Abstract: Over the past few years, Silicon Carbide (SiC) power MOSFETs had a huge success both in terms of performances and impact on market. However, threshold voltage (Vth) instability is still a key aspect to attention, especially in long-term switching behavior. In this work, we have implemented Dynamic Gate Stress (DGS) reliability test on an automotive grade, planar-gate, SiC MOSFET. We have assessed the impact of duty cycles values, namely 25 % and 50 %, combined with different Rg values, namely 0 Ω and 6.8 Ω. As a result, a limited impact of duty cycle has been noticed on Vth and on-state resistance (RDS,ON) drifts, independently from the gate resistance value adopted. Besides, for each combination of parameters analyzed, gate–source voltage (VGS) waveforms have been acquired before and after the stress, and, consequently, a statistical analysis have been implemented. No significant variations in peak values and slew rates have been noticed.

Keywords: Duty cycle | Dynamic Gate Stress | Gate resistance | MOSFET | Reliability | Silicon Carbide

Abstract: Viscoelastic polymers are increasingly employed in lattice structures for their absorption and damping capabilities, particularly in applications involving vibration suppression or impacts. These structures exhibit remarkable properties, such as high specific stiffness, specific strength and energy absorption capacity, making them highly attractive for applications in aerospace, automotive, and biomedical fields. However, the accurate modeling by taking into account frequency-dependent behavior, especially for applications involving damping, remains challenging due to the interplay between geometric complexity and material viscoelasticity. To address this challenge, this study makes use of a general numerical homogenisation method enhanced for frequency-dependent material properties in order to predict the damping of the lattice structure at the macroscopic scale. A fractional derivative constitutive model is used to describe the frequency-depend behaviour of the bulk material, while a custom Ansys APDL code is developed to adapt the homogenisation method to the case of material with frequency-dependent properties. The results demonstrate that, for lattice structures made of a single material phase, it is possible to perform the homogenisation process at an arbitrary frequency. The resulting stiffness tensor of the equivalent homogeneous anisotropic material that replaces the structure at the macroscopic scale varies with frequency according to the same law used for the bulk material at a lower scale. Furthermore, the results show that even if the stiffness tensor of the lattice structure at the upper scale exhibits elastic symmetry depending on the topology of the unit cell, the damping matrix at the upper scale is unaffected by the lattice topology.

Keywords: Homogeneization | Lattice structures

Abstract: In semiconductor environment, the manufacturing process and the related quality control hold a fundamental position. This aspect has been enhanced with the introduction of new materials, such as Silicon Carbide (SiC), and the necessity to perform a reliable method to detect wafer defects. In this paper, the Electrical Wafer Sorting (EWS), a reliable technique for creating electrical wafer maps, is combined with a deep learning pipeline to improve the defects identification. With respect to the state of the art, the innovative aspect is in the combination of a supervised system with an unsupervised sub-system. Compared to benchmarking algorithms present in literature, this approach allows to correctly classify well-know defect patterns and to characterize new defect morphology, leading to the identification of new potential issues in the production line and, overall, to a production yield improvement.

Keywords: Deep Learning | Electrical Wafer Sorting | Silicon Carbide | Wafer Defect Maps

Abstract: The growing use of wide-band-gap semiconductors in power electronics increases the demand for efficient yet low-cost thermal management. Pin-fin heat sinks offer a practical solution due to their robustness and ease of fabrication, but their geometric optimization via Computational Fluid Dynamics (CFD) models remains computationally demanding, particularly in multi-variable contexts. This work presents a novel surrogate modeling approach based on Non-Uniform Rational Basis Splines (NURBS) entities for predicting thermal and hydraulic performance in pin-fin cooling systems for traction inverters. Two CFD modeling strategies were explored: one allowing variable pin count, and another preserving topological consistency by adjusting the domain width. While the former introduced geometric discontinuities that degraded metamodel accuracy, the latter enabled the NURBS-based surrogate model to achieve high predictive performance with a few seconds evaluation times. Compared to Kriging surrogate models and Artificial Neural Networks (ANNs), the NURBS approach delivers superior computational efficiency, making it particularly well-suited for real-time applications, sensitivity analyses, and gradient-based optimization.

Keywords: Cooling systems | Metamodeling | NURBS | Surrogate Model | Power module

Abstract: Edge-side Prognostics and Health Management (PHM) for Electric Vehicles (EVs) demands vehicle sub-systems Remaining Useful Life (RUL) predictors running on automotive-grade Microcontroller Units (MCUs) under tight memory, latency, and energy budgets. Classical Knowledge Distillation (KD) often degrades long-horizon accuracy and fails on the complex forecasting-to-decision pipeline for Silicon-Carbide (SiC) traction-inverter power modules. We propose Neuro-Modulated Knowledge Distillation (NM-KD), distilling a Multi-Scale Temporal Fusion Transformer (TFT-MS) into a lightweight model deployable on MCUs. NM-KD adapts loss weights via learned gates, bounds student sensitivity with a Lipschitz regularizer, and leverages Stochastic Weight Averaging (SWA) modulation. The TFT-MS teacher is benchmarked against several architectures spanning six design families, while the student selection is validated against five MCU-deployable alternatives. On SiC power devices, the student matches short-horizon performance and outperforms the teacher at long horizon (50-step accuracy 95.13% vs. 94.32%). On-target deployment reduces non-volatile memory by 83.12%, latency by 81.73%, and energy by 60.57%. Cross-batch generalization on 21 modules from two independent manufacturing lots confirms robustness to process variability. A lightweight temporal remapping converts accelerated-cycle predictions into field-relevant RUL estimates. NM-KD enables fast, low-power, accurate PHM on automotive Electronic Control Units (ECUs).

Keywords: Deep learning | Knowledge distillation | Neuro-modulation | Silicon carbide | Traction inverter

Abstract: The aim of this study is to develop a transient thermal analysis by means of Computational Fluid Dynamics (CFD) to assess the thermal impedance of a SiC-based direct-cooled traction inverter from STMicroelectronics. Thermal impedance measurements are performed during a power cycle test. The virtual junction temperature of the switches is determined assuming the body diode voltage drop as a Temperature-Sensitive Electric Parameter (TSEP). In more detail, one switch is heated, and the junction temperature is measured by TSEP for the other switches, accounting for cross-heating between them. Subsequently, a sensitivity analysis of the time step is performed to allow the adoption of a variable time step during the investigated time range. Following this analysis, the computational time required for the simulation is reduced by 60% compared to using a constant time step.

Keywords: CFD | Cross-heating | Thermal Impedance | Traction Inverter | TSEP

Abstract: This paper presents a study focused on comparing optimization methods applied to three distinct lattice structure: Octet, FCC, and BCC. The comparison was carried out through a comprehensive review of the relevant literature using the Google Scholar database. Various factors were considered, including the additive manufacturing process and corresponding materials, the software used for structural design and simulation, the geometric parameters, and the improvement obtained. It has been observed that certain optimization techniques, such as the addition of struts, can enhance the energy absorption capacity of lattice structures by increasing their relative density. In comparison, methods such as curved lattice designs were found to alleviate stress concentrations at the nodal points, leading to a more uniform stress distribution.

Keywords: Additive manufacturing | BCC | Energy Absorption | FCC | Lattice structure | Octet

Abstract: Technological development made vehicle safer thanks to the advanced driving assistance systems (ADAS). There exists passive systems, like ABS that boosts vehicle performance during an emergency braking, and active systems, like active cruise control that actively drives car during normal cruise. However, ADAS need to further evolve to continue the risk reduction and to increase automation level. Physiological sensing and deep learning are promising options at these regards. This paper will present a methodology to estimate the driver drowsiness from photoplethysmography (PPG) waveform, acquired by no-invasive probe embedded in the vehicle steering wheel. PPG signal is treated using the innovative hyper-filtering process, then it is elaborated by a convolutional deep architecture. A driver sample, made by 70 people distributed by gender and age, was selected to validate the approach, monitoring PPG and confirming the actual level of drowsiness by electroencephalography. The proposed network makes a classification task to distinguish a wakeful drive from a drowsy one. The developed method has an accuracy of 99%, which were higher than other networks considered for the benchmark.

Keywords: ADAS | automotive physio-sensing | Deep Learning

Abstract: Novel reliability tests are being developed for power semiconductor devices, especially for those based on wide band-gap materials, such as silicon carbide (SiC), in electric vehicles field. More specifically, because of the automotive environment and higher permissible slew rates in SiC devices, it is important to assess reliability in harsh conditions. Potentially related to this test, incomplete ionization of the dopants and edge termination fails are reported for SiC devices, in consequence of fast transients, but aging phenomena and parameters drift have not been deeply investigated.

Keywords: Dynamic reverse bias | MOSFET | Reliability | Silicon carbide | Slew rate

Abstract: In this work, the dynamic gate stress (DGS) on a planar-gate silicon carbide MOSFET is performed based on an automotive mission profile. An extensive characterization was performed, even beyond automotive qualification guidelines, including the effect of the temperature. The results show that the temperature accelerates the threshold voltage drift, which ranges from 3 % at room temperature up to 6 % at 125 °C and 150°C, with negligible impact on the on-state resistance. Moreover, we measured the gate-source voltage waveforms before and after the DGS stress, not finding significant variations in switching gradients.

Abstract: Silicon carbide (SiC) power MOSFETs use in different fields of application leads to increase the attention on reliability issues and long-term stability. Among these, threshold voltage (Vth) stability is one of the main topics. In this work, we have carried out dynamic gate stress (DGS) reliability tests on an automotive grade, planar-gate, SiC MOSFET. The goal is to evaluate the effect of different external gate resistance Rg magnitudes. We have captured the gate-source voltage (VGS) waveforms during DGS tests at two different Rg values, namely 0 Ω and 6.8 Ω. Results have shown 2% and 1% Vth drifts in the two cases. In either case, we noticed a negligible impact on the on-state resistance (RDS,ON). No significant variations in the VGS switching gradients were observed either.

Abstract: This work investigates the reliability of SiC MOSFET under dynamic reverse bias (DRB) conditions during mission profile. Through a dedicated campaign with an innovative experimental setup, we build a lifetime model to predict reliability during applicative mission profile. We conduct a long-term DRB test on a robust sample size and obtain the Weibull statistics. Using the lifetime model, we calculate the expected unreliability failure during mission profile, demonstrating SiC device robustness.

Abstract: The use of wide-bandgap semiconductor-based transistors has become essential in recent years for the development of new systems for sustainable mobility and, more generally, for energy conversion. In this frame, silicon carbide-based power MOSFETs are currently the most promising devices, as they enable the simultaneous management of high voltages and high currents. During the switching phases, the device experiences current pulses, which, due to Joule heating, lead to thermomechanical expansion processes caused by the generated heat. This process represents one of the main aging mechanisms for this class of devices, whose failure mechanisms may significantly differ from that of silicon-based devices. This work proposes an analysis protocol to thermally and thermomechanically characterize a commercially available SiC power MOSFET. To this end, the device was subjected to periodic stress cycles to realistically simulate its aging process as closely as possible. To assess the device's health status, its dynamic ON resistance, measured during a test pulse, was monitored. This choice is motivated by the possibility of tracking this parameter during normal system operation, thus enabling a possible estimation of the device's remaining lifetime on the field.

Keywords: on-state resistance | power MOSFETs | semiconductor device reliability | silicon carbide | thermal analysis

Abstract: Efficient thermal management is essential for the reliability and performance of traction inverters. However, direct optimization via Computational Fluid Dynamics (CFD) is often impractical due to the high dimensionality of the design space and the high computational cost of each simulation. To overcome this limitation, a surrogate-based optimization framework is developed to enhance the thermal and hydraulic performance of an automotive traction inverter cooling system. The methodology integrates CFD, deep neural networks (DNNs), and a multi-objective evolutionary algorithm. A simplified representation of the ACEPACKTM DRIVE power module is employed to generate an extensive dataset through automated, GPU-accelerated CFD simulations, making data generation computationally feasible while avoiding the prohibitive cost of direct optimization. A DNN surrogate model is trained to accurately predict pressure drop and heated-wall temperature, achieving mean relative errors below 3% and 1%, respectively. This surrogate model then guides a Non-Dominated Sorting Genetic Algorithm III in the optimization of key geometric parameters, including pin-fin diameter, spacing, height, wall clearance, as well as of physical parameter such as the surface roughness of the pin-fins. CFD-based validation of the Pareto-optimal designs, performed on the full inverter geometry, indicates reductions of up to 25% in pressure drop and approximately 2% in junction temperature. These results suggest that the proposed methodology promises robustness and generalizability, showing good potential for further application in data-driven thermal design optimization.

