Ion implantation and subsequent annealing reshape the defect landscape and stress state of compound semiconductors, yet the temperature-dependent mechanisms in SiC remain incompletely understood. Here, we utilize molecular dynamics (MD) simulations and confocal micro-Raman measurements to resolve how implantation temperature and post-annealing regulate lattice disorder, amorphization kinetics, and residual-stress evolution in chemical vapor deposited (CVD) 4H-SiC. MD reveals surface-nucleated amorphization that propagates inward, whereas elevated implantation temperatures activate defect recombination pathways that suppress amorphous-layer formation. Raman signatures of optical-phonon shifts, linewidth broadening, and amorphization bands track the coupled evolution of lattice disorder and stress. Experimentally, increasing implantation temperature smooths the surface (S_a 0.133 → 0.101 nm) and reduces the amorphous-layer thickness (from ∼700 nm at 25°C to undetectable at 500°C), while driving more compressive residual stress (−57 → −132 MPa). Post-annealing largely restores phonon lifetimes and eliminates amorphization signatures, consistent with the recovery trends predicted by MD. These results delineate a thermal-treatment window that controls amorphization and residual stress in 4H-SiC, providing a transferable Raman-based methodology for nondestructive assessment of implantation-induced damage in compound semiconductors.

Solder joint reliability related to failures due to thermomechanical loading is a critically important yet physically complex engineering problem. As a result, simulated behavior is oftentimes computationally expensive. In an increasingly data-driven world, it is popular to use efficient data-driven design schemes. Among the family of efficient optimization methods, Bayesian optimization with Gaussian process regression is a key representative. The authors argue that additional computational savings can be obtained from exploiting thorough surrogate modeling and selecting a design candidate based on multiple acquisition functions. This is feasible due to the relatively low computational cost, compared to the expensive simulation objective. This paper presents a novel heuristic framework for performing Bayesian optimization with adaptive hyperparameters across multiple optimization iterations. A comparative study shows the ability of adaptive Bayesian optimization to save on expensive objective evaluations with respect to the worst-performing regular Bayesian optimization scheme. As an engineering use case, the solder joint reliability problem is tackled by minimizing the accumulated non-linear creep strain under a cyclic thermal load. Results show that adaptive Bayesian optimization can at least match the performance of regular Bayesian optimization in terms of raw objective performance, but achieves this with half of the computational expense budget. This practical result underlines the methodological potential of the novel adaptive Bayesian data-driven methodology to achieve more efficient results and significantly cut optimization-related expenses. Lastly, to promote the reproducibility of the results, the data-driven implementations are made available on an open-source basis.

This study is motivated by a conceptual inconsistency in the physical interpretation of eight-chain hyperelastic theory, which arises from the combined effect of two distinct issues: the use of the marginal projection distribution p_z(|r_z|) as a surrogate for the full probability density of end-to-end distance p_r̄(r̄), and the subsequent reliance on a root mean square (RMS) approximation step in the micro–macro averaging of chain stretch. We first revisit this probabilistic mismatch by reformulating the probability density function of freely-jointed chains (FJCs) in terms of the squared end-to-end vector r², thereby restoring consistency on chain-level statistics. Building on this formulation, the micro–macro mapping averaging of chain conformational free energy is constructed directly in terms of r², leading to a one-step mean-field approximation that avoids RMS averaging. The modified probability transformation is examined by Monte Carlo sampling at the microscopic level. To account for interchain interactions, q-mean statistical description of micro tube confinement was incorporated, leading to the appearance of the general invariant I_q=λ₁^q+λ₂^q+λ₃^q. The resulting continuum constitutive model is assessed against multiaxial experimental data for several polymer networks, including vulcanized natural rubber, Entec Enflex S4035A thermoplastic elastomer, Tetra-PEG, and isoprene rubber vulcanizate. Comparisons with three existing hyperelastic strain energy formulations, the extended eight-chain, extended tube models, and the four-parameter ”comprehensive” model, demonstrate comparable phenomenological accuracy of the current model while providing a clearer and more consistent micro–macro physical interpretation of model parameters. A parametric study further illustrates how the dimensionless parameters n and q govern the shape of the macroscopic stress–strain responses. The present formulation provides a consistent theoretical basis within the scope of hyperelasticity and admits potential extensions toward more complex irreversible phenomena.

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

In this work, the Material Point Method (MPM) is reviewed for application in the microelectronics industry. Microelectronic processes often involve large deformations, evolving interfaces, multiphysics coupling, and complex geometries that challenge conventional mesh-based methods such as the finite element method (FEM). Meshless methods provide an alternative solution that avoids these issues. A comparison is made between Smoothed Particle Hydrodynamics (SPH), Element Free Galerkin (EFG), peridynamics, Radial Basis Function–Finite Difference (RBF-FD), and MPM, evaluated with respect to convergence, consistency and stability, boundary enforcement, adaptivity, coupling, and industrial applicability. Based on this assessment, MPM and its main variants (BSMPM, GIMP, CPDI, and TLMPM) are examined in depth. The method’s ability to address large deformations, moving interfaces, contact, history-dependent material behavior, and multiphysics interactions is examined. The underfill process is used as a representative use case to illustrate challenges such as free surface flow, void formation, thermomechanical coupling, and residual stress. Overall, MPM shows strong potential, although further benchmarking and validation are required for widespread industrial adoption.

