Scratch and mar behaviors are increasingly considered a measure of polymeric materials durability and suitability for a variety of high-end functional and engineering applications, especially the automotive and consumer electronics sectors. Plastic materials may be exposed to elevated temperatures during service. For instance, plastic components used for car interiors and exteriors may be subjected to elevated temperatures during summer months, which may directly impact scratch and mar resistance. The present study aims to determine and quantify scratch and mar resistance and visibility at high temperatures (from 23 °C up to 90 °C) for several thermoplastic polymers, namely polycarbonate, polycarbonate copolymer, poly(methyl methacrylate), and styrene-acrylonitrile. Yield strain is identified as a quantitative predictor for scratch and mar visibility resistance across multiple thermoplastics and temperature ranges. These findings provide guidelines for polymer design for high-temperature applications in automotive interiors. Implications of the present study for designing scratch and mar resistance of polymers are discussed. • Scratch and mar behaviors of thermoplastics from room temperature to 90 °C • Scratch and mar resistance decrease with increasing temperature • Scratch behavior shows a strong correlation with compressive yield stress • Yield strain predicts material resistance to scratches and mar visibility

Ensuring the stability and precision of voltage references is critical in the domain of automotive electronics, where consistent analog-to-digital conversion is essential. Zener diodes, commonly employed as voltage reference sources, suffer from thermal instability, which can degrade the overall system accuracy. Traditional validation methods are often manual, time-consuming, and susceptible to human error. This paper presents a fully automated test and validation framework that integrates Standard Commands for Programmable Instruments-based control of instrumentation with Serial Peripheral Interface-based communication between embedded microcontrollers. The system is capable of performing comprehensive temperature-based characterization of Zener references. Furthermore, a digital correction algorithm is implemented to mitigate temperature-induced voltage deviations. Curve-fitting techniques are used to model thermal behavior, and Horner’s method is adopted to optimize the computational efficiency of the correction function. The corrected values are validated against actual measurements to confirm improved voltage stability. The results demonstrate the framework’s potential for rapid, accurate, and repeatable validation of reference components in automotive environments, offering significant advancements in both test automation and system reliability. Experimental validation was performed on multiple Zener-based reference sources across a temperature range of -40°C to +125°C. The uncorrected voltage references exhibited thermal drift in the range of ±8-10 mV, corresponding to a stability variation of approximately ±0.12%. After applying the proposed digital correction algorithm, the residual drift was reduced to ±1.5 mV, achieving an improvement factor of nearly 6×. Curve-fitting and Horner’s method-based polynomial evaluation reduced computational complexity by ~40% compared to conventional polynomial implementations, enabling efficient real-time execution on resource-constrained embedded controllers. Overall, the automated framework achieved >95% repeatability across repeated test cycles, while reducing manual intervention time by more than 70% compared to traditional validation methods.

Abstract Printed Circuit Boards (PCB) defect detection constitutes a critical stage in electronic manufacturing, serving as a vital safeguard for product reliability, functional safety, and overall quality in industries such as automotive, aerospace, and consumer electronics. However, existing methods still face some key limitations, including the frequent omission of micron-scale defects caused by insufficient receptive fields and coarse feature representations, alongside high computational costs that hinder real-time deployment on resource-constrained production equipment. Therefore, this paper proposes YOLO-MDMN---an enhanced variant of YOLOv12n. First, the improved Monte Carlo Receptive Field (MCRF) module is integrated into the A2C2f module, which utilizes stochastic multi-scale sampling to reduce both target fragmentation and computational overhead. Second, the Dynamic Spatial-Preserving Feature Neck (DSPFN) is utilized to combine Space-to-Depth encoding with content-aware upsampling and adaptive fusion to preserve high-frequency details during scaling. Third, the Detect\_MBConv detection head incorporates adaptive expansion ratios, scale-aware depthwise convolution, and dual-pathway attention for improved efficiency. Finally, the Shape-Nwd loss function is applied to combine geometric constraints with adaptive Gaussian modeling for stable micro-defect localization. Experiments on PKU-Market-PCB dataset show YOLO-MDMN achieves 93.8\% mAP50, outperforming YOLOv12n by 3.5\%, while reducing parameters by 39.7\% and computation by 40.6\% and achieving real-time inference at 344.8 FPS, which demonstrates efficacy for resource-constrained industrial deployment.

