Reliability of Emerging Bonded Interface Materials for Large-Area Attachments

Conventional thermal interface materials (TIMs), such as greases, gels, and phase change materials, pose bottlenecks to heat removal and have long caused reliability issues in automotive power electronics packages. Bonded interface materials (BIMs) with superior thermal performance have the potential to be a replacement to the conventional TIMs. However, due to coefficient of thermal expansion mismatches between different components in a package and resultant thermomechanical stresses, fractures or delamination could occur, causing serious reliability concerns. These defects manifest themselves in increased thermal resistance in the package. In this paper, the results of reliability evaluation of emerging BIMs for large-area attachments in power electronics packaging are reported. Thermoplastic (polyamide) adhesive with embedded near-vertical-aligned carbon fibers, sintered silver, and conventional lead solder (Sn₆₃Pb₃₇) materials were bonded between 50.8 mm \times 50.8 mm cross-sectional footprint silicon nitride substrates and copper base plate samples, and were subjected to accelerated thermal cycling until failure or 2500 cycles. Damage in the BIMs was monitored every 100 cycles by scanning acoustic microscopy. Thermoplastic with embedded carbon fibers performed the best with no defects, whereas sintered silver and lead solder failed at 2300 and 1400 thermal cycles, respectively. Besides thermal cycling, additional lead solder samples were subjected to thermal shock and thermal cycling with extended dwell periods. A finite element method (FEM)-based model was developed to simulate the behavior of lead solder under thermomechanical loading. Strain energy density per cycle results were calculated from the FEM simulations. A predictive lifetime model was formulated for lead solder by correlating strain energy density results extracted from modeling with cycles-to-failure obtained from experimental accelerated tests. A power-law-based approach was used to formulate the predictive lifetime model.