Keywords: CFD | Deep neural network | NSGA-III | Optimization | Power module

Abstract: High-efficiency power converter design and optimization depend on precise loss estimation in power semiconductor devices. This study examines a cascaded system that consists of a DC-DC boost converter and single-phase fullbridge inverter to produce a sinusoidal AC output for grid connected applications. To identify the primary loss causes, a simple analytical framework for evaluating MOSFET conduction and switching losses is devised, which includes device parasitic capacitances, gate charge dynamics, Miller's plateau voltage and diode reverse recovery effects. LTSPICE simulations are used to validate the analytical model across a range of switching frequencies, showing a high degree of agreement between the simulated and predicted outcomes.

Keywords: Analytical modelling | Conduction loss | DC-AC converter | Switching loss

Abstract: The automotive development of Electric Vehicles (EVs) is accelerating due to environmental concerns and technological advances. The complexity and performance demand of EVs require the use of Silicon-Carbide (SiC) technologies for the related efficiency, high-temperature resistance, and robust dynamic switching. To ensure the high performance of electric vehicles, the rigorous screening of the delivered SiC devices plays a pivotal role. Defects in SiC production can cause failures that directly affect the performance of electric vehicle engines, particularly in the traction inverter subsystem. To identify these defects early, advanced visual screening through optical microscopy and X-ray approaches has been proposed by leading car makers. These screening methodologies require advanced technical expertise and are still prone to significant errors, even when performed manually by experienced operators. To address these inefficiencies, the authors propose an ensemble deep learning pipeline for performing a robust automated visual inspection of SiC devices. By combining Multi-Head Attention blocks with adaptive input data distortion compensation through Jacobian regularization within convolutional architectures, the proposed model leverages global context and local feature maps, enhancing accuracy and robustness in multimodal defects detection. The proposed combined approach, tested on ACEPACK/TPACK DRIVE SiC power modules provided by STMicroelectronics, achieved an average accuracy of approximately 93% in both methodologies.

Keywords: Deep Learning | Defects analysis | Silicon-Carbide

Abstract: Accurate monitoring of the gate–oxide health of Silicon-Carbide (SiC) MOSFET devices is pivotal for condition-based maintenance of electrified vehicles, high-frequency converters and consumer electronic applications. A MOSFET parameter closely related to the device oxide interface is the threshold voltage. The SiC MOSFETs threshold voltage (Vth) drifts with interface oxide–trap accumulation and it is therefore a direct early-marker of the device degradation. The Vth drift monitoring is then significantly relevant in the mentioned application fields. This work proposes a non-intrusive, single-shot intelligent pipeline that infers Vth solely from an input data-snapshot of the steady-state MOSFET static behavior based on current-to-voltage I – V family curves sampled during routine gate driving. We introduce HyperDeep, a novel Hyperbolic Möbius Deep architecture that embeds each I – V input snapshot in the hyperbolic Poincaré ball, processes it through ad-hoc designed residual Möbius layers followed by hyperbolic self-attention blocks. An adaptive exponential Lipschitz regularization block compensates process-spread-induced statistical drift in SiC devices, preserving mapping stability across SiC MOSFET’s wide threshold-voltage window. The proposed HyperDeep system was trained on large dataset that includes both synthetic and real data obtained through Dynamic Gate Stress (DGS) methodology applied to SiC MOSFET GEN3 devices delivered by STMicroelectronics. The proposed deep pipeline attains in average of 0.015 MSE (Mean Squared Error) in retrieving actual Vth, outperforming compared state-of-the-art architectures.

Keywords: Deep learning | gate driving | hyperbolic geometry | MOSFET | residual lifetime

Abstract: Silicon Carbide (SiC) power devices are highly sought in modern power electronics for their superior performance; however, yield is severely impacted by crystal-growth defects often termed killer defects. Fast and accurate post-growth inspection of SiC wafers is therefore critical to identify such defects and improve manufacturing outcomes. We propose an improved YOLO-based one-stage detector that integrates a Non-Local Block + Gradient Reversal Layer (GRL) module into the YOLO backbone between the Spatial Pyramid Pooling (SPP) and BottleneckCSP layers. The Non-Local blocks enable the CNN to leverage global context in the microscopic images, improving its ability to recognize subtle defect patterns across the wafer. Meanwhile, the GRL-based domain adaptation allows the model to learn domain-invariant features, addressing distribution shifts between different datasets or imaging conditions. The proposed architecture, comprising these components, is evaluated on a dataset of SiC wafer optical micrographs containing various defect types to demonstrate its effectiveness (e.g., dislocations and stacking faults). The proposed method achieves mAP@0.5=95% and mAP@0.5:0.95=94.5%. These improvements demonstrate the efficacy of combining attention and adversarial domain adaptation in the YOLO architecture. The enhanced model detects SiC defects with higher accuracy and robustness to varying imaging conditions, marking a significant step forward in automated wafer defect inspection.

Keywords: Deep Learning | Defects analysis | Non-local block | Silicon-Carbide

Abstract: Deploying deep neural networks on embedded systems is challenging due to stringent constraints on memory, compute, and power. DISTILLO (aDvanced Interactive ST knowledge distILLation) is a knowledge distillation framework tailored for classification tasks in resource-limited environments. It features two strategies: DISTILLO-Classical, using dynamic loss weighting with Kullback-Leibler or Jensen-Shannon divergence, and DISTILLO-Ensemble, which combines multiple student models distilled at different temperatures. Jensen-Shannon divergence is adopted to provide symmetric, bounded, and stable gradients, improving the robustness of the training. Experiments using Vision Transformers as teachers and lightweight CNNs as students show that DISTILLO-Classical achieves up to +5.37% accuracy gain on CIFAR-100 and +4.42% on Imagenette. DISTILLO-Ensemble further improves performance, reaching +13.97% and +8.32% gains, respectively, with minimal memory and latency overhead. DISTILLO enables the effective deployment of deep models on embedded platforms such as STM32 microcontrollers.

Keywords: embedded systems | knowledge distillation | low-resources

Abstract: The objective of this study was to develop a Computational Fluid Dynamics (CFD) 3D model for an industrial application, to investigate how surface roughness affected pressure drop and thermal performance in the ACEPACKTM DRIVE, a commercial SiC-based power module used in traction inverters, that features a pin-finned baseplate with cylindrical pin-fins. The surface roughness of the pin-fins was modelled by using a sand-grain model available in Ansys Fluent, which represents a novelty in the literature and can pave the way for the development of accurate and computationally efficient simulations. The CFD model exhibits an error from experimental data within the range 10%–22% when the flow rate varies from 2 l/min to 12 l/min (maximum error at 2 l/min), while the validation of the thermal behaviour was obtained with a maximum error of 2.5%. Subsequently, a parametric analysis was carried out, varying the flow rate of the coolant, in order to investigate the influence of pin-fins surface roughness on performance, by considering two possible design option featuring respectively a surface roughness equal to 1 μm and 6 μm. The results showed a reduction in pressure drop from 4% to 11% and a degradation of the thermal performance, less than the 2%, when the pin-fins roughness increases.

Keywords: CFD | Pin-fins | Power module | Surface roughness

Abstract: This paper presents a method to study the reliability behavior of the ACEPACKTM SMIT, which is a top side-cooled power module employing high-voltage silicon MOSFETs in a half bridge topology. The experimental test involves power cycling: this is an accelerated stress test, which allows monitoring a temperature-sensitive electric parameter to study the thermal behavior of the package. The efficiency of heat exchange between the module and the cooling plate surfaces is strongly influenced by the thermal interface material (TIM) used between them. TIM is designed to fill gaps and voids between two surfaces, in order to to increase the effective contact area and improve thermal conductivity at the interface. In this work, the thermal performance of two different TIMs, a thermal grease and a phase change material, will be analyzed. The aim of the paper is to provide an experimental approach for characterizing the reliability behavior of power modules, considering the thermal behavior when different TIMs are considered.

Keywords: Accelerated stress test | Power Module | Reliability | Thermal Interface Material | TIM

Abstract: The use of silicon carbide (SiC) in power semiconductor modules has led to higher power density, increased maximum junction temperature, high voltage application, and more compact devices, which require efficient cooling systems. This study was to investigate the influence of the surface roughness on the pressure drop of ACEPACKTM DRIVE, a commercial SiC-based power module for traction inverter. This power module has a cylindrical pin-finned baseplate that is mounted on a dedicated cooling device (water jacket) in which coolant media flows. The analysis aimed to characterize the pressure drop between the inlet and exhaust sections of the water jacket, with the objective of optimising the coolant flow for an efficient module cooling, avoiding both excessive resistance and insufficient flow. Confocal laser scanning microscope was used to measure roughness on two different pin-fins with the same geometric characteristics but different surface roughness. Pressure drop measurements were taken at different coolant temperatures and flow rates using a hydraulic test bench. Results indicate that the pressure drop of the higher roughness configuration is 13-19% smaller than the first one, depending on the flow rate and coolant temperature. The suggested reason is that this decrease is caused by a reduction in pressure drops due to concentrated losses associated with fluid flow separation.

Keywords: CLSM | Pin-Fins | Power module | sPressure drop | Roughness

Abstract: Inverse modelling with deep learning algorithms involves training deep architecture to predict device’s parameters from its static behaviour. Inverse device modelling is suitable to reconstruct drifted physical parameters of devices temporally degraded or to retrieve physical configuration. There are many variables that can influence the performance of an inverse modelling method. In this work the authors propose a deep learning method trained for retrieving physical parameters of Level-3 model of Power Silicon-Carbide MOSFET (SiC Power MOS). The SiC devices are used in applications where classical silicon devices failed due to high-temperature or high switching capability. The key application of SiC power devices is in the automotive field (i.e. in the field of electrical vehicles). Due to physiological degradation or high-stressing environment, SiC Power MOS shows a significant drift of physical parameters which can be monitored by using inverse modelling. The aim of this work is to provide a possible deep learning-based solution for retrieving physical parameters of the SiC Power MOSFET. Preliminary results based on the retrieving of channel length of the device are reported. Channel length of power MOSFET is a key parameter involved in the static and dynamic behaviour of the device. The experimental results reported in this work confirmed the effectiveness of a multi-layer perceptron designed to retrieve this parameter.

Keywords: channel length modeling | Deep network | Power MOS inverse modeling

Abstract: The recent improvement in semiconductor devices has led to higher efficiency and power density. SiC and GaN offer higher switching frequencies and lower losses; however, the knowledge of the behavior of these devices is not mature. In this paper, a system for fast charging of batteries for electric vehicles based on an isolated DC-DC converter equipped with both SiC and GaN devices is presented, and an experimental comparison among these two technologies will be given in terms of dynamic performances, electromagnetic compatibility, stability, efficiency.

Keywords: DC-DC Converter | Fast-Recharging | Gallium Nitride | Power Electronics | Silicon Carbide

Abstract: Micro-Raman spectroscopy was carried out to evaluate the localized residual stresses in commercial Gallium-Nitride-based devices, specifically, AlGaN/GaN high-electron-mobility Transistors (HEMTs) with a novel packaging design provided by STMicroelectronics S.r.l. (Catania, Italy). The packaging plays a key role in protecting the device core against the external environment, thus minimizing damages caused by mechanical shocks, exposure to light, and contact with chemicals, conjointly achieving an efficient heat dissipation rate. Even though the packaging is a required step for the proper functioning of ready-to-use electronic devices, its application typically may introduce mechanical stress to AlGaN/GaN HEMTs, which can result in various reliability issues. In this paper, we investigate the impact of packaging on residual stress by analyzing the frequency shift of the E2 Raman peak along GaN layers and at the GaN/Si interface. An extensive evaluation was conducted using both a packaged device and a wafer-level device. The correlation between Raman frequency shifts of the E2 mode was accurately quantified, revealing a stress mitigation of approximately 0.1 GPa. This reduction is ascribed to the compressive stress introduced by the packaging, which partially offsets the intrinsic tensile stress of the wafer-level device. The proposed methodology could, in principle, be implemented to improve the development of packaging.