This work presents the development and characterization of 3D‐printed mechanically driven giant magnetoresistance (GMR) sensors using self‐compliant spring structures and piezoresistive materials. Fused deposition modeling 3D printing has been employed to fabricate sensors from conductive and magnetic polylactic acid composite materials, enabling low‐cost and highly customizable designs. Three sensor topologies were fabricated to optimize magnetoresistive and piezoresistive responses. Electromechanical and magnetic characterizations showed that the self‐compliant spring arm width influences the device mechanical stiffness, piezoresistive response, and magnetoresistive sensitivity. Sensitivities up to 0.34%/mm for piezoresistive sensors with a 3‐mm arm under direct mechanical deformation and 0.77%/mT for the magnetoresistive sensors with a 1‐mm arm were obtained, with a response 10 times higher in sensitivity than other printed spin‐dependent GMR devices in the literature. The applicability was demonstrated in pressure sensing and noncontact magnetic position detection, integrated in a Bluetooth low energy application. The sensors showcased reliable performance under dynamic conditions at a frequency range of 0.1, 0.25, and 0.5 Hz, highlighting their potential in automotive, robotics, and consumer electronics. This work establishes self‐compliant structural design as an effective tool for fabricating mechanically driven GMR‐like sensors using low‐cost, additive manufacturing techniques, allowing further integration of geometry‐driven devices into increasingly interconnected IoT networks.

As new System-on-Chip (SoC) architectures continue to emerge at an accelerated rate, the need for efficient power management strategies has become imperative. The high functionality requirements combined with strict power consumption controls are essential in modern applications such as mobile computing, automotive electronics, and Internet-of-Things (IoT) systems. This paper reviews the implementation of SAIF-guided in-design IR analysis as part of the physical design process, serving as a logical extension of power-aware SoC implementation in Place-and-Route (PnR). By incorporating Switching Activity Interchange Format (SAIF) data earlier in the design cycle, designers can resolve IR drop problems more efficiently, leading to improved power integrity and enhanced chip reliability. The paper presents findings from recent work on dynamic mapping heuristics, voltage/frequency scaling, RTL-level optimization, and hybrid prediction models. It therefore provides a comprehensive discussion of power optimization techniques that leverage integrated modeling, validation methods, and predictive techniques. The combination of traditional and intelligent solutions in integrating power concerns into advanced SoC-based systems is demonstrated through UVM-based verification, machine learning-based power estimation, and clock-gating technology integration.

This study examines how United States chip export controls propagate through the semiconductor sector and reshape China’s integrated circuit value chain. Using the 2020 national input–output table, it constructs a complete allocation coefficient matrix to quantify supply-driven transmission effects on downstream industries. The analysis shows that regulatory revisions to the Export Administration Regulations, expansion of the Entity List, and implementation of the Foreign Direct Product Rule together create a multilayer restriction system covering equipment, software, and materials, which generates structural dependence in critical technological nodes. Empirical results indicate that communication equipment, computer manufacturing, and automotive electronics exhibit the highest exposure to chip supply constraints, while modern service sectors also demonstrate strong sensitivity due to their reliance on digital infrastructure. Chips therefore function not only as essential manufacturing inputs but also as foundational components of the digital economy. The findings highlight the systemic vulnerability of high-technology manufacturing and advanced services to external supply shocks and suggest that strengthening domestic innovation capacity and substitution capability is central to improving industrial resilience.

