The paper presents a degradation for remaining useful lifetime framework for smart power stages (SPS) with an integrated temperature sensor for electronic control units (ECU). A reduced order state space model with physically meaningful time constants is derived from finite element simulations. The state space model is the core of the damage estimation of the SPS during operation. A framework for remaining useful lifetime estimation is presented simulating degradation based on an estimated mission profile for cars. Temperature cycles are extracted and used to estimate the time constant drift representing package degradation. An exemplary approach on how to integrate degradation monitoring into a lifetime approximation of the package is presented. The state space model is extended for estimator based predictions to integrate the model in future test benches for real life monitoring and remaining useful life predictions of active devices.

Due to the better performance of the Wide Band Gap (WBG) devices, there has been a paradigm shift toward WBG-based power modules for diverse applications like Electric Vehicles (EVs). However, the high parasitic inductance value of power modules hinders these devices from unlocking their full potential. Therefore, this paper comprehensively reviews SiC-based Single Side Cooling (SSC) power modules that benefit from low parasitic inductance. The paper also discusses the need to develop newer power modules using modern packaging methods. The surveyed power modules are categorized into three main groups, namely wire bonding, hybrid, and 3D packaging methods. This classification contains several vital parameters of the studied power modules, such as nominal and Double Pulse Tests (DPT) power ratings, parasitic inductance, size, etc. The main features and characteristics corresponding to the reviewed power modules' packaging methods and techniques are also briefly described. Finally, a thorough discussion about challenges and future trends is highlighted before concluding the paper.

Modeling and monitoring advanced power semi-conductor packages are challenging due to their multiphysics behavior, structural complexity, and the high computational cost associated with detailed models. Conventional high-fidelity approaches, such as finite element models, provide high accuracy but are often unsuitable for applications like health monitoring, while purely data-driven models may lack physical interpretability and robustness under degradation.This paper proposes the concept of a multi-agent digital twin framework to address these challenges by decomposing the overall system into interconnected virtual domains with different roles and fidelity levels. The approach is demonstrated for health monitoring of a SiC MOSFET in a DC-DC buck converter. A three-agent architecture is implemented, consisting of a temporal ANN for system identification, a decision layer for failure detection and localization, and a parametric reduced-order thermal model for failure assessment. Experimental results show that the proposed framework can accurately identify system behavior, detect and localize failures, and quantify parameter variations associated with degradation.

Sintered Cu nanoparticles (NPs) are promising for high-performance electronics due to their excellent thermal and electrical conductivity, as well as mechanical reliability. This study investigates the microscale mechanical behavior of sintered Cu NPs with a bimodal particle size distribution, focusing on strain rate and temperature effects. Micro-pillar compression tests were performed across strain rates of 0.0001 s⁻¹ to 0.01 s⁻¹ and temperatures from 25 °C to 350 °C. Results show that higher strain rates enhance yield strength through strain-rate hardening, while elevated temperatures lead to thermal softening and reduced mechanical stability. The Anand viscoplastic model accurately predicts these deformation behaviors. Microstructural analysis via scanning electron microscopy (SEM) and transmission electron microscopy (TEM) reveals localized deformation at 175 °C, with dislocations concentrated near the top surface and persistent porosity below, whereas at 350 °C, re-sintering and grain boundary diffusion create a denser microstructure. Phase-field fracture modeling further elucidates crack propagation, emphasizing the role of pore size and temperature. This combined experimental and modeling approach enhances understanding of viscoplastic deformation and fracture mechanisms in sintered Cu NPs, informing their use in interconnects, power electronics and thermal management systems.

In this study, we introduced a hybrid Potts-phase field model to simulate the co-evolution of grain growth and pores migration in sintered silver layers. The Potts model is good at capture the grain growth dynamics, while the phase field model describes the evolution of the porous network. These models are coupled via a hybrid free energy function to achieve a realistic representation of the microstructure evolution. This study further extends the hybrid model by incorporating (a) a flexible exchange interaction matrix to model the crystal anisotropy in grain growth, (b) Glauber or Kawasaki dynamics to describe different diffusion mechanisms, and (c) the effect of pinning sites, representing impurity-driven grain boundary stabilization. The computational framework is implemented using Taichi Lang, which allows for efficient parallel simulations. Results show that the model effectively captures the long-term evolution of the sintered silver microstructure in good agreement with experimental observations. This hybrid model is a powerful tool to predict microstructural reliability of sintered silver die attach layers, supporting material design and process optimization for high-power electronic applications.