Keywords: AlGaN/GaN high-electron-mobility transistor | micro-Raman spectroscopy | packaged device | power electronic | wafer level

Abstract: Composition and morphology of two types of bilayers of plasma-enhanced chemical vapor deposition hydrogened silicon nitride (SiNx:H) and polyimide (PI), as effcient barrier against moisture in SiC-based power devices, are investigated. Two types of silicon nitrides are obtained by changing the flow ratios of the SiH4 and NH3 precursors. Rutherford Backscatterered analyses show that the Si/N ratio varies from 0.6 to 0.8. Elastic recoil detection analyses show that the sample with higher nitrogen content has a higher total bound hydrogen content of 7.8 × 1017 cm−2 with respect to the 7.1 × 1017 cm−2. Fourier-transform infrared spectroscopy characterizations show Si–H group concentrations of 0.96 × 1017 and 6.86 × 1017 cm−2 and NH groups of 4.82 × 1017 and 2.28 × 1017 cm−2, respectively. Silicon nitride films with higher concentration of N–H groups show higher reactivity and permeability to water, making them less effective as a barrier layer. Atomic force microscopy analyses of a PI layer deposited on the nitride layer, SiNx:H/PI show for both type of samples a similar roughness, indicating planarization that can increase the adhesion of SiNx:H/PI and resistance to moisture. The delamination mechanism of the bilayer under pressure pot test conditions is proposed.

Keywords: hydrogened silicon nitrides | passivation bilayers | polyimides | SiC devices

Abstract: This paper presents an experimental thermographic analysis of a directly-cooled silicon-carbide based power module, designed for automotive traction applications. The aim of this activity is related to one of the reliability assessments executed on power MOSFETs arranged in this package, named active power cycle. In this framework, thermo-sensitive electrical parameters (TSEPs) are commonly used to estimate the junction temperature of power devices. In the paper, the TSEP related to the body diode voltage drop is compared with the results obtained by using a high frame-rate thermal camera. Moreover, the heat propagation inside the module during the heating phase is showed.

Abstract: In this paper, a liquid-To-liquid thermal shock test is performed on TO-247 packages. By employing liquid with a high heat transfer coefficient as an energy transfer medium, it becomes possible to quickly couple thermomechanical stresses at the module interface. The temperature jump is achieved by maintaining the hot chamber at 150°C and the cold one at-65°C, by immerging the samples in each chamber for 8 minutes. Using ANSYS Mechanical, a numerical model was developed to evaluate the lifetime of the TO-247 under thermal shock test. In addition, this model was also used to compare the lifetime of these packages when a temperature cycle is considered. Experimental results showed differences between cold and hot ramp rate. In more detail, the average ramp rate of the 4 samples in hot environment is about 90°C/s while in the cold one it is about 65°C/s. Difference between heating and cooling rate could be addressed to the temperature effect on fluid viscosity. The numerical results show that the thermal shock test (with a soak time of 5 minutes) anticipates crack initiation compared to the temperature cycle (with the same soak time), suggesting that the difference in accumulation of inelastic work due to fatigue lies in the different ramp rates. A further comparison between two thermal shock was done, decreasing the soak time to 2 minutes, which confirmed the previous results.

Abstract: This study developed a 3D Computational Fluid Dynamics (CFD) model to compute the thermal resistance of the SiC-based direct cooled ACEPACK™ DRIVE power module, by STMicroelectronics. The model was validated with respect to experimental data. The model investigate regarding the temperature dependency of materials thermal conductivity. In more detail, two different thermal conductivity values for solder layer were considered, showing their significant impact on thermal resistance. After adjusting for this parameter and taking into account the effects of temperature-dependent thermal conductivity of the active metal brazing (AMB) substrate, the model showed good accuracy with an error ranging from 0.5% to 1.6%. Furthermore, the CFD model was used to investigate the influence of the non-linear thermal conductivity of the AMB on thermal resistance, finding that it varies as a polynomial function of flow rates and increases linearly with dissipated power.

Abstract: When compared to silicon, silicon carbide's (SiC) electro-thermal characteristics make it a strong contender for high voltage and high frequency applications. Since SiC power MOSFETs have been more widely available commercially just recently, there is an immediate need for precise simulation models to anticipate device behavior and facilitate circuit design. The silicon carbide (SiC) power MOSFET electro-thermal behavioral model (ETM) created by SPICE is presented in this study. The phenomena typical of static and dynamic behavior that depend on self-heating and junction temperature are covered in this model, which is based on the SPICE model. By using a single equation to describe MOSFET behavior spanning three distinct zones - weak, moderate, and strong inversion zones - the modified EKV model performs better than the reduced quadratic model. The model was simulated for different temperatures in comparison to DATASHEET for different characteristics. Accurate results are observed in comparison to the datasheet.

Keywords: Behavioral Modelling | EKV | SiC MOSFET

Abstract: When compared to silicon, silicon carbide's (SiC) electro-thermal characteristics make it a strong contender for high voltage and high frequency applications. Since SiC power MOSFETs have been more widely available commercially just recently, there is an immediate need for precise simulation models to anticipate device behavior and facilitate circuit design. The silicon carbide (SiC) power MOSFET electro-thermal behavioral model (ETM) created by SPICE is presented in this study. The phenomena typical of static and dynamic behavior that depend on self-heating and junction temperature are covered in this model, which is based on the SPICE model. By using a single equation to describe MOSFET behavior spanning three distinct zones - weak, moderate, and strong inversion zones - the modified EKV model performs better than the reduced quadratic model. The model was simulated for different temperatures in comparison to DATASHEET for different characteristics. Accurate results are observed in comparison to the datasheet.

Keywords: Behavioral Modelling | EKV | SiC MOSFET

Abstract: Within the framework of the assisted systems for automotive applications, considerable research has been employed to monitoring the driver’s attention level in order to assess the risk level of the driving scenario. In this context, physiological monitoring of the driver’s condition has emerged as a relevant approach to enhance driving assistance without having an invasive approach. According to these premises, the authors have developed a driving assistance system capable to employ a dedicated bio-sensor for capture the driver’s photoplethysmographic (PPG) signal, which is closely linked to their level of attention. This PPG signal is then processed by a dedicated deep learning architecture to reconstruct the driver’s attention level. Meanwhile a separate automotive-grade intelligent vision-based system has been developed to quantify the risk level of the driving scenario by means of a video saliency analysis technique. The effectiveness of this comprehensive system has been validated through experimental results.

Keywords: ADAS | automotive | Deep Learning | risk assessment

Abstract: Detecting and identifying production defects in the semiconductor industry are crucial for maintaining quality control during manufacturing. The use of new materials, such as Silicon and Silicon Carbide, highlights the need for a reliable wafer defect detection system. The Electrical Wafer Sorting (EWS) stage, which involves an electrical analysis of defect maps, is effective in spotting anomalies and defect patterns on wafers. This phase is time-consuming but enables semiconductor companies to improve and optimize their manufacturing processes, including the integration of advanced deep learning techniques. The proposed pipeline aims to meet the demand for a fully automated system to identify manufacturing defects in wafers, utilizing intelligent analysis of EWS wafer maps in combination with a Deep Convolutional Neural Network and an unsupervised subsystem. The stringent level of intelligent control at the EWS stage is necessary because the devices produced from the analyzed wafers are mainly power devices used in the power and inverter systems of the latest generation of conventional and electric cars. Experimental results have confirmed the effectiveness of this approach.

Keywords: Deep learning | Defect Analysis | Pattern recognition | Silicon | Silicon Carbide

Abstract: Beyond the traditional static biased tests, novel dynamic electric assessments are being developed for wide band-gap devices and package solutions, to assess their reliability behaviour in the automotive environment. In the dynamic reverse bias (DRB) test, the power devices are dynamically stressed with very high slew rates of drain-source voltage for one thousand hours. The test evaluates the reliability at applicative-like conditions in terms of switching frequency and bus voltage. This paper presents a DRB test characterization: more in details, all the most relevant electrical and thermal aspects are both characterized. Hence, the voltage waveforms are assessed to ensure the compliance with guideline and the alignment with the application. Main test parameters, such as frequency, temperature and voltage, are correlated by dedicated analysis. Moreover, power losses due to device’s capacitances are calculated by a straightforward approach. A thermal experimental method is developed to perform a benchmark.

Abstract: Automotive market requires more and more power semiconductor modules for the realization of vehicle electrification. With respect to more conventional discrete packages, power modules have more complex manufacturing flow in which there are some process parameters that play a key role for a robust design, mechanical and hydraulic integration with the vehicle. Among these parameters, the flatness of the final product must be controlled in order to guarantee the mounting of power modules on cooling system and the proper working of thermal management. This paper would introduce the technology of liquid cooling solution for electrified vehicles’ power module, pointing out the importance of power module flatness. Then, it is proposed an experimental methodology to analyze the warpage behaviour during power at the different process steps and at the end of power module manufacturing. Measurements confirm that flatness is within admitted tolerance (200 μ m), highlighting the ceramic soldering process as the most critical for warpage modification.

Keywords: Design | Flatness | Manufacturing | Power module | Tolerances

Abstract: Driven by the spread of electric vehicles, the market for SiC power devices is expanding so rapidly that many suppliers are struggling to meet the customer's demand both in terms of final devices and raw material, which nowadays consists of SiC wafers with a diameter of 150 mm (6 in.). STMicroelectronics (ST), world leader in the sale of SiC power device, has reacted by starting the in-house production of the next-generation wafers with a diameter of 200 mm (8 in.). This work describes the optimization of the n-type 4H-SiC epilayers on 200 mm substrates performed by ST in collaboration with LPE® “an ASM company” (LPE). The density of defects and the thickness and doping uniformity of the epilayers grown on 200 mm substrates are characterized, showing results comparable to the ones obtained for standard 150 mm wafers. Also, the reproducibility of the manufacturing process is improved, resulting in a run-to-run variation of the epilayer's thickness and doping below 2%.

Keywords: 200 mm wafers | 4H SiC | 8-in. Silicon carbide | Epitaxial growth | Power devices

Abstract: Transfer molded modules (TMMs) are becoming more and more diffused in semiconductor industries for several automotive applications. Epoxy molding compounds are used as plastic encapsulants for TMMs thanks to their adhesion, hygroscopic ruggedness and reliability improvement in active cycle conditions. However, a numeric quantification of adhesion is of paramount importance to build up a methodology to compare different resins. The target of the activity is the characterization of the adhesion strength and mode-mixity angle for copper-resin system. Four point bending experiment and numeric model based on fracture mechanics are employed for this purpose.

Keywords: Copper | Ductile fracture | Epoxy resins | Fracture mechanics | Resins | Semiconductor device manufacture

Abstract: This work presents an integrated experimental–numerical method to characterize, model, and experimentally study the properties of transfer molded power modules, considering two different thermal interface materials (TIMs). More specifically, a thermal grease and a phase change material are considered. The aim is to select the most reliable solution by making analytical characterization and power cycling tests on the modules equipped with the two kinds of TIMs. Then, further reliability study is accomplished, in order to estimate the lifetime of the power module equipped with the best TIM, that is the phase change one. Finally, a finite-element numerical model is developed and correlated with experimental data.

Keywords: Power cycle | Power packages | Thermal interface material | Thermal simulation

Abstract: In automotive and industrial application domains, the "health monitoring"or predictive reliability of electronic devices plays a key-role in ensuring reliability of the electrical components. Health monitoring regards a collection of methods aimed at monitoring the operational features and performance of an electronic components in order to schedule preventive/predictive maintenance. Similarly, predictive reliability makes it possible to test electronic devices in an intelligent manner, i.e. by identifying predictive patterns of degradation or anomalous behavior in order to effectively characterize the monitored systems. Specifically, the authors of the present work will show the excellent results obtained by applying artificial intelligence techniques to the monitoring by optical microscopy of the power modules in Silicon Carbide technology usually placed in the traction inverter of electric vehicles. The Silicon-Carbide Power Module is a key component embedded in the traction inverter-system of the modern electric cars, and its functional degradation or unusual behavior may have a significant negative impact on the car's safety. As with any electronic components, the power module is subjected to electro-mechanical stresses which impact its functionality over time, highlighting progressive states of physical degradation. One technique for detecting defects in Silicon-Carbide Power Modules is optical microscopy. Through ad-hoc deep learning system based on the use of an enhanced YOLOv5 architecture, the captured optical microscopic image of the analyzed Silicon-Carbide Power Module will be automatically processed providing in output a bounding-box segmentation of the most impactful and significant defect patterns for the functioning of the monitored power device. Several tests have been performed on different power modules of the ACEPACKTM DRIVE series delivered by STMicroelectronics. The collected performance (identification and classification accuracy close to 93%) confirmed the effectiveness of the proposed solution.