Abstract The increasing volume of electronic waste (e-waste) and shortage of critical materials emphasize the need for sustainable management of end-of-life printed circuit boards (PCBs). This study explores the techno-economic feasibility of reusing electronic components (ECs) from discarded PCBs, particularly used in automotive applications. We developed a systematic process involving manual disassembling with hot air guns, followed by a three-stage sorting process involving size-based segregation, magnetic separation, and optical sorting through convolutional neural networks (CNNs). The CNN-based sorting achieved over 99% identification accuracy, and electrical testing confirmed 98% of the components as functional for reuse. Techno-economic analysis of a simulated EC recovery plant showed encouraging financial outcomes, proving profitable even with a conservative resale value of 5–20% of market prices. A techno-economic model for a recovery plant was developed based on bottom-up costing, incorporating disassembly rates, labor productivity, equipment costs, reverse logistics, and resale value assumptions to evaluate break-even time and scalability across geographic regions. The research proved the environmental and economic benefits of integrating EC reuse into circular economy practices, offering a scalable framework for sustainable e-waste management. Graphical Abstract

This review analyzes the transition from silicon to wide-bandgap (WBG) and ultrawide-bandgap (UWBG) semiconductor materials for power electronics, focusing on Silicon Carbide (SiC) and Gallium Nitride (GaN) technologies. Following a PRISMA-based systematic review methodology, we analyzed 94 peer-reviewed publications spanning device technology, converter architectures, and system applications. We employ a bottom-up approach, progressing from fundamental material properties through device architectures and converter topologies to system-level implications. We examine how intrinsic material properties enable operation at elevated temperatures, voltages, and frequencies while minimizing losses. Through analysis of Figures of Merit and system-level Key Performance Indicators, we quantify WBG benefits across automotive, industrial, renewable energy, and consumer electronics sectors, demonstrating 3–5× power density improvements and 20–40% cost reductions. The review presents emerging device technologies, including vertical GaN for medium-voltage applications and monolithic bidirectional switches (BDSs), enabling single-stage power conversion. We provide the first comprehensive topology-level comparison of emerging vertical GaN and monolithic bidirectional switches against established SiC solutions, identifying specific applications where each technology offers advantages. A comprehensive topology-by-topology comparison between SiC and GaN is provided, offering design guidelines for device selection. The review addresses practical constraints, including dynamic on-resistance degradation, threshold voltage instability, and electromagnetic interference challenges for both SiC and GaN. Finally, we examine emerging UWBG materials (β-Ga2O3, AlN, c-BN, Diamond) and their development status, manufacturing challenges, supply chain considerations, and commercialization prospects for ultra-high-voltage applications.

Current high temperature substrate solutions provided by cofired ceramics are limited by factors including large line and space dimensions, a lack of integrated passive components, and incompatibility with vertically stacked heterogeneous integration methods. These limitations challenge the development of technologies for hypersonics, automotive electronics, geothermal downhole applications, and many others. In this talk, 3D Glass Solutions (3D Glass) presents design rules and data to support a photosensitive glass-ceramic (PSG) substrate which enables high routing density, integrated resistors, substrate cavities, and vertically stacked heterogeneous integration (3DHI) capabilities. We will articulate the advantages of using PSG ceramic as a substrate for high temperature electronics and share our work demonstrating this substrate in quasi-coax partial air transmission line. This work includes design rules for the substrate and electrical and thermal test data verifying functionality and reliability up to 500°C. The described work demonstrates a manufacturing platform for high temperature compatible advanced packaging technologies. In this presentation, we detail production and assembly factors that impact size, weight, and performance (SWAP) metrics for a variety of product definitions. We also discuss the reliability of simulation results vs. product test results to demonstrate a reliable design to product flow.

The Automotive Industry drives many innovations for electronics and uses state-of-the-art devices. From electronification to V2X communications to sensors and high speed processing these modules require increasing environmental requirements from the Automotive Electronics Council. Passive electronic components like capacitors and multilayer varistors that perform decoupling, filtering, and circuit protection functions enable ECU and IC capability. But these passives can limit full capability if they do not keep up with high temperature requirements while maintaining electrical performance. In addition to high temperature material and product advancements on active and semiconductor devices, an update on high temperature passive components is worthwhile. The focus will be on capacitors where material set and capacitance are largely impacted by operating temperature. High temperature advancements will also be discussed for circuit protection devices that must perform reliably and repeatedly in austere transient environments.

