Multi-Objective Optimization for Through-Silicon via Structure Considering Thermomechanical Reliability and Electrical Performance

The rapid advancement of high-performance computing has spurred growing demand for miniaturized, high-density, high-power, and highly reliable electronic packaging. Through-silicon via (TSV), as a pivotal technology enabling high-density integrated packaging, achieves vertical interconnection that reduces signal latency and power consumption while substantially improving system integration. However, inherent challenges persist due to coefficient of thermal expansion mismatches among heterogeneous materials in TSV and parasitic effects introduced by high-density TSV arrays, leading to critical concerns regarding thermomechanical reliability and signal integrity. This study focuses on TSV structures, investigating their thermomechanical reliability and electrical performance. First, the macro–micro model of 2.5D package structure was established to address cross-scale challenges based on Representative Volume Element (RVE) homogenization and sub-model technique. Then, an equivalent circuit model integrating transmission line network theory was developed and validated through full-wave electromagnetic simulations using S-parameter analysis to analyze signal transmission characteristics. Finally, by introducing an improved multi-objective grasshopper algorithm, the structural parameters of TSV are co-optimized using a genetic algorithm back propagation network (GA-BP) and an improved multi-objective grasshopper algorithm (IMOGOA) to enhance both thermomechanical reliability and electrical characteristics simultaneously. The proposed approach offers a practical and effective solution for improving the reliability and performance of high-density integrated packaging, providing valuable insights for future packaging design and optimization.