Keywords: Deep Learning | Optical Microscopy | Power Modules

Abstract: In this work, a method to thermally characterize a power semiconductor module based on silicon carbide for traction inverters is presented. In general, this is important in order to determine the real thermal behavior of the system and, consequently, to forecast the application reliability performances. Thermal impedance is measured by a dedicated bench, capable to heat power module by applying a constant current, yet ensuring a controlled liquid cooling environment. The obtained experimental curve is then translated into a system made by several RC ports, obtained employing convolution's algorithms. Solving the related differential equations, temperature profile can be obtained as function of time. Considering the actual application power loss, the related temperature profile can be calculated and collected in a discrete number of different load cases characterized by a duration and a thermal swing.

Keywords: Numerical simulation | Power Module | Reliability | Silicon Carbide | Thermal characterization

Abstract: Automotive domain is making rapid growth in next generation cars development embedding higher levels of autonomy and intelligent assistance. Although the general advanced driver assistance system (ADAS) architectures are widely debated in the global automotive market, limited interaction between driver and these intelligent solutions sometimes make these solutions inefficient. For these reasons, the authors started an investigation about driver's feedback with respect to the intelligent assistance inputs provided by the ADAS technologies. In this context, the goal of this proposal is to show the implemented intelligent system which learns from the analysis of the car driver's eyes saccadic movements, the correlated level of attention towards the salient driving scene. With this approach, the authors were able to collect a kind of visual-feedback signal which learns the driver eye's fixing dynamic associated to the analyzed driving scene. Through ad-hoc enhanced motion magnification technique, the authors were able to amplify the mentioned saccadic dynamics to allow a downstream deep classifier to associate this physiological behavior with the corresponding level of the driver attention. The collected performances (near to 97)

Keywords: ADAS | Deep Learning | Driver eye saccadic movements | Motion Magnification

Abstract: In automotive and industrial domains, the “health monitoring” or “condition monitoring” of electronic devices is gradually playing a key role in manufacturing processes and innovation roadmaps. The concept of health monitoring is often related to the so-called “residual lifetime” of the monitored system. In this work, the authors have designed a deep learning system for the health monitoring of power devices in Silicon Carbide (SiC) technology used in the Traction Inverter Systems of the latest generation electric cars. A Temporal Fusion Transformer embedding such layers of Temporal Convolutional Network with a Multi-Head Attention block for the robust lifetime assessment of SiC power devices, is proposed...

Keywords: Device Health Monitoring | Intelligent vehicles | Inverters | Monitoring | Multichip modules | Performance evaluation | SiC Power Module | Silicon carbide | Temperature measurement | Temporal Fusion Transformer

Abstract: The hybrid and battery electric vehicle market is heavily increasing the demand for semiconductor power modules. The manufacturing of such products is more complex than discrete devices. Some parameters, such as module deformation (warpage), play a major role. Power modules have to comply with customer Geometric Dimensioning & Tolerancing (GD&T) targets in order to avoid coolant leakage during operation and to guarantee mechanical compatibility with the driving board. Compliance with an appropriate flatness tolerance reduces rejects during manufacturing processes such as ultrasonic welding, and the consequent impact on reliability. Due to these requirements, there is a need to implement dedicated countermeasures during manufacturing flows and to develop the proper methodologies to monitor flatness tolerances. Appropriate component selection at the design stage also limits flatness through the prediction of deformations during assembly flows using finite element model. This activity outlines the manufacturing flow for a direct cooled semiconductor power module and presents a method for product optimization in terms of flatness tolerance using a dedicated finite element model that calculates the warpage deformation induced by baseplate soldering and different ceramic substrate layouts. Furthermore, we describe experimental methodologies for measuring power module flatness and straightness across the manufacturing phases. Dedicated experiments were conducted for methodological and design validation.

Keywords: finite element analysis | flatness | Power module | straightness | tolerance

Abstract: Power converters and semiconductor devices are spreading their application fields, due to new renewable energy and automotive frameworks. In the electrified vehicles context, the even more stringent requirements, both in terms of performances and reliability, pose new challenges in the design phase of power switches. This paper analyzes, by means of finite-element simulations, a low-voltage power semiconductor system-in-package devoted to automotive applications, which integrates a MOSFET-based half bridge and a controller. Three simulation physical domains integrated in a unique flow are considered: thermo-mechanical, electromagnetic, and thermal numerical models. The aim is to develop a new comprehensive methodology which starts with a thermo-structural simulation of the package, then computes the on-state resistance and parasitic components to assess the electrical behavior of the package. Finally, a simulation check is made to verify if the power device performances are thermally consistent with applicative conditions.

Abstract: Wide bandgap material-based devices allow faster switching frequency and exhibit smaller losses than traditional Si devices; nevertheless, a complete understanding of the functioning of these new devices remains poorly understood. A fast battery charger for electric vehicles based on a converter employing SiC and GaN devices is here reported Besides, these two technologies are experimentally compared, in the same layout, to highlights their performance in terms of electrical dynamic and electromagnetic compatibility.

Keywords: DC-DC converter | EMI | GaN | isolated converter | SiC

Abstract: Modern semiconductor manufacturing production lines include several technological processes such as diffusion, wafer cleaning and epitaxy and therefore they are subject to degradation phenomena that must be carefully monitored. The processed semiconductor wafer consequently requires a very accurate testing phase which allows to detect the presence of defects to be traced back to the production line and which can have an impact on the downstream yield. The electric wafer testing phase (EWS i.e. Electrical Wafer Sorting) is certainly one of the key stages in semiconductor wafer monitoring in both classical silicon-based technology and modern silicon carbide production lines. The EWS validation phase includes the execution of several electrical tests directly on the integrated circuits (dies) over the wafer. The EWS electrical assessment outcome can be reported in a 2D binary image-map enabling the formation of specific visual patterns in accordance with the defect statistics found in the testing phase. Specifically, from this intelligent EWS analysis it is possible to early-assess defects in the production lines, electrical defects in the devices and finally a proper wafer-yield forecasting estimation. The classification of the EWS image-map visual patterns is a very challenging and time-consuming task. In that context, ad-hoc deep learning solution has been developed in order to perform supervised/unsupervised EWS image-maps patterns recognition and tracking. The related pipeline is composed by ad-hoc convolutional deep architecture with an innovative augmentation system based on spatiotemporal preprocessing of input EWS image-maps. The implemented architecture is able to classify the input EWS binary maps into a well-known pattern-classes whose features at the production line level and the impact on yield are known. The designed deep network is able to identify new EWS patterns not included in the already known classes, so as to address the production-engineer accordingly. The proposed pipeline shows very promising results as it is able to classify the tested EWS with an average accuracy close to 97%.

Keywords: Clustering | CNN | EWS

Abstract: Power modules development is becoming more and more important for switching applications, to improve electric and reliability performances. This paper presents an experimental-numerical method to characterize the reliability behavior of ACEPACKTM SMIT package, a top side-cooled module designed with a half bridge topology, which employs high-voltage silicon MOSFETs. The experimental test involves power cycling to study the reliability and thermal behavior. Then, a finite-element based model is developed to simulate test conditions, to calculate temperature behavior inside the package.

Abstract: The use of molding compound as encapsulant is nowadays increasing in semiconductor power module applications. The adhesion of package interfaces between copper components and molding compound is one of the key aspect for an improved durability. The presented activity proposes the fracture toughness characterization of copper–resin interface in a power semiconductor package due to different experimental tests and the cohesive zone method to describe interfacial fracture. Double Cantilever Beam (DCB) and Four Point Bending (FPB) tests have been executed on dedicated bi-material coupons. The scope of these trials has been to enhance two different propagation modes based on different ratio between mode-I (opening) and mode-II (sliding) according to a mixed-mode approach. Strain energy release rate (SERR) and mode-mixity have been estimated by a finite element analysis based on the virtual crack closure technique (VCCT) and the crack surface displacement method (CSD). The information about fracture toughness at two different mode mixity have been considered to predict the SERR for every arbitrary mode mixity. Finally, dedicated finite element models based on cohesive elements have been developed and calibrated considering the fracture toughness experimental values and the measured force–displacements behavior during the two considered tests. Dedicated physical analyses have been carried out to validate the proposed method.

Keywords: Cohesive zone method | Finite element analysis | Fracture toughness | Interface | Power semiconductor package

Abstract: Copper is nowadays replacing the traditional gold in wire bonding interconnections, due to lower cost, better thermal/electrical properties and reliability performances. The increased hardness of Cu imposes higher bonding force and ultrasonic power during the wire-bonding process, increasing the risk of stress-induced bondpad damage. The aim of the presented work has been the modeling and characterization of stress and deformations resulting from the ball-bonding phase in order to have a quantitative method able to optimize the process set-up and the manufacturing capabilities already at design level. A finite element model has been developed and benchmarked with experimental samples obtained by freezing the ball bonding process at different steps, on which the deformations occurred in the bonded copper ball and in the bondpad layers have been measured through Xe plasma focused ion beam (Plasma-FIB) cross sections.

Keywords: Copper ball bonding | FEM | Power semiconductor devices | Ultrasonic softening | Wire bonding

Abstract: The massive development of Hybrid and Electrical Vehicles is strongly impacting the semiconductor industry demanding for highly reliable Power Electronic components. These challenges mainly originate from Silicon Carbide MOSFET’s superior properties allowing high power, high temperature capability, fast switching transients and high electric field operations. All these features can be obtained in a significant reduced chip area. In order to benefit from the disrupting advantages of these wide band gap semiconductor based power devices, a strong focus on silver sintering, as one of the most promising die attach technologies, is needed to withstand these challenging requirements. The aim of this work is to develop an integrated methodology, numerical and experimental, to assess the Ag sintering die attach process for a SiC power MOSFET. Different process parameters have been benchmarked by means of physical analyses, performed at time zero and also after liquid-to-liquid thermal shock aging test. The sintering flakes densification process has been reproduced by Finite Element Analysis and the obtained morphological texture has been used for extracting the mechanical properties of the layer as a function of the thermo-compression process itself. A simulation method, based on the evaluation of the inelastic strain accounted per cycle has been used for matching the experimental results according to an aging model. Furthermore, it has been predicted the silver sintering performances considering an active temperature cycle. The proposed methodology has supported the optimization of silver sintering parameters and has calculated the reliability performances of the silver sintering joint due to costumer-like active temperature cycle. Negligible sintering degradation has been carried out with a predicted number of cycles over two millions, suggesting die attach failure is not a relevant reliability bottleneck.

Keywords: Active temperature cycle | Reliability | Silicon carbide | Silver sintering | Simulation

Abstract: We investigate the mechanism governing threshold voltage (VTH) hysteresis in packaged SiC MOSFETs. A double-ramp measurement method was employed for this scope, being able to accurately evaluate the time-dependent recovery of the positive VTH shift induced by the sweep-up of the gate voltage. Particularly, we studied the effect of the (i) gate driving voltage (VGH), (ii) recovery time (TOFF) and (iii) temperature (T) on the VTH hysteresis. No appreciable differences were observed among data collected at different VGH, whereas a recovery speed-up was observed at higher T values. Temperature dependent measurement of VTH recovery yielded a 0.3 eV activation energy, that has been associated to SiC/SiO2 interface traps located ~0.3 eV below the SiC conduction band.

Keywords: interface traps | SiC | V hysteresis TH

Abstract: In this work, the thermal characterization of a commercially available SiC-based power module named as ACEPACK Drive, specifically designed by STMicroelectronics for automotive applications, was carried out. In particular, we studied the dynamic thermal behaviour and temperature gradient of one leg of the ACEPACK Drive by a combination of high-speed thermal microscopy and conventional thermal mapping. As main result, the temperature distribution on the device turned out to be homogeneous, with a maximum at around ~99 °C in simulated operative condition.

Abstract: Imperfections in SiC die can have an impact on their mechanical properties, affecting the target of the high reliability standard, required in power devices intended for automotive applications. In this work the failure strength of 4H-SiC square die of different thicknesses has been determined through a ball-on-ring (BOR) test and compared with previous three-point bending test results. Moreover, an interpretation of the experimental results on the net deflection d-d0 at the center of the die sample, according to a revisited Vitman and Pukh equation, has been reported. This allowed to achieve an assessment of the effective or equivalent Young's modulus of the die, with the BOR equipment on back-grinded 4H-SiC die, thinned up to 110 µm. The BOR provided consistent values for the 180 µm thin samples with the results from the previous the 3-PB test and a value of the equivalent Young's modulus of (391 ±90) GPa for the 110 µm, which is comparable with the theoretical limit measured in 4H-SiC.