Purpose Lead (Pb)-free solder alloys are increasingly adopted in microelectronic packaging due to their environmental compliance and favorable mechanical performance. This study aims to investigate the effect of thermal aging on the mechanical behavior of Sn98.5-Ag1.0-Cu0.5 (SAC105) solder alloy doped with indium (1, 2 and 3 Wt.%) to enhance reliability in high-temperature electronic applications. Design/methodology/approach Specimens were fabricated via die casting and thermally aged at 125°C and 180°C for 72 h. Mechanical properties, including yield strength (YS) and ultimate tensile strength (UTS), were evaluated using a universal testing machine. Microstructural evolution was examined through scanning electron microscopy (SEM), and elemental composition was confirmed via energy-dispersive X-ray spectroscopy. Findings As-cast alloys with 1–3 Wt.% In exhibited progressive improvements in YS and UTS, with the 3 Wt.% In composition reaching 46 and 52.62 MPa, respectively – a 72% increase over base SAC105. This enhancement is attributed to solid solution strengthening and microstructural refinement. Although thermal aging led to strength degradation, indium-containing alloys retained superior integrity. Notably, the SAC105 + 3 Wt.% In alloy maintained a UTS of 44.75 MPa after aging at 180°C. SEM analysis revealed uniform indium distribution and formation of Cu6(Sn,In)5 and Ag3(Sn,In) intermetallic compounds. Practical implications Indium doping offers a cost-effective strategy towards sustainable and high reliability solder materials for automotive and aerospace electronics, with potential to reduce lead dependence in compliance with RoHD directives. Originality/value This work provides novel insights into indium’s role in reinforcing SAC105 solder alloys, supporting the development of sustainable, high-performance lead-free solders for thermally demanding applications.

High-speed solenoid valves (HSVs) are widely applied in fuel injection, hydraulic control, and high-speed switching systems, where their dynamic response performance directly determines overall system efficiency and stability. Considerable research efforts have been devoted to improving HSV performance, particularly through advancements in electromagnetic coil structures and driving circuits. However, investigations into magnetic isolation structures remain relatively limited. Existing designs often lack comprehensive parameter analyses and frequently suffer from issues such as complex fabrication and high cost, which hinder their broader application in engineering practice. To address these challenges, this study proposes a novel magnetic isolation slice design aimed at enhancing the dynamic response characteristics of HSVs. A quadratic correlation model was established to describe the relationship between magnetic isolation slice parameters and response time, and a response surface methodology was employed to systematically analyze the influence of these parameters on dynamic performance. The results indicate that optimized magnetic isolation slice parameters reduce the HSV opening time by 76.0% and increase the electromagnetic force at the fully open state by 46.9%, thereby significantly enhancing the dynamic performance of the HSV. This work not only significantly enhances the performance of HSVs in industrial automation, automotive electronics, and intelligent control systems but also has important implications for the design and performance optimization of precision scientific instruments, such as automated analytical instruments and fluid dynamics devices. This study provides essential technical support for the development of efficient and precise scientific instruments, contributing to the advancement of modern scientific instrument performance.

The growth of electrical/electronic (E/E) systems in vehicles intensifies the need to address their environmental impacts in the automotive industry. Existing tools for E/E architecture (EEA) development focus mainly on technical implementation, while corresponding environmental frameworks remain insufficiently integrated at the product design level. This paper introduces AutoPCM, an automated Large Language Model-based approach that augments human expertise by transforming manufacturing documents into product architecture decompositions. AutoPCM generates the Physical Component Mapping, a visualisation method for representing automotive electronic product architectures, and evaluates applicable circular strategies following the Eco-Sensitivity Framework, a product-centered view of possible circular strategies for distributed and centralised EEAs. Large Language Models interpret manufacturing documents to extract component relationships and joining technologies, generate clear matrix-based representations of product structures, and convert them into JSON Linked Data (JSON-LD) for circularity assessment. AutoPCM, implemented in Palantir Foundry, is validated on two automotive case studies, a headlight electronic control unit and a camera sensor, achieving high performance with F1 scores of 0.93–1.0 for matrix heading and 0.82–0.95 for joint coding. The approach enables real-time sustainability feedback, supporting designers and decision-makers in optimising EEAs for the circular economy.