This study evaluates the reliability of die interconnect layers in a stacked die system fabricated using two different sintering agents: a microparticle-based silver paste and preform-based copper nanowires, intended for high-power packaging applications. Single-step sintering is performed to attach both dies at the same time, offering a faster and efficient assembly for improving scalability in manufacturing. The copper nanowires are sintered using KlettSintering method at 230° C for 5 minutes under a pressure of 20 MPa, while the silver paste was sintered pressure-free at 280 °C for 45 minutes in nitrogen. The assembled units were characterized using shear strength and microstructural analysis. Both sintering methods showed high porosity in the top die-attach layer compared to the bottom die-attach layer, which is reflected in lower shear values for top die (35 MPa) compared to bottom die (45 MPa) in the silver sintered unit. The long-term reliability of the die-stack systems was assessed through a 500 -hour high-temperature storage test and a 500-cycle temperature cycling test, revealing significant impacts of thermo-mechanical stresses on die attach layers of both sintered units. The KlettSintered system maintained consistent performance throughout the reliability tests but exhibited coarsening and oxidation during temperature cycling. Furthermore, the study identifies areas for potential improvement, particularly in improving multi-die sintering performance in a single-step process, which is crucial for ensuring durability in high-power applications.

This study investigates the microstructure evolution and mechanical behavior of bimodal-sized sintered copper (Cu) nanoparticles (NPs) under varying sintering pressures. Micro-pillar compression tests reveal a transition from collapse-dominated to compaction-driven deformation as sintering pressure increases. Transmission electron microscopy (TEM) and transmission Kikuchi diffraction (TKD) analyses identify a two-stage deformation mechanism—initial pore compaction followed by intragranular slip—fundamentally distinct from bulk Cu. Molecular dynamics (MD) simulations further reveal that large particles promote dislocation-mediated plasticity by accommodating intragranular slip, while small particles enhance load transfer through localized shear-compaction, together enabling uniform strain distribution and supporting the experimentally observed strain accommodation. The resulting microstructure achieves a combination of high yield strength (up to 320 MPa) and low elastic modulus (20 GPa), offering a compliant yet robust response. These findings elucidate a unique processing–structure–property relationship and provide a rational basis for designing porous metal interconnects capable of withstanding thermomechanical stresses in advanced electronic packaging.

This study investigates the interface strength and fracture behavior of sintered copper (Cu) nanoparticles (NPs) for all-Cu integration in advanced microelectronics packaging. Micro-cantilever bending tests on three configurations (Cu NP-notched, interface-notched and un-notched micro-cantilevers) were analyzed using scanning electron microscopy (SEM), transmission electron microscopy (TEM), transmission Kikuchi diffraction (TKD) and cohesive zone model (CZM). The interface-notched micro-cantilevers demonstrate superior fracture resistance, with a stress intensity factor (K_Q) of 2.88±0.10 MPa m^1/2, compared to 2.12±0.11 MPa m^1/2 for Cu NP-notched micro-cantilevers. Simulation results, consistent with experimental results, reveal that Cu NP-notched micro-cantilevers exhibit lower fracture resistance due to porosity and stress concentrations, while interface-notched micro-cantilevers show enhanced strength, attributed to robust bonding and reduced void distribution. Un-notched micro-cantilevers display superior load-bearing capacity, with cracks bypassing the interface and propagating through porous regions. Moreover, in un-notched micro-cantilevers, a synergistic deformation mechanism is observed, where crack propagation through the sintered Cu NPs coexists with plastic slip deformation in the Cu substrate. These findings highlight the strong interfacial bonding and effective stress transfer at the Cu substrate-sintered Cu NP interface, validating the feasibility of direct sintering using Cu NPs without additional coatings.

The mechanical strength of sintered nanoparticles (NPs) limits their application in advanced electronics packaging. In this study, we explore the anisotropy in the microstructure and mechanical properties of sintered copper (Cu) NPs by combining experimental techniques with molecular dynamics (MD) simulations. We establish a clear relationship between processing conditions, microstructural evolution, and resulting properties in pressure-assisted sintering of Cu NPs. Our findings reveal that pressure-assisted sintering induces significant anisotropy in the microstructure, as evidenced by variations in areal relative density and the orientation distribution of necks formed during sintering. Specifically, along the direction of applied pressure, the microstructure exhibits reduced variation in areal relative density and a higher prevalence of necks with favorable orientations. The resulting anisotropic mechanical properties, with significantly higher strength along the pressure direction compared to other directions, are demonstrated through micro-cantilever bending tests and tensile simulations. This anisotropy is further explained by the combined effects of strain localization (influenced by areal relative density) and the failure modes of necks (determined by their orientation relative to the loading direction). This work provides valuable insights into the analysis of sintered NPs microstructures and offers guidance for optimizing the sintering process.

Silicon-Carbide (SiC) MOSFETs are widely used in high-power and high-efficiency applications such as electric vehicles and power supplies. However, long-term reliability remains a critical concern, particularly under extreme operating conditions. This work aims to explain the health monitoring of SiC metal oxide-semiconductor field effect transistors (MOSFETs) through precise junction temperature (T_j) profiling based on performed measurements. The study focuses on the temperature-dependent behavior of the on-resistance (RDS(on)), a key parameter that varies with the aging, degradation, and temperature of the device. By systematically measuring R_DS(on) at different temperatures and at various stages of the operating life of the device, we can establish a predictive model to assess the health of SiC MOSFETs. The importance of pulse duration of the drain current is stressed to avoid the self-heating effect with some device physics insights. The proposed methodology enables better understanding of the SiC MOSFET performance for future real-time condition monitoring, facilitating early failure detection and lifetime estimation. This approach provides valuable information for improving reliability and optimizing maintenance strategies in power electronics systems. Experimental results validate the effectiveness of the proposed method and give direction for future research opportunities.