Keywords: 4H-SiC | ball-on-ring | equivalent Young's Modulus | failure strength

Abstract: One of the main bottleneck for power semiconductor durability is the solder joint reliability. A proper design of the interconnections between silicon chip and printed control board is needed to fulfill the strict industrial and automotive requirements. Considering that solders are alloys with melting temperature lower than 450∘C, high-temperature package processes and costumer profile condition enhances the visco-plastic solder degradation, affecting the joint dimensional tolerances and reliability. The mechanical characterization of solder compounds and processes results fundamental to achieve reliability and geometric dimensioning and tolerancing targets. The presented work proposes an analytical-experimental methodology to characterize the mechanical constitutive equation of a specific solder compound widely used in semiconductor industries that is SnAgCu. Visco-plastic solder behavior with respect to environment temperature is experimental detected employing different uniaxial tensile tests considering some scenarios in terms of strain rate and temperature conditions. These outcomes are numerically post-processed to find out the Anand parameters of the analyzed solder according.

Keywords: Anand model | Material characterization | Solder compound | Visco-plasticity

Abstract: The use of molding compound as encapsulating material is nowadays increasing in semiconductor industry. Such component guarantees excellent thermal and reliability performances than the current silicone-based gel, enabling higher working temperature for semiconductor device and mitigating the solder joint reliability bottleneck. The adhesion of package interfaces between copper components and molding compound is one of the key aspect for optimized durability. Dedicated experiments and theoretical framework based on fracture mechanic are needed for this purpose. The presented activity proposes the fracture toughness characterization of copper-resin interface in a power semiconductor package. Double Cantilever Beam (DCB) test has been executed on dedicated bimaterial coupon with an initial crack at interface. The aim of this test has been to enhance the fracture propagation mode-I (opening). Strain energy release rate (SERR) and mode-mixity have been estimated from this experiment developing a finite element analysis that is able to predict the crack length during the experimental DCB trials and to predict the energy release rate by virtual crack closure technique (VCCT). Mode-mixity has been estimated collecting displacements near the crack tip by crack surface displacement method (CSD). The proposed methodology for fracture toughness characterization represents a strong pillar to predict fracture behavior due to any load conditions and it is needed to describe interface adhesion by cohesive zone method (CZM).

Keywords: Finite element analysis | Fracture | Interfacial delamination | Power electronics | Virtual crack closure technique

Abstract: This paper proposes a control system for a quadratic boost DC/DC converter in a wide range of operations, based on an inner loop with a sliding mode controller, for reaching a desired equilibrium state, and an outer loop with integral-type controller, for assuring robustness against load and input voltage variations and converter parameter uncertainties. The sliding mode controller is designed with the extended linearization method and assures local asymptotic stability, whereas the integral controller is designed using classical frequency methods, and assures input–output stability. It is shown that the proposed controller also deals with the sudden changes in the nominal operating conditions; thus, if a change of the operating conditions takes place, the proposed control scheme automatically creates a sliding regime which stabilizes the converter trajectories to the new equilibrium point. Experimental results carried out on a suitably developed test set up show the effectiveness of the proposed approach.

Keywords: extended linearization | quadratic boost converter | robustness | sliding mode control

Abstract: Nowadays the increasing demand of high-efficiency power devices for automotive framework, forced the scientific community to develop new technologies capable to operate under intense power loads. Among the broad scenario SiC-based substrates represent a promising solution. This study focuses on a high-speed thermal characterization of a power module designed by STMicroelectronics (ACEPACK DRIVE) with the aim to provide a map of the temperature values reached at the surface upon current-pulse stresses. Thermal images collected on one leg show a symmetrical temperature distribution, with a maximum of around 60 °C on the device metals and ensures that any reliability issues due to the thermo-mechanical stress are avoided.

Keywords: Automotive | Power electronic device | Reliability | Silicon carbide | Thermal mapping

Abstract: This paper proposes an experimental method devoted at characterizing the maximum continuous drain-source current sustainable by a power semiconductor device. This information, strictly related to thermal limit of the package, is being more and more important, especially for automotive applications, where the robustness must be assured, in terms of reliability. More specifically, usually it is demanded a high value of current which the device must be handled. The test vehicle used in this work is the low-voltage LFPAK package, based on a silicon MOSFET. Moreover, a finite element based model is developed in order to numerically reproduce the experiment: in this way, it is possible to study the system in a more detailed manner, and changes in device's and cooling system's designs can be quickly evaluated.

Keywords: Electric measurements | Finite element analysis | Power packages | Thermal characterization

Abstract: Recently, estimation of the visual saliency map in car driving scenarios has received significant research interests. Visual saliency perception includes the processing of specific parts of the visual driving scene in which the subject (car driver) pays more attention (specifically the parts whose gaze is focused). This work makes further contributions to video saliency research with application on the sustainable assisted driver technologies. Ad-hoc Semantic Fully Convolutional Deep Network embedding Gradient-Reversal domain adaptation layer has been implemented to process the video frames captured by a commercial low frame-rate automotive-grade camera device hosted outside the vehicle. A parallel motion-magnified visual-to-physio drowsiness assessment of the car driver will complete the proposed full automotive solution. The collected experimental results confirmed the effectiveness of the proposed solution.

Keywords: ADAS | Deep Learning | physio-signal | Saliency

Abstract: Automotive industry is making rapid progress in the development of next generation cars with higher levels of autonomy and intelligent assistance. Although the general advanced driver assistance system (ADAS) architecture is widely discussed, limited interaction between driver and these intelligent solutions sometimes make these approaches inefficient. For these reasons, the authors triggered an investigation about driver's feedback in relation to the assistance inputs provided by the ADAS technologies. In this context, the goal of this proposal is the design of an intelligent system that learns from the analysis of the car driver eyes saccadic movements, the correlated level of attention towards the salient driving scene. With this approach, we enabled a visual-feedback system which learns the driver eye's fixing dynamic associated to the analyzed driving scene. Through ad-hoc enhanced motion magnification technique, the authors were able to amplify the mentioned saccadic dynamics in order to allow a downstream deep classifier to associate this physiological behavior with the corresponding level of the driver attention. The collected performances (over 97%) confirmed the effectiveness of the proposed method.

Keywords: ADAS | Deep Learning | Driver eye saccadic movements | Motion Magnification

Abstract: espite all the advancements, thermal characterization of GaN HEMT devices is still a challenging task today. In this paper we present a new transient measurement approach utilizing the gate current as temperature sensitive electric parameter (TSEP) and compare the results to the data captured using the channel resistance (Vds). The experienced differences are small, but repeatable. We examine the various factors that could cause artifacts in each method, but no evidence of measurement error was found.

Keywords: GaN | HEMT | thermal transient testing

Abstract: ilicon carbide (SiC)-based power modules in automotive applications are becoming more and more important in the framework of battery and hybrid vehicles. Consequently, the reliability concerns related to these products must be carefully assessed, considering the harsh environment of automotive applications. The aim of this work is to give some insights into the reliability assessments during the design stage of SiC modules devoted to traction applications, considering different aspects such as power cycle, thermal characterization, and solder joint reliability.

Keywords: Automobiles | Reliability

Abstract: Detection and identification of production defects in semiconductor industry is a key process to allow effective quality control of manufacturing. The advent of new technologies including Silicon and Silicon Carbide, highlights the necessity to have a robust detection system of wafer defects.The Electrical Wafer Sorting (EWS) stage based on defects map electrical analysis is suitable to spot anomalies and defect patterns in the wafer. This time consuming phase enables semiconductor companies to optimize and improve manufacturing process also through the usage of modern deep learning approaches. The proposed pipeline addresses the need to have a full-automatic wafer manufacturing defects identification system based on the EWS wafer map intelligent analysis and by using an approach based on a Deep Convolutional Neural Network combined with an unsupervised sub-system. The collected experimental results confirmed the robustness of the proposed approach.

Keywords: Deep learning | Machine learning | Pattern recognition | Silicon | Silicon Carbide

Abstract: Structural mechanics and mechanical reliability issues are becoming more and more challenging in the semiconductor industry due to the continuous trend of the device dimensional shrinkage and simultaneous increased operative temperature and power density. As main consequence of the downsizing and more aggressive operative conditions, the mechanical robustness assessment is now having a central role in the device engineering and assessment phase. The risk of mechanical crack in the brittle oxide layers, which are embedded in pad stacks, increases during the device manufacturing processes such as the electrical wafer testing and during wire bonding. This risk increases with the presence of intrinsic mechanical stress in individual layers resulting from the metal grain growth mechanisms, the stack layers’ interfacial mismatches in coefficients of thermal expansion and the temperature stress induced by doping diffusion and film deposition. The current trend of innovation in the electronic industry is going over the semiconductor material itself and it is now impacting the improvement of the Back-End of Line. Key actors are becoming the interactions between the semiconductor die and the device packaging such as adhesion layers, barriers and metal stacks. In the present work, different pad structures have been structurally analyzed and benchmarked. The experimental characterization of the pad structures has been done through a flat punch nano-indentation to investigate on the mechanical strength and the crack propagation. The considered mechanical load reproduces the vertical impact force applied during wire bonding process to create the bond-pad electrical interconnection. The obtained testing results have been compared to finite element models to analyze the stress distribution through the different layers’ stacks. Scope of this work is to demonstrate the validity of the proposed integrated numerical/experimental methodology, showing the impact of the metal connections layouts by the analysis of the stress notch factors and crack propagation behaviour.

Keywords: finite element | nanoindentation | Pad | stress analysis

Abstract: In recent years, the power electronics industry based on silicon carbide (SiC) has rapidly expanded, but suppliers are struggling to meet the market demand both for final devices and for the starting raw material, which nowadays consists of SiC wafers with a diameter of 150 mm (6 inches). For this reason, the top industrial players in the field of SiC power electronics are starting the development of next-generation wafers with a diameter of 200 mm (8 inches). This work describes the recent achievements in the implementation of the world's first industrial pilot line to produce power devices based on 200 mm SiC wafers. In particular, the crystal growth of the 200 mm SiC boules, the slicing and polishing of the wafers, the deposition of the epitaxial layer, and the first tests in the pilot lines are presented.

Keywords: 200 mm wafers | 4H SiC | 8-Inch silicon carbide | Epitaxial growth | Pilot line | REACTION

Abstract: In the presented paper it has been proposed a methodology that translates the customer conditions in terms of electric power into thermo-mechanical variables correlated with power module failure mechanisms. An initial analysis of power module failure modes will be presented, then the module temperature during inverter load profile will be numerically estimated. The so-obtained time-temperature during inverter operation will be converted using Rainflow-like approach into a pre-defined number of loading conditions. According to the time and temperature dependency of the typical failure mechanism, the mentioned loading cases will be characterized by different temperature swing and time duration. The extrapolated equivalent history will be a starting point to set durability tests aimed to predict reliability performances.

Abstract: New technological and packaging solutions are more and more being employed for power semiconductor switches in an automotive environment, especially the SiC-and GaN-based ones. In this framework, new front-end and back-end solutions have been developed, and many more are in the design stage. New and more integrated power devices are useful to guarantee the performances in electric vehicles, in terms of thermal management, size reduction, and low power losses. In this paper, a GaN-based system in package solution is simulated to assess the structure temperature submitted to a Joule heating power loss. The monolithic package solution involves a half-bridge topology, as well as a driver logic. A novel integrated electromagnetic and thermal method, based on finite element simulations, is proposed in this work. More specifically, dynamic electric power losses of the copper interconnections are computed in the first simulation stage, by an electromagnetic model. In the second stage, the obtained losses’ geometrical map is imported in the finite element thermal simulation, and it is considered as the input. Hence, the temperature distribution of the package’s copper traces is computed. The simulation model verifies the proper design of copper traces. The obtained temperature swing avoids any thermal-related reliability bottleneck.