ABSTRACTStructural supercapacitors integrating carbon fiber (CF) electrodes offer promising multifunctionality by combining load‐bearing capacity with energy storage. Surface‐functionalized CF electrodes paired with electrospun polymeric nanofiber separators can enhance triboelectric performance, while explaining one reason for increased capacitance of structural supercapacitors observed previously under mechanical deformation. Interlayer triboelectric charges from CF/separator interfaces are quantified in cyclic contact‐separation mode, harnessing the triboelectric series and materials that are further apart to maximize the output. Triboelectric measurements reveal that desized CF produces the highest instantaneous current output, however, its inherently low dielectric storage and rapid self‐discharge render it unsuitable for long‐term energy retention. In contrast, CFs functionalized with tailored chemical groups can achieve both robust triboelectric charge generation and stable capacitive output. Furthermore, a hybrid piezoelectric‐triboelectric layer within these CF composites enhances charge separation and leverages synergistic piezoelectric polarization to sustain higher voltage across the electrodes (e.g., charge density of 19.9 ± 0.2 µC m−2 between silicon‐functionalized CF and poly(vinylidene fluoride)‐trifluoroethylene (PVDF‐TrFE) separator, and 23.1 mF g−1 specific capacitance in a structural supercapacitor device). This work underscores the potential of combining triboelectric and piezoelectric phenomena within structural supercapacitors on the way toward self‐powered, load‐bearing components in aerospace, automotive, and wearable electronics industries.

The integration of power electronic converters in automotive systems has led to increased challenges in managing Electromagnetic Interference (EMI), particularly in components such as fuel pump drive systems. This paper presents an experimental characterization of conducted EMI-both common-mode (CM) and differential-mode (DM), generated by a synchronous DC-DC converter used to supply a 12V DC motor in a vehicle fuel pump. Two types of power switches, MOSFET and IGBT, are analyzed under identical operating conditions to evaluate their influence on EMI performance. The study is conducted using a dedicated experimental test bench that allows for accurate measurement of EMI emissions in real-world conditions. Results reveal distinct EMI profiles depending on the switching device employed, with the MOSFET configuration showing higher DM noise due to faster switching dynamics, while the IGBT offers a more moderate EMI spectrum. This experimental investigation highlights the importance of switch selection in automotive power electronics and contributes to the design of more EMC-compliant and reliable converter systems for fuel pump applications and beyond.

The imperative for EMC-optimized gate drivers in Gallium Nitride (GaN)-based automotive DC-DC converters stems from the stringent CISPR 25 standards and GaN’s intrinsic high-speed switching characteristics, which paradoxically exacerbate electromagnetic interference (EMI). This review distinguishes itself by proposing a novel frequency-domain classification framework (Zone I: <50 MHz for conducted harmonics; Zone II: >50 MHz for switching noise and ringing), which systematically organizes and assesses gate driving techniques against the triad of fundamental GaN EMC challenges: pronounced capacitance nonlinearity, low threshold voltage, and extreme parasitic sensitivity. Unlike prior surveys that primarily catalog techniques, the analysis elevates the gate driver from a simple switch interface to the central “electromagnetic actuator” of the power stage, explicitly elucidating its pivotal role in mediating the critical trade-offs among switching speed, loss, and EMC performance. A comprehensive evaluation and comparison of advanced techniques—from spread-spectrum modulation for Zone I to adaptive current shaping and resonant topologies for Zone II—are provided, alongside an analysis of their design trade-offs. Furthermore, this review presents a first-of-its-kind, phased implementation roadmap towards holistic EMC compliance, integrating intelligent hybrid control, heterogeneous integration, and system-level co-design. This review bridges the gap between device physics and system engineering, offering structured design methodologies and a clear future direction for achieving electromagnetic integrity in next-generation automotive power electronics.

ABSTRACT The three‐axis magnetometers are widely utilized in automotive electronics, industrial robotics, and intelligent navigation for motion recognition and attitude detection. But the conventional 3D magnetic field detection is realized with multiple orthogonal sensors, causing the spatial errors, non‐orthogonality, and bulky issue. This study presents an ultra‐low power 3D magneto‐impedance (MI) sensor based on a planar [FeSiBC 20 nm/Cu 6 nm] 50 /graphene microcoil/[FeSiBC 20 nm/Cu 6 nm] 50 heterostructure. Utilizing the synergetic effects of soft magnetic material's magnetoimpedance and graphene's Hall effect under the weak current excitation, it decouples the X, Y, Z magnetic field components in one measurement, avoiding the multiple steps required by the recent planar sensors. It possesses the ultra‐low power of 25 µW, high resolutions of 20, 20, 7587 nT/Hz 1/2 at the X, Y, Z direction, and real‐time detection capability. Experiments verify that the miniature sensor array improves the magnetic field imaging accuracy by around 65% compared to the conventional 1D Hall sensors in the magnetic field leakage test.

