized performance requirements of renewable energy systems, electric vehicle power electronics, and wide-bandgap semiconductor protection circuits.</p>

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Comparative analysis of nonbismuth metal oxide varistor compositions and performance characteristics

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月6日

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  • Arash Vaghef-Koodehi,
  • Yaser Bahari

摘要

The persistent reliance on conventional ZnO–Bi₂O₃ varistor systems has increasingly revealed fundamental limitations that constrain their deployment in modern power infrastructure, particularly concerning thermal volatilization, environmental sustainability, and operational temperature ceilings. This comprehensive review systematically evaluates emerging non-bismuth metal oxide varistor architectures, providing a critical comparative framework across praseodymium-, barium-, tin-, and tungsten-oxide-based ceramic platforms. Through rigorous analysis of structure–property relationships, we establish quantitative performance boundaries for each material class, demonstrating that praseodymium-doped ZnO systems achieve nonlinearity coefficients exceeding 60 while extending thermal tolerance to 170 °C—a 36% improvement over bismuth-based counterparts. Our investigation reveals that SnO₂-based compositions deliver breakdown field strengths of 300–800 V/mm coupled with suppressed leakage currents, whereas BaTiO₃ ferroelectric varistors exhibit superior frequency-dependent stability for alternating current applications. The WO₃ platform enables precisely controlled low-voltage switching thresholds unattainable in conventional systems. Advanced processing methodologies, including spark plasma sintering and controlled-atmosphere protocols, are critically assessed for their impact on microstructural homogeneity and reproducibility. Through correlation matrix analysis, we identify inherent performance trade-offs—notably the inverse relationship between breakdown voltage and nonlinearity coefficient—and establish rational design criteria for application-specific optimization. Integration of density functional theory predictions with machine learning-assisted materials screening demonstrates predictive accuracy exceeding 90% for electrical property estimation. This synthesis of compositional engineering, nanostructural manipulation, and computational guidance provides a unified framework for next-generation varistor development, addressing both regulatory compliance demands and the specialized performance requirements of renewable energy systems, electric vehicle power electronics, and wide-bandgap semiconductor protection circuits.