Keywords: Automotive | Electromagnetic simulation | Finite element simulation | Gallium nitride | Half-bridge | Integrated package | Power devices | Thermal simulation

Abstract: The increasing demand in automotive markets is leading the semiconductor industries to develop high-performance and highly reliable power devices. Silicon carbide MOSFET chips are replacing silicon-based solutions through their improved electric and thermal capabilities. In order to support the development of these novel semiconductors, packaging technologies are evolving to provide enough reliable products. Silver sintering is one of the most promising technologies for die attach. Due to their superior reliability properties with respect to conventional soft solder compounds, dedicated reliability flow and physical analyses should be designed and employed for sintering process optimization and durability assessment. This paper proposes an experimental methodology to optimize the pressure value applied during the silver sintering manufacturing of a silicon carbide power MOSFET molded package. The evaluation of the best pressure value is based on scanning electron microscopy performed after a liquid-to-liquid thermal shock reliability test. Furthermore, the sintering layer degradation is monitored during durability stress by scanning the acoustic microscopy and electric measurement of a temperature sensitive electric parameter. Moreover, mechanical elastoplastic behavior is characterized by uniaxial tensile test for a bulk sample and finite element analysis is developed to predict the mechanical behavior as a function of void fraction inside sintering layer.

Keywords: Finite element analysis | Mechanical characterization | Physical analyses | Reliability | Silver sintering

Abstract: Power SiC MOSFETs are going to substitute Si devices by to their significantly better performances that make them much suitable in power switching applications such as electric/hybrid vehicles. The increasingly use of these devices in critical mission profiles requires an ever-higher reliability, whereas the increase of the dissipated power during high-speed working cycling due to short current pulses leads to unavoidable thermal and mechanical stress. Here, we propose a direct method to evaluate the mechanical stress due to current pulses. This method highlights that high Power SiC-based MOSFET undergoes to almost two different thermomechanical processes with completely different time scale. The results allow a link between the thermo-mechanical stress and the device failure conditions, with special focus on the current pulses effects on metal surface, as this is a main power devices weakness.

Keywords: Coffin Manson | Power MOSFET | reliability | silicon carbide | strain wide band gap semiconductors

Abstract: Electrochemical deposited (ECD) thick film copper on silicon substrate is one of the most challenging technological brick for semiconductor industry representing a relevant improvement from the state of art because of its excellent electrical and thermal conductivity compared with traditional materials, such as aluminum. The main technological factor that makes challenging the industrial implementation of thick copper layer is the severe wafer warpage induced by Cu annealing process, which negatively impacts the wafer manufacturability. The aim of presented work is the understanding of warpage variation during annealing process of ECD thick (20 µm) copper layer. Warpage is experimentally characterized at different temperature by means of Phase-Shift Moiré principle, according to different annealing profiles. Physical analysis is employed to correlated the macroscopic warpage behavior with microstructure modification. A linear Finite Element Model (FEM) is developed to predict the geometrically stress-curvature relation, comparing results with analytical models.

Keywords: ECD | FEM | Phase-Shift Moiré | Semiconductor | Warpage

Abstract: Nowadays, solder reliability in new power electronic packages is an important research topic. Therefore, it is of paramount importance to properly understand and model the material behaviour and to develop a calculation model to predict reliability performances. This work presents a thermo-mechanical analysis of different solder layers for a low voltage discrete package. The solder joint reliability between package and PCB is also considered in the simulation. This modelling activity is possible by employing the Anand visco-plastic model and by means of a finite element model implemented in COMSOL. The number of cycles to failure can be subsequently computed, with the Darveaux method, for fatigue life estimation purpose.

Abstract: The paper reports the mechanical properties of 4H-SiC die with different thicknesses, that have been determined through a 3-point bend (3-PB) test. In particular, it reports 1) the measurement of the failure strength of thin 4H-SiC rectangular die; 2) the Weibull analysis of the failure strength of 4H-SiC die, exploited to determine the maximal load that can be applied to the die, without any breakage; 3) the measure of 244±15 GPa for the effective Young modulus E of SiC die, gained from the 3-PB test elaborations.

Abstract: The high power demanding in many emerging power electronic applications requires innovative solutions in semiconductor field. One of the possible keys to satisfy this requirement is the use of more paralleled devices. For traction applications, parallel connection of Silicon Carbide (SiC) MOSFETs is widely employed. In this framework, the power devices are housed in module packages. This paper presents a parametric analysis of a SiC power module for traction inverters, with a three-phase topology, containing many paralleled dice for each swich. The scope of the work is to study this phenomenon with a numerical investigation based on a circuit simulation, evaluating the junction temperature in a case study. The parameters varied in the simulations are the threshold voltage and the drain-source on-state resistance.

Abstract: Crystalline micrometer size stripes in 2.2 μm thick Ge2Sb2Te5 phase-change material films were produced by irradiation with a Continuous Wave Laser of 405 nm wavelength. The shape and the dimensions of the crystallized regions were investigated by Transmission Electron Microscopy and then compared with simulations based on temperature-crystal growth velocity literature data. The temperature-time profile was determined taking into account the laser power, the optical and thermal properties of both the amorphous and crystalline phase. The mechanical properties of the amorphous and of the crystallized regions were characterized by an ultra nano-indentation technique. This procedure allows a direct and local measurement of hardness and Young's modulus in the amorphous and in the contiguous crystalline regions on the micrometer scale. The following values for Young's modulus and for hardness were obtained: 33±4 GPa and 2.00±0.3 GPa for the amorphous phase, and 51±8 GPa and 2.90±0.45 GPa for the crystalline phase. The stresses induced by the density increase in the crystallized region cause, on the irradiated surface, a series of fracture whose characteristic behavior depends on the laser power and on the spacing between two contiguous scans. These results are of relevance for the mechanical failure mechanisms in potential phase-change devices.

Keywords: Continuous wave laser irradiation | GST | GST mechanical properties | Ultra nano-indentation

Abstract: The presented work investigates about the deformation of semiconductor device induced by electrochemical deposited thick copper films. It enhances thermal and electric performances allowing to use copper interconnections without formations of intermetallic layers at the interfaces with consequent reliability improvement. Nevertheless, the induced deformation strongly affects manufacturability, criticizing the integration between different process steps. Experiment based on phase-shift Moiré principle has been performed to better understand the relation between warpage and temperature. Finite element model has been developed to reproduce the phenomenon in order to address the design and the process integration optimizing workability, electrical performances and reliability.

Keywords: Finite element model | Manufacturability | Power electronics | Process integration | Warpage

Abstract: Hybrid and full electric automotive market is strongly increasing the demand for power semiconductor modules. With respect to discrete packages, manufacturing of power modules is more complex and new process parameter, such as module deformation (warpage), assumes a key role for a robust design and to guarantee reliable application. The aim of this paper is to study the warpage behaviour during power module assembly flow by means of dedicated warpage measurement at different process steps. Once highlighted the most impacting process for warpage, a finite element model has been developed to reproduce phenomenology, predicting the induced deformation.

Keywords: Finite element modeling | Manufacturability | Planarity | Power module | Warpage measurement

Abstract: Si- and SiC-based fast on-board chargers require very special thermal strategies, to ensure high reliability in order to assess long life in harsh environments, such as the automotive one. Indeed, the power losses in the switches may lead to a severe temperature rise in the enclosed cabinet, causing a reduce lifetime of the system. In this paper, we propose a scalable fast charger for automotive applications able to manage a 7 kW power flow. A thermal simulation based on COMSOL Multiphysics is performed in this work. The study allows us to get a realistic evaluation of the higher temperatures reached by the active Si and SiC devices of the converter during the normal operation, at the steady state and at the maximum allowed power.

Keywords: automotive | DC/DC converter | fast charger | LLC | OBC | PFC | thermal simulation

Abstract: The Silicon Carbide (SiC) semiconductor material is playing a fundamental role in the development of new power modules. Due to its excellent physical properties, the power devices based on this novel compound improve the traction inverter performance in electric vehicles. This work presents a 3D Finite Element Model (FEM) and fluid dynamics simulation to investigate the behavior of a directly cooled SiC module structure. Furthermore, a two-step experimental procedure to thermally characterize the module is also reported. It comprises a calibration and, subsequently, the thermal impedance computation. The proposed FEM model is compared with experimental test results in order to demonstrate its effectiveness.

Abstract: In recent years, new efficient power devices have been implemented. Silicon Carbide has replaced silicon as regards the production and the utilization of many devices, such as MOSFETs, diodes, IGBTs and many others. SiC devices are characterized by a low reverse recovery charge, high carrier saturation velocity, by which it is possible to work at high frequency, and high breakdown voltage. Thanks to the great thermal conductivity and the wide bandgap, these devices can operate at high temperature and reach high voltages and currents. What is important to stress is the fact that power losses in SiC devices are lower than the silicon ones. These are the reasons why these devices are utilized in a wide range of technological applications, including power electronics. In this paper, power losses in Si and SiC devices are evaluated in simulation and compared to each other. In order to demonstrate the remarkable advantages of the SiC devices over the silicon ones, a study which makes use of an isolated DC-DC converter has been conducted. As regards the proposed full-bridge converter, SiC and silicon MOSFETs and diodes, of whom some static and dynamic parameters are defined, are used in order to transfer power from a DC voltage supply to a load.

Keywords: DC-DC converters | Isolated power converters | Power losses | SiC devices

Abstract: The valve train plays a major role in the performance of internal combustion engines by controlling the combustion process and it is therefore one of the key aspects for increasing the efficiency of combustion engines. Considering the dynamics, the spring force must be high enough to reliably close the valve preventing from seating bouncing due to surge modes after the valve closure. On the other side, the spring force should be kept as low as possible in order to reduce the engine friction losses and consequently the fuel consumption. In the high-performance engines, the valve springs have to be designed and optimized for sustaining higher stresses with compact dimensions leading to critical material and manufacturing processes. This requires a reduction of moving masses and a strong focus on design and process optimization of the coil springs for reducing the mechanical load and the friction losses at low engine speed. At the same time, valve train should be reliable at high engine speed. The calculation of stresses and contact forces for moving parts under dynamic load is essential for durability analysis. A method to calculate the contact of moving masses is described and proposed to justify valve motions experimental results. To fully understand the failure mechanism of test bed reliability trials, the dynamic stresses have been calculated modeling the real springs’ shape. The contact forces have been reproduced considering the coil clash effects and the dynamic behavior of the flexible spring.

Keywords: Coil clash | FEM | Multibody | Valve springs | Valve train

Abstract: Electrochemical deposited (ECD) thick film copper on silicon substrate is one of the most challenging technological brick for semiconductor industry representing a relevant improvement from the state of art because of its excellent electrical and thermal conductivity compared with traditional compound such as aluminum. The main technological factor that makes challenging the industrial implementation of thick copper layer is the severe wafer warpage induced by Cu annealing process, which negatively impacts the wafer manufacturability. The aim of presented work is the understanding of warpage variation during annealing process of ECD thick (~20 µm) copper layer. Warpage has been experimental characterized at different temperature by means of Phase-Shift Moiré principle, according to different annealing profiles. A linear Finite Element Model (FEM) has been developed to predict the geometrically stress-curvature relation, comparing results with analytical models.

Keywords: ECD | FEM | Phase-Shift Moiré | Semiconductor | Warpage

Abstract: Semiconductor power modules are the key hardware components of a traction inverter. It drives motor speed and torque, managing the energy exchange from battery to motor and viceversa. The increasing demand for electric and hybrid vehicle requests high performance power modules. Power semiconductor devices based on wide band gap compound, like silicon carbide (SiC), have excellent electrical properties in terms of on-state resistance, stray inductance and performance at high commutation frequency. One of the most promising solution is silicon carbide MOSFET power module in which each switch is made by several different dies placed in parallel. Embedded direct cooling system and novel materials with high conductivity (e.g., active metal brazed substrates) can be considered to enhance thermal performance. A robust method is needed to characterize and to predict power module temperature behavior considering the importance of the thermal performance to improve reliability and to optimize module weight and dimensions. According to several parallel dies inside each switch, classic method based on temperature electric sensitive parameter (TSEP) shall be validated with direct measurement. In this framework, it has been reported the thermal characterization of a power module for a traction inverter based on eight silicon carbide MOSFETs for each switch. Both TSEP and infrared measurements have been employed. Thermal behavior has been numerically reproduced, creating a simplified equivalent network and developing a predictive model by finite element method (FEM).

Keywords: numerical model | Power modules | SiC MOSFET | thermal measurements

Abstract: Belt drives are commonly used in various types of transmissions to link two or more rotating shafts. In order to transmit the motion, an effective grip on the pulley has to be set by imposing a pre-load on the belt. Moreover, the dynamics of the system is strongly affected not only by the geometrical and inertial properties but also by the imposed belt tension force as a functional parameter affecting the vibration characteristics. In the present work, it is presented an integrated methodology, experimental and numerical, to determine the dynamic behaviour of a water pump drive in a high-performance internal combustion engine.