In this study, network-structured polysiloxane hybrimers (NPH 1–3) were synthesized for high-performance optical encapsulation, focusing on advanced LED applications. Among them, NPH 3 exhibited exceptional optical and mechanical properties. At wavelengths of 450, 520, and 635 nm, it demonstrated a high refractive index of 1.61, 1.59, and 1.58, respectively, and an outstanding transmittance of 96.5% at 450 nm. The material exhibited rapid curing within 4.5 hours and a high hardness of 76.2 Shore D, surpassing conventional encapsulants like epoxy resins and commercial silicone polymers. Notably, NPH 3 maintained excellent thermal stability, as thermal aging at 200 °C for 72 h resulted in only a marginal decrease in transmittance from 96.5% to 96%, which demonstrates its remarkable resistance to optical degradation under prolonged high temperature exposure. This high thermal resilience, together with its superior refractive properties, boosts light extraction efficiency by minimizing internal reflections, rendering the material exceptionally attractive for various optoelectronic applications. Beyond traditional LED encapsulation, the impressive thermal stability expands its applicability to systems operating at elevated temperatures, such as high power LED systems, high resolution sensors, photonic devices, aerospace and automotive electronics, and high-temperature industrial sensors. NPH 3 exhibits a well balanced set of properties, including high optical transparency, rapid curing kinetics, and enhanced mechanical strength, attributed to its network-structured phenylsiloxane framework. These characteristics collectively identify NPH 3 as a promising candidate for next-generation encapsulant materials in advanced optoelectronic systems where long-term reliability and high operational efficiency are essential.

High‐density interconnect (HDI) microvias are foundational to modern information technologies, enabling high‐density routing in advanced computing, 5G, automotive, and aerospace electronics. As microvia dimensions shrink and stacked architectures become ubiquitous, reliability gains have stagnated despite continued geometric optimization. Growing evidence shows that reliability in advanced HDI microvias is increasingly governed by the coupled effects of via geometry, materials selection, and time‐dependent degradation at the buried electroless–target copper interface, where nanoscale void nucleation, progressive interfacial decohesion, and locally thinned copper layers control damage evolution and early failure. This interface constitutes a heterogeneous copper material system whose microstructure and bonding integrity are critically shaped by manufacturing physics, including laser drilling, surface conditioning, seed‐layer continuity, and electroplating dynamics, yet remain weakly represented in geometry‐focused qualification standards. Recent advances in nondestructive evaluation, data‐driven defect analysis, and physics‐informed modeling now enable progressive interface degradation to be detected, characterized, and assessed prior to field exposure. Treating the electroless–target interface as a functional materials system and a primary design variable provides a pathway toward predictive, mechanism‐based reliability frameworks for next‐generation electronic substrates.

Wireless power transfer (WPT) systems are widely used in automotive and consumer electronics due to the many benefits they can offer. However, according to the inherent presence of power electronics and extended electromagnetic parts, they can be the source of significant electromagnetic interference (EMI). This paper investigates the conducted emissions (CEs) of a 1 kW WPT system, assessing the effect of the conductive shields of the coil assemblies on the CEs through a purely experimental approach. The study also considers the effect of power modulation implemented by a phase-shift control, and highlights its impact on the overall CEs behaviour. The objective is to provide a quantitative insight into the role of the shielding in WPT CEs, considering both the conditions of grounded and ungrounded shields. The measurements are conducted over the DC bus of a GaN-based commercially available evaluation board in order to guarantee the highest level of reproducibility of the results. The CEs are measured with an EMI receiver and the impedance seen from the system under test to the power supply is stabilized with a line impedance stabilization network (LISN).