Optical micro-electromechanical systems (MEMS) demand exceptional precision, yet warpage during the die attach process on printed circuit boards can compromise performance. Here, a three-dimensional thermoelastic analytical model has been developed based on Fourier heat conduction and supported beam theory. This model facilitates the in-situ calibration of solder parameters via confocal micro-Raman spectroscopy, ensuring that the simulated dynamic evolution of warpage during soldering aligns closely with digital image correlation experiments. The results show consistence with Finite Element Method with error less than 1 % and time saving more than 60 %. Orthogonal experimental analysis further reveals that substrate thickness and thermal expansion coefficient variations are the primary factors affecting warpage, while chip area has a negligible role. Given the practical challenges in reducing substrate thickness, a stress-balancing strategy incorporating an additional transition layer is proposed, which is effectively validated with a high-resolution three-dimensional profilometer. This work provides valuable insights into the predictive modeling and warpage behavior characterization, directly supporting improved mitigation strategies in the die attach process.

Silicon carbide (SiC) MOSFETs, as leading wide bandgap semiconductor devices, exhibit superior stability and reliability under high-temperature, high-switching frequencies, and high-power density operational conditions. SiC MOSFET with fan-out panel-level packaging (FOPLP) utilizes a redistribution layer (RDL) to substitute bonding wires, achieving low thermal resistance, electrical resistance, and parasitic inductance. This study proposes an optimal design strategy for SiC MOSFET FOPLP, considering parasitic inductance suppression, heat dissipation, thermal-mechanical reliability, and insulation enhancements. First, we establish the parasitic inductance, heat transfer network, and thermomechanical stress physical analytical models of SiC MOSFET FOPLP. Subsequently, the non-dominated sorting genetic algorithm (NSGA-II) and the improved multi-objective particle swarm optimization algorithm (MOPSO) are integrated to realize the co-optimization of parasitic inductance, thermal resistance, thermal stress, and electric field intensity distribution. Finally, we attain the optimal parameters of the SiC MOSFET FOPLP, i.e. chip thickness (x₁), solder thickness (x₂), RDL thickness (x₃), and chip side length (x₄) as 0.25 mm, 0.05 mm, 0.35 mm, and 6.00 mm, respectively. Additionally, according to comparison the MOPSO algorithm exhibits faster convergence and superior diversity than NAGA-II in the electrical-thermal-mechanical multiphysics co-optimization. Generally, the proposed physical analytical models combined with a multi-objective optimization method have a substantial guidance and forward-looking prospect on the design of SiC MOSFET FOPLP.

This study systematically investigated the potential of waste carbon fibers (WCFs) as a sustainable solution in enhancing the multiple induction heating healing of asphalt mixture, thereby tackling two major concerns: the environmental impact of WCFs and the durability of asphalt pavement. Firstly, four groups of asphalt binder samples with different WCFs contents were prepared. The viscosity and workability of WCFs modified asphalt binder were analyzed. Next, asphalt mixture containing 2% steel fibers was prepared at the optimal WCFs content, while control groups without WCFs were prepared with 2% and 4% steel fibers content. A comprehensive study was conducted on the induction heating rate, effective heating depth and surface temperature cooling rules of the asphalt mixture. Finally, by conducting multiple “fracture-healing” tests, the influence of WCFs on the healing efficiency of asphalt mixture was analyzed. The results revealed that WCFs increased the viscosity of the virgin asphalt, but excessive WCFs content hindered the workability. The optimal WCFs content was determined to be 1% (by weight of asphalt binder). WCFs enhanced the thermal conductivity of the asphalt mixture, accelerating heating and improving vertical heat transfer while reducing surface temperature decline. During multiple “fracture -healing” processes, the inclusion of WCFs enhanced the mechanical strength of the asphalt mixture, improved its healing efficiency, and increased the number of healings. Even after five cycles, the specimen with the most damage still showed a fracture energy recovery rate (FERR) of over 30%. In conclusion, WCFs significantly enhanced the multiple induction heating healing efficiency of the asphalt mixture.