Keywords: Belt | Internal combustion engine | Multibody model | Natural frequency | Vibration modes | Water pump transmission drive

Abstract: Solder reliability is a key aspect for the packaging of low voltage power semiconductor device. The interconnections among package components, e.g. the silicon chip and copper leadframe, and between package itself and the external printed control board (PCB) should be properly designed to ensure the automotive durability requirements. In this framework, the proposed paper introduces an experimental-numeric characterization flow with the purpose to analyze solder visco-plasticity and fatigue during passive temperature cycle. The presented methodology has included solder mechanical characterization aimed to determine the parameters of Anand model which reproduces the solder visco-plastic behavior and the mechanical properties' temperature dependency. Finite element model has been employed to calculate the inelastic work which solder dissipates during each temperature cycle. Simulation results serve as input to predict solder lifetime according to an energetic method. Moreover, failure analyses have been performed to assess the failure mechanism and to check model correlation in terms of number of cycles to failure forecast.

Keywords: finite element model | material characterization | power semiconductor package | Reliability

Abstract: REACTION is an EU Innovation Action Funded Project which aims to develop the first worldwide 200mm Silicon Carbide (SiC) Pilot Line for SiC based Power technology. The project, which mainly addresses the Smart Mobility societal challenge (car electrification), will allow to match the ever-increasing demand of requirements in terms of quality and cost constraint for next decade generation's power electronics. A major strength of the project is the complete value chain implementation of the Pilot Line, which integrates and optimizes the cooperation and partnership among producers of 8"SiC substrates and equipment developers, as well as SiC process technologists, RTOs and end-users partners, in order to deliver the final applications. Hence, to achieve innovative SiC power devices with improved performances, along with cost and size reduction, are the most relevant requirements addressed in the project that are expected to lead to a new stronger European supply chain for very compact SiC converters, ideal for the addressed Automotive application.

Keywords: Automotive | Package | Power Electronics | SiC | Smart Mobility

Abstract: This paper presents the results of the electrical characterization of a silicon Low Voltage Trench Gate charged-coupled Power MOSFET under external uniaxial mechanical stress. The stress was imposed by a 3 Point Bending system during electrical measurement of the oxide leakage current.

Keywords: 3 Point Bending | gate oxide | mechanical stress | Power device | Silicon MOSFET | Trench Gate

Abstract: This work has investigated the impact of crystallographic structure on SnAgCu (SAC) solder reliability at print board circuit (PCB) level. A detailed reliability analysis has been performed on packages with different solder thickness. The correlation between experiments and Finite Element Model results explains how NiAu metallization and the reduction of solder thickness improve the solder joint reliability performances.

Abstract: Innovation on semiconductors technology requires enhancements of all actors like adhesion layers, barriers and metal stacks, beyond of semiconductor materials themselves. In general, metallic layers influence the whole die performances. The composition and the layout of these metal layers are fundamental for the signal transmission from the frame to the die and vice versa, and therefore their improvement contributes to the die development in terms of performances and reliability. In the present work, two pad structures have been benchmarked and analyzed under the structural strength standpoint. The experimental comparison among the different pads has been done through a flat punch nanoindentation to highlight the material strength and the crack propagation phenomena. Testing results have been compared to finite element models to analyze the stress through the different layers. The findings of the work demonstrate the validity of the methodology adopted and show the importance of the metallic connections layouts for the stress concentration and crack formation analysis.

Abstract: The presented analysis has been aimed to evaluate the impact of die solder and sintering solution for automotive power modules in terms of thermal behavior. First, dedicated temperature measurements have been performed to evaluate the module thermal impedance in the two cases. Then, a lumped equivalent networks has been calculated, by means of a dedicated numeric, and finally function structures have been extracted.

Abstract: In this work the warpage of a power modules ceramic substrates due to temperature variation has been numerically calculated. It has been used a not linear finite element model, which account the experimentally characterized material properties, including the copper elastoplasticity. Model results have been compared with dedicated interferometric measurements to validate the model. As application example, it has been calculated the benefit in terms of temperature warpage realized with a different substrate design option.

Abstract: The presented work shows the results of investigations with respect to the microstructural evolution and the thermo-mechanical characterization of thick Cu films (20 mm), electrochemical deposited on silicon substrates. Warpage measurements based on Phase-Shift Moir´e principle have been performed considering different temperature profiles. A theoretical explanation has been proposed to justify experimental warpage behavior, also proofed by Differential Scanning Calorimetry (DSC).

Abstract: Copper wires are nowadays replacing the traditional Au material in wire bonding interconnections, due to lower cost, better thermal/electrical properties and reliability performances. The increased hardness of Cu imposes higher bonding force and ultrasonic power during the wire-bonding process, increasing the risk of stress-induced bondpad damage. The aim of the presented work has been the modeling and characterization of stress and deformations resulting from the ball-bonding phase. A Finite Element Model has been developed and benchmarked with experimental samples obtained by freezing the ball bonding process at different steps, on which the deformations occurred in the bonded copper ball and in the bondpad layers have been measured through Plasma-FIB cross sections.

Abstract: In the context of reliability of silicon Power Devices, we conducted a study on Power MOS Gate Trench devices. The stress tensor inside the device is characterized through experimental analysis and Finite Element calculation. A test bench is developed to investigate the impact of mechanical stress on the gate leakage current of examined devices.

Abstract: The massive development of Hybrid and Electrical Vehicles (HEV) is strongly impacting the semiconductor industry demanding for highly reliable Power Electronic components. Within the engine compartment installation space is of major concern, therefore small size and high integration level of the modules are needed. Conventionally devices are typically soldered to ceramics substrates that are vacuum soldered to water-cooled base plates. The known reliability limitations of traditional solder joints are significantly limiting the power density increase, limiting the maximum operative temperature and representing a strong constrain for using high performances devices such as wide bandgap compound like Silicon Carbide (SiC). Silver sintering today has started to replace the solder joint from chips to carrier substrates, leaving one major reliability bottleneck. Combining properly temperature, time and pressure, a strong, highly electrically and thermally conductive bond is formed. The aim of this work is to develop an integrated methodology, numerical and experimental, to assess the Ag sintering die attach process for a SiC power MOSFET. Different process parameters have been benchmarked by means of physical analyses, performed at time zero and also after liquid-to-liquid thermal shock aging test. The sintering flakes densification process has been reproduced by Finite Element Analysis and the obtained morphological texture has been used for extracting the mechanical properties of the layer as a function of the thermo-compression process itself. A simulation method, based on the evaluation of the inelastic strain accounted per cycle has been used for matching the experimental results according to an aging model.

Keywords: Die attach | Finite Element Model | Reliability | Silicon Carbide | Thermal shocks

Abstract: In the present work it is shown how stress engineering can be used in semiconductor industry to improve Power MOSFET transistor’s performance beyond simple geometrical downscaling. The aim of this paper is to present an integrated methodology, coupling modelling and experimental results, focused on the structural optimization of a power device by means of final passivation mechanical stress tuning. The proposed approach is based on a Finite Element Model that describes and predicts the mechanical strain of a singulated power device (MOSFET) validated by the correlation with interferometric experimental warpage measurements (Topography and Deformation Measurements). Scope of the activity is to engineer Power Devices with reduced intrinsic stresses in order to optimize the reliability performances. Controlled stress into a single semiconductor crystal oriented substrate can be managed at manufacturing level by several methods, including the introduction of a layer on the top of the substrate or around the gate region. From the knowledge of the mechanical boundaries, as a function of temperature, it is possible to predict the stress conditions impacting on device fabrication and on reliability performances. Moreover, according to the piezoresistive model, it has been evaluated the electrical characteristics (on-resistance) in the operative working condition range. According to the proposed approach an optimized passivation layer solution has been proposed, simulated by Finite Element model and validated by experiments.

Keywords: FEM | Moiré topography | Reliability | Silicon MOSFET | Warpage

Abstract: In [1] below, reference 1 is incorrect. It should read: A. Sitta, M. Calabretta, M. Renna, and D. Cavallaro, 'Solder joint reliability: Thermo-mechanical analysis on power flat packages' in Advances on Mechanics, Design Engineering and Manufacturing. Cham, Switzerland: Springer, 2017, pp. 709-716.Instead of Advances on mechanics, design engineering and manufacturing,in Proc. Int. Joint Conf. Mech. Design Eng. Adv. Manuf., Catania, Italy, Sep. 2016. [Online]. Available: https://rd.springer.com/book/10.1007/978-3-319-45781-9.

Abstract: In this paper an overview on Power Packages challenges and technology approaches is given. These challenges mainly originate from Silicon Carbide MOSFETs superior properties allowing high power, high temperature capability, fast switching transients and high electric field operations. All these features can be obtained in a significant reduced chip area. In order to benefit from the disrupting advantages of these wide band gap semiconductor based power devices, a strong focus on packaging and interconnection technologies is needed to withstand these challenging requirements. In addition one of the major and strong boost for Silicon Carbide technology development is given by the car electrification trend: The strict requirements for the Automotive Market are leading to a design and engineering oriented, since the preliminary stage of development, to optimize the reliability of Power Packages.

Keywords: Die Attach | Finite Element Model | Reliability | Silicon Carbide | Thermal Shocks

Abstract: The metallized insulating substrates work as mechanical supports for the circuitry of Power Module Packages. Due to their specific functions, substrates for power electronics are made by different materials. The conductive metal layers can assume different functions: the top metal serves as power circuitry routing while the bottom metal improves the mechanical robustness and thermal efficiency. Ceramic layer provides excellent electrical insulation. These features play an essential role in the operation of power modules, which are often operated at high voltage and high current density. The substrates, composed by materials with different thermal expansion coefficients, are subjected to cyclic stresses due to temperature variations induced by operative working conditions. The substrate layouts typically include differences in shape and/or thickness between the top and the bottom side; this generates asymmetrical distributions of stress/strain resulting in overall warpage. The variations of this warpage induce mechanical fatigue during lifetime and represent a limiting factor for reliability. The scope of the presented work is the characterization of the out of plane warpage of Active Metal Brazed substrates (AMB) by means of numerical approach. The elastoplastic properties of metal and ceramic have been measured, evaluating the thermal softening of the copper as well. These characteristics are needed to calculate AMB warpage through Finite Element Models (FEM), simulating the warpage induced by a passive temperature cycling. Warpage computed from numerical model have been benchmarked and validated with optical warpage measurements. The validated numerical model has been developed to optimize the substrate warpage variation during cycling improving the whole package reliability.

Keywords: Ceramic substrate | FEM | material characterization | warpage

Abstract: High temperature application and long term reliability are the future trends for power electronics. A key factor to enable future applications is the interconnection durability improvement under high temperature and thermo-mechanical cycling loads. Nowadays, the standard solders cannot fulfill the reliability requirements of future power electronic devices, therefore interconnection technologies have to be developed. One of the most promising joining technique is Ag sintering. Combining properly temperature, time and pressure, a strong, highly electrically and thermally conductive bond is formed. The aim of this work is to develop a methodology to assess the Ag sintering die attach process for a SiC power MOSFET. Different process parameters have been benchmarked by means of physical analyses, performed not only on just assembled devices but also considering the aging effect induced by a liquid-to-liquid thermal shock test.

Keywords: Ag sintering | Power devices | Reliability | Thermal shock

Abstract: The purpose of this paper is to predict the device lifetime under a power cycling test by a simulation method that is based on a distributed self-heating SPICE model. Correlation between numeric extrapolation and experimental data is done by considering the Repetitive Avalanche test, a particular active temperature cycling that evaluates the ruggedness of a power device. The considered failure mechanism is due to front metal aging that produces contact resistance degradation. This phenomenon is strongly dependent on temperature, and by the proposed simulation tool, validated with experimental data, it is possible to evaluate the accurate temperature map and, consequently, predict the lifetime.

