Mechanical behavior of sintered metallic interconnects in electrical packaging: From experimental characterization to multiscale modeling

Sintered Ag and Cu materials have emerged as key interconnect technologies for next-generation high-temperature power electronics owing to their excellent thermal conductivity, electrical conductivity, and high-temperature reliability. However, their long-term reliability is often limited by fracture and damage evolution within porous and microstructurally heterogeneous bonding layers. Unlike dense metals, fracture in sintered materials is governed not only by the intrinsic properties of the metallic phase but also by the morphology and connectivity of sintering necks, residual pores, grain boundaries, interfaces, oxidation, and service-induced microstructural evolution. This review provides a comprehensive overview of recent advances in understanding fracture behavior in sintered Ag and Cu-based interconnects. Macroscopic mechanical tests, including tensile, shear, thermal cycling, power cycling, and fatigue testing, are discussed in relation to bonding strength, failure modes, and reliability degradation. Microscale characterization techniques, such as nanoindentation, micropillar compression, micro-tensile testing, and micro-cantilever bending, are reviewed for their ability to reveal local deformation mechanisms, pore collapse, neck failure, strain localization, and crack propagation. Particular attention is given to micro-cantilever testing as a direct approach for measuring local fracture toughness and distinguishing cohesive fracture within porous sintered layers from interface-controlled failure. Furthermore, multiscale simulation approaches, including molecular dynamics, crystal plasticity, phase-field modeling, cohesive-zone modeling, and finite-element analysis, are summarized to illustrate fracture processes from atomic-scale neck rupture to package-level reliability. Finally, future research directions are outlined, including realistic three-dimensional pore–neck reconstruction, reliability-oriented fracture characterization after aging and cyclic loading, oxidation-aware modeling of Cu-based systems, and the integration of physics-based simulations with data-driven and AI-assisted approaches for predictive reliability assessment.