The rapid proliferation of artificial intelligence (AI) servers and high-performance computing systems has significantly elevated the technical and reliability requirements for multilayer ceramic capacitors (MLCCs). In such systems, MLCCs are critical passive components that must deliver high capacitance, fast transient response, and robust insulation performance under high temperature, voltage, and current density. This review examines the material, structural, and process innovations that underpin MLCC performance in AI applications. Key topics include the development of ultrathin dielectric layers (<0.5 μm), rare-earth doped BaTiO₃-based dielectrics with enhanced DC bias stability, and core-shell microstructures designed for temperature and field resilience. The paper also explores insulation degradation mechanisms―such as vacancydriven conduction and demixing―and advanced reliability assessment methodologies, including HALT, TSDC, and the tipping point framework. Comparisons with automotive-grade MLCCs highlight the unique requirements of AI systems, such as ultraminiaturization, high volumetric efficiency, and ppm-level field failure rates. Finally, the review discusses emerging trends in MLCC technology, including particle engineering, interface stabilization, and advanced lamination techniques, and provides insight into the future direction of capacitor development tailored to AI data center environments.

Citations

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  Shuyan Huang, Xinjie Wang, Mengjian Xiao, Xu Cheng, Xiaohui Wang
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  Won-Su Lee, Jong Kyu Lee, Moon-Taek Cho, Jung Rag Yoon
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• Manufacturing Process Optimization of Oxide-Based Multilayer Ceramic Batteries Using Multilayer Ceramic Processing Technologies
  Won-Su Lee, Jong Kyu Lee, Jung Rag Yoon
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