Keywords: active cycle | Metal aging | predictive simulation | reliability

Abstract: The working principle of a Phase Change Memory (PCM) cell exploits the repeated reversible transition between a crystalline and an amorphous phase of chalcogenide alloys typically Ge2Sb2Te5, that are characterized respectively by a high (SET) and a low (RESET) conductive state. The change in density between the two phases (6%) induces a very high compressive stress to the active amorphous region by the surrounding crystalline materials. Moreover, the physical iterative transformation between crystalline and amorphous phase transformation introduces a swelling and deswelling effect. This is one of the key failure mechanisms that are limiting the reliability of the final integration of the PCM system. Knowledge of the mechanical properties of the amorphous phase is then an important factor. Amorphous structure, i. e. its short-range order, depends on the adopted formation procedure. In this paper we analyze the mechanical characteristics of sputtered amorphous Ge2Sb2Te5 thin layers and the modification introduced by ion irradiation, a procedure adopted to simulate the amorphous state produced by melt quenching. Measurements of Young's Modulus and Hardness were performed using Ultra High-Nano Indentation on plane samples. The values of both quantities increase of about 10–20% in the 30 keV Ge+ irradiated samples. This trend is due to the reduction of homopolar wrong bonds (Ge–Ge and Te–Te) present in the as deposited film. Thermal spikes associated to the impinging ion cause a local atomic rearrangement that results in a structure similar to that of the crystalline phase. The investigation was extended to cantilevers of length in the range 10–200 μm, with a layer of 100 nm Ge2Sb2Te5 deposited on 280 nm thick SiN. The cantilever modal analysis and the out of plane deflection measurements were correlated using a Finite Element modeling, that makes use of the mechanical values measured by Ultra high Nano Indentation. After deposition the amorphous Ge2Sb2Te5 layer is subject to a compressive mechanical shrinkage, this internal stress is released after ion implantation.

Keywords: Cantilever | Nano-indentation | Phase change material

Abstract: In the present work, we investigate some mechanical and electrical properties of a Chemical Vapor Deposition (CVD)-grown graphene layer transferred on 50 nm-thick Ge2Sb2Te5 chalcogenide and discuss the possible application of graphene as a scaled contact replacing metal lines in phase-change memory devices. At first, the graphene-chalcogenide interface was extensively investigated. The expected chemical composition was confirmed by means of Electron Energy Loss Spectrometry (EELS), and the absence of bond distortions in the chalcogenide layer after graphene transfer was proved through Raman spectroscopy. The latter evidenced also the presence of defects, further confirmed by Transmission Electron Microscopy (TEM) investigations. The quality of the contact stack was evaluated by means of the adhesion among layers and by the sheet resistance of the layers themselves. Scratch tests and numerical simulations revealed a stress distribution compatible with a failure of the interface where the graphene layer features a 2 %-void. Next, the contact resistance proved an effective good Ohmic quality with a high graphene sheet resistance, about 1400 Ohm/square, which suggests that a better optimized transfer process should be applied to reduce it more than one order of magnitude.

Keywords: CTLM | CVD-Grown graphene | Nano-scratch | PCM

Abstract: The scope of this paper is to work out a predictive method to estimate the power device reliability under active cycle tests. The proposed method is able to predict, through a numerical model, the local maximum temperature during test. The results validation has been pursued correlating the numerical thermal maps results with the experimental temperature distribution obtained from an infra-red camera. Front metal ratcheting has been recognized as the main root cause of contact resistance degradation during the considered reliability test (Repetitive Avalanche). This failure mode is dependent on the temperature variation for cycle, by which it is possible to predict the device lifetime according to the Coffin-Manson fatigue model.

Keywords: Avalanche Test | Numerical Model | Power Device | Reliability

Abstract: In the last decades the main focus for improvements in Power Electronics was mainly addressed on chip technology. Therefore, Power Electronic performance depends by a high ratio on package technologies and on their interconnections. In particular, the automotive industry has high requirements regarding cost efficiency, reliability and compactness. Increasing power densities, cost pressure and more stringent reliability target for modern power semiconductors are making thermal system optimization more and more important in relation to electrical optimization. This article will give an overview of the new methodological approach leaded by Finite Element (FE) simulation for new packages and interconnection solution ideas. A viscoplastic creep modelling is adopted for the solder taking into account time, temperature and stress dependences in Thermal Cycle. A parametric study is performed by changing geometrical solutions. The results obtained from the modelling has been used to form design guidelines that were also matched with experimental data.

Keywords: Finite Element Modeling | Power Electronics | Solder Joint | Viscoplasticity

Abstract: The valve return springs in the distribution chain of internal combustion engines constitute a fundamental component for the duration, efficiency and performance of the engine itself [1,2,3,4]. This is even more true for high-performance engines whose mechanical and thermal power leads to the premature deterioration of poorly designed components. The elevated forces in such engines necessitate, where the valve springs have not been substituted by alternative kinematic systems, progressive springs, i.e. springs with variable stiffness. Despite this fact, the literature does not contain any univocal methods for defining the geometry of this type of spring. In the present study, the question is approached on the basis of a numerical-iterative calculation, providing a general methodology which, starting from data regarding the functioning of the engine and the geometric volumes to be respected, leads to the definition of the optimal geometry of the helix, taking account of the trend of the stiffness, of the natural frequencies and of the loads over the entire operating range of the spring. Tests on springs calculated in this way were performed using multi-body software, in order to verify the correspondence between the initial design data and the real behaviour of the geometry generated. © 2011 SAE International.

Abstract: Engine efficiency and optimization are key aspects for automotive manufacturers. Lamborghini has particularly focus attention for reduction of time to market building up a synergic approach for new component's development using simulation, Know-how experiences, engine engineering expertise and experimental validation. In particular to reach the best results in the shortest time it is used, in the preliminary stage of development, a massive support of simulation analysis. In the Lamborghini approach analysis and simulation has become key aspects during concept and development of timing drives. This type of activity is used to support the development of better chain timing drives focusing on improving durability, lower friction, less noise and reduced cost in less time than conventional trial and processes. Even during the concept design phase it is useful to use a mathematical model to calculate dynamic forces and motions of a chain drive. These models are used to assess in detail the choice of drive layout, to check that component load limits are not exceeded and to make a first choice of the tensioner settings. Later, when the first prototype engines are available, measurements of timing drive sprocket motion, tensioner motion and tensioner force are typically taken. At this stage the model can be correlated to the measured data and then the correlated model can then be used to explore the potential for improvements to the timing drive during later phases of engine development. This paper describes the correlation of a mathematical model of a complex timing chain drive for a Lamborghini V12 gasoline engine to measurements made on a prototype engine. The depth of model required and the choice of stiffness and damping values needed to give excellent agreement between calculations and measured data are discussed. © 2011 SAE International.

Abstract: The valve return springs in the distribution chain of internal combustion engines constitute a fundamental component for the duration, efficiency and performance of the engine itself [1,2,3,4]. This is even more true for high-performance engines whose mechanical and thermal power leads to the premature deterioration of poorly designed components. The elevated forces in such engines necessitate, where the valve springs have not been substituted by alternative kinematic systems, progressive springs, i.e. springs with variable stiffness. Despite this fact, the literature does not contain any univocal methods for defining the geometry of this type of spring. In the present study, the question is approached on the basis of a numerical-iterative calculation, providing a general methodology which, starting from data regarding the functioning of the engine and the geometric volumes to be respected, leads to the definition of the optimal geometry of the helix, taking account of the trend of the stiffness, of the natural frequencies and of the loads over the entire operating range of the spring. Tests on springs calculated in this way were performed using multi-body software, in order to verify the correspondence between the initial design data and the real behaviour of the geometry generated. Copyright © 2011 SAE International.

Abstract: Engine efficiency is one of the key aspects to reduce CO2 emissions. In order to improve the emission maintaining high performance capabilities several devices are introduced in the system; variable valve timing technology allows more flexibility for modern engines to meet peak performance, fuel economy and low emissions targets [7] while providing good driveability. This paper describes the Lamborghini continuously-variable cam phaser model using a graphical technique, called Power Oriented Graphs (POG), this uses an energetic approach for representing the physical systems. The generally accepted approach is to calibrate an engine on a dynamometer and to adjust the operation of the engine to meet performance targets. With the current build and test approach, these adjustments may not be made until well into the development program, and this calibration is a costly and time consuming step in the engine development process: the main purpose of this works is showing how was described the model in order to get more easy and fast the calibrating operations. Furthermore the usefulness to model the system consists of analyzing in simulation many more system configurations than those available for real experiments so it's important using a simple methodology that is able to analyze the whole system's dynamic in order to reach the performance expectations. The results obtained were validated demonstrating the effectiveness of the POG technique. Copyright © 2011 SAE International.

Abstract: Engine efficiency and optimization are key aspects for automotive manufacturers. Lamborghini has particularly focus attention for reduction of time to market building up a synergic approach for new component's development using simulation, Know-how experiences, engine engineering expertise and experimental validation. In particular to reach the best results in the shortest time it is used, in the preliminary stage of development, a massive support of simulation analysis. In the Lamborghini approach analysis and simulation has become key aspects during concept and development of timing drives. This type of activity is used to support the development of better chain timing drives focusing on improving durability, lower friction, less noise and reduced cost in less time than conventional trial and processes. Even during the concept design phase it is useful to use a mathematical model to calculate dynamic forces and motions of a chain drive. These models are used to assess in detail the choice of drive layout, to check that component load limits are not exceeded and to make a first choice of the tensioner settings. Later, when the first prototype engines are available, measurements of timing drive sprocket motion, tensioner motion and tensioner force are typically taken. At this stage the model can be correlated to the measured data and then the correlated model can then be used to explore the potential for improvements to the timing drive during later phases of engine development. This paper describes the correlation of a mathematical model of a complex timing chain drive for a Lamborghini V12 gasoline engine to measurements made on a prototype engine. The depth of model required and the choice of stiffness and damping values needed to give excellent agreement between calculations and measured data are discussed. © 2011 SAE International.

Abstract: Engine efficiency is one of the key aspects to reduce CO 2 emissions. Lamborghini S.p.A. has focused attention on the engine friction modeling, analysis and measurement to understand and control the phenomena. To reduce friction it is necessary to improve understanding of the behavior of the engine components and to pay attention to detail at every tribological contact. The valvetrain can make a significant contribution to whole engine friction especially at low engine speed and this is particularly true for a high speed sports car engine. Direct acting valvetrains are often used for this type of engine to minimise the moved mass and so enable high speed operation. However the sliding contact between the cam and tappet results in higher friction loss than the roller finger follower valvetrain used on many modern passenger car engines. In addition, the high maximum engine speed demands a large valve spring force to maintain contact between cam and tappet. The large spring force can lead to increased valvetrain friction at low engine speed when the inertia force is low. Thus the development of calculation methods to quantify friction of direct acting valvetrains and support the design of components is important. This paper describes the use of advanced mathematical models to quantify power loss at cam/tappet contact, tappet/ bore contact and camshaft bearings. The mathematical models are sufficiently detailed to capture the major influencing factors while being quick enough to use to enable engine designers to make decisions in the required time frame. This paper compares calculated and measured friction data for the valvetrain of a high speed passenger car engine as tested on a motored cylinder head test rig. The system friction was measured and calculated across the operating speed range with different oil supply temperature. The effect of diamond like carbon (DLC) coatings on the tappets was quantified by measurement and analysis. © 2010 SAE International.

Abstract: Engine efficiency is one of the key aspects to reduce CO 2 emissions. Lamborghini S.p.A. has focused attention on the engine friction modeling, analysis and measurement to understand and control the phenomena. To reduce friction it is necessary to improve understanding of the behavior of the engine components and to pay attention to detail at every tribological contact. The valvetrain can make a significant contribution to whole engine friction especially at low engine speed and this is particularly true for a high speed sports car engine. Direct acting valvetrains are often used for this type of engine to minimise the moved mass and so enable high speed operation. However the sliding contact between the cam and tappet results in higher friction loss than the roller finger follower valvetrain used on many modern passenger car engines. In addition, the high maximum engine speed demands a large valve spring force to maintain contact between cam and tappet. The large spring force can lead to increased valvetrain friction at low engine speed when the inertia force is low. Thus the development of calculation methods to quantify friction of direct acting valvetrains and support the design of components is important. This paper describes the use of advanced mathematical models to quantify power loss at cam/tappet contact, tappet/bore contact and camshaft bearings. The mathematical models are sufficiently detailed to capture the major influencing factors while being quick enough to use to enable engine designers to make decisions in the required time frame. This paper compares calculated and measured friction data for the valvetrain of a high speed passenger car engine as tested on a motored cylinder head test rig. The system friction was measured and calculated across the operating speed range with different oil supply temperature. The effect of diamond like carbon (DLC) coatings on the tappets was quantified by measurement and analysis. Copyright © 2010 SAE International.