This article introduces an online condition monitoring strategy that utilizes a transient heat pulse to detect package thermal performance degradation. The metric employed is the temperature-dependent transient thermal impedance "Zth(t, Tamb)."The proposed methodology offers quantitative insights into package thermal performance degradation and effectively pinpoints the presence of multiple failure mechanisms. A thermal test chip assembled in a power quad flat no-lead package is used in this study to demonstrate the methodology. The packaged devices are first characterized to determine the transient pulse duration, a critical parameter to monitor a specific region of interest. Subsequently, package thermal performance degradation is continuously monitored online during thermomechanical cycling lifetime experiments. The validity of the measurement results is later confirmed through acoustic imaging and cross-sectional analysis. The changes observed in Zth(t, Tamb) over thermal cycling correspond to the delamination of the active metal layers on the die and cohesive failure on the die attach. This article further includes a comparative summary, highlighting the distinctions between the proposed and industry-standard test methods. In conclusion, the importance of online condition monitoring to detect early signs of failure is emphasized, and the proposed methodology s practical applicability in real-life scenarios is briefly discussed.

A significant challenge in the implementation of health monitoring systems for estimating the health state of devices is the lack of accurate information about design details. This challenge is particularly prominent in the field of power electronics, where both IC designers and converter designers are often hesitant to share information about their designs. Addressing this issue, this paper introduces a novel AI-driven digital twin modeling methodology that enables the detection and classification of failures in power semiconductors, particularly Wide Band Gap semiconductors. By employing AI-based system identification techniques, this method offers a noninvasive approach to health monitoring of power switches with high resolution, even while operating under real conditions. The proposed method has been validated by simulating wire bond failure in a SiC power MOSFET using MATLAB SIMULINK, and the results demonstrate its accuracy.

Resin-reinforced Ag sintering materials represent a promising solution for die-attach applications in high-power devices requiring enhanced reliability and heat dissipation. However, the presence of resin and intricate microstructure poses challenges to its thermal performance, and improvement strategies remain unclear. This work utilizes 3D FIB-SEM nanotomography to reconstruct the microstructure of this material under various process conditions. The analysis reveals that, even with an Ag volume fraction as low as 47.3%, Ag particles form a robust 3D network. Geometric tortuosity quantifies the effect of different sintering conditions on the Ag particle network in all spatial directions. Effective thermal conductivity is simulated based on realistic microstructure models. Results show a significant negative correlation between tortuosity and effective thermal conductivity. Increasing sintering temperature in Model B notably reduces tortuosity and enhances effective thermal conductivity. Sensitivity analysis underscores the dominant role of Ag volume fraction in regulating effective thermal conductivity. Finally, transient thermal impedance measurement of this material as a thin die-attach layer in actual high-power devices demonstrated its application potential. This article strives to explore the relationship between process, microstructure, and thermal properties of this material to provide a reference for further development.

Prognostic monitoring of power quad flat no-lead (PQFN) packages with four distinct silver pastes, each varying in material composition (pure-Ag and resin-reinforced hybridAg) and sintering processes (pressure-assisted and pressureless), was investigated in this study. The PQFN packages with silver sintered die-attach materials were subjected to thermal cycling tests (?55 ° C to 150 ° C), and the performance degradation was evaluated based on the following metrics: 1) electrical ON-state resistance RDSon monitored periodically at specific thermal cycling intervals and 2) transient thermal impedance Zth(t = 0.1 s) monitored online during thermal cycling. These measurements were further validated using acoustic microscopy imaging and cross-sectional inspection. The pressureless Ag-sintering material demonstrated comparable performance to pressure-assisted Agsintering, with a dense microstructure, and consistent electrical and stable thermal performance. Whereas the pressureless resinreinforced hybrid-Ag material exhibited degradation with a relative increase of 33% in RDSon, 38% in Zth(t = 0.1 s), and 67% delamination of the die-attach interface over 1000 cycles. These findings suggest that pressureless Ag-sintering may offer a viable alternative to pressure-assisted methods for lead (Pb)- free die-attachments, while resin-reinforced hybrid-Ag requires further development for improved thermomechanical reliability..

Solder fatigue is a key failure mode in the electronic industry. Monitoring the actual degradation of the solder under real-time conditions in any application would be extremely beneficial. In this chapter, we describe the combination of experimental material characterization with numerical finite element (FE) simulations to obtain a prognostics and health monitoring (PHM) methodology for LED drivers used in outdoor lighting applications. Experimental characterization of a new type of solder is described. A FE model is created of a typical component in electronic drivers. The calculated damage level and the collected life data correlate together and form a model for predicting the lifetime of the drivers at certain user condition. The developed PHM methodology helps in identifying and reporting the failure of the driver in real time or can be used for predicting the actual remaining useful life (RUL).