Two-dimensional materials (2DMs)-based devices exhibit aerospace potential due to their superior properties. However, the operational reliability of 2DMs-based devices in space environments is significantly influenced by charged-particle radiation, necessitating rigorous ground-based radiation tolerance assessments. Current research on radiation effects in 2DMs is primarily experimental, yet such methodologies are inherently time-consuming, resource-intensive, and limited in throughput. To address these challenges, computational modeling and simulation techniques are increasingly being integrated with experimental characterization to accelerate materials design and unravel underlying physical mechanisms. This review systematically evaluates the state-of-the-art multiscale computational frameworks for 2DMs research, focusing on recent advancements, technical challenges, and emerging opportunities. A novel integrative approach is proposed, combining density functional theory, molecular dynamics, Monte Carlo, finite element analysis, and machine learning techniques. Particular emphasis is placed on addressing challenges in multiscale modeling, including accurate representation of complex phenomena across spatial and temporal scales under extreme environmental conditions. Conversely, opportunities for enhancing predictive capabilities are highlighted, with implications for expediting materials discovery in electronics, photonics, energy storage, catalysis, and nanomechanical systems. This comprehensive survey provides a strategic roadmap for future research directions in multiscale computational modeling of 2DMs, emphasizing interdisciplinary methodologies that bridge atomistic simulations with macroscale engineering applications. The insights presented herein aim to advance the development of radiation-hardened 2DMs-based devices for next-generation aerospace systems.

Although silver sintering is widely used in die attach, its reliability under low-pressure and pressureless sintering conditions remains a challenge, and the degradation mechanism needs to be addressed urgently. This study investigates the degradation mechanisms of silver sintered die attach subjected to thermal shock (TS) (−45 °C to 125 °C), revealing its microstructural evolution, degradation of mechanical properties, and pore dynamics. After 1500 cycles, the average porosity did not decrease and remained at approximately 10%, but the porosity distribution exhibited significant heterogeneity, forming three characteristic regions of high porosity, low porosity, and crack regions. With the porosity evolution, the grain size increased by a factor of 2.1–2.8, with the largest grain sizes in the crack region, and the recrystallization fraction decreased significantly, from 89.6 % to a range of 37.3 %–72.1 %. Additionally, the combination with the decrease in both statistically stored dislocation density and total dislocation density reveals a decline in hardness and yield strength of silver sintered layer from 1.05 GPa and 326 MPa to 0.92 GPa and 231 MPa, respectively, gradually diminishing their ability to impede pore migration and merging. Thermal-mechanical coupling simulations based on the actual porous structure images show that the mismatch in the coefficient of thermal expansion induces alternating tensile and compressive thermal stresses, driving pore evolution and crack propagation. The kinetic Monte Carlo (KMC) Potts model based on Kawasaki dynamics combined with pore conservation can effectively predict the long-term pore evolution in this case. These findings provide important guidance for optimizing the sintering process and improving the application of silver sintering materials in high-reliability electronic packaging.

Ultrasensitive and specific detection of low-abundance tumor biomarkers remains a major challenge for early and minimally invasive cancer diagnosis. Here, we present a high-performance biosensing platform that integrates a genetically engineered bacterial S-layer with an AlGaN/GaN high-electron-mobility transistor (HEMT) sensor for label-free detection of tumor antigens. As a proof-of-concept, the ovarian cancer antigen human epididymis protein 4 (HE4) was selected . Specifically, the S-layer protein rSbpA was fused with HE4-specific nanobody 1G8 to construct a bifunctional membrane capable of self-assembling into an ordered biorecognition layer on the sensor surface. Compared to conventional chemical crosslinking, S-layer-driven assembly increased antibody loading by 50 % and minimized nonspecific adsorption in plasma environments. The resulting HEMT sensor detected HE4 across a dynamic linear range (10⁻²¹ to 10⁻¹⁴ M), identifying patients with ovarian cancer with 100 % diagnostic accuracy (AUC = 1.0). This study establishes a versatile and modular biosensing strategy for ultra-low-abundance biomarker detection with broad potential applications in the precision diagnostics of cancer and other diseases.

The reliability of through-glass via (TGV) interconnects is critical for advanced semiconductor packaging. This work investigates microstructural and mechanical evolution in electroplated TGV–Cu subjected to long-term aging at 250 °C. TGV samples were fabricated via laser-induced etching and double-sided copper electroplating, then aged for up to 1008 h. Nanoindentation revealed region-dependent reductions in hardness (from 2.0–2.5 GPa to below 0.5 GPa) and modulus (from 110–130 GPa to 40–90 GPa), with surface-near regions most affected. The glass substrate maintained stable mechanical properties until microcracks formed after 1008 h. EBSD quantification showed grain-size enlargement from 0.46 µm to 1.86 µm and a concurrent decrease in dislocation density. Molecular dynamics simulations of 3, 4, 5 nm grains corroborated the inverse relationship between grain size and micro-mechanical properties. A hybrid Potts-phase field model further linked grain coarsening to stress relaxation and elastic-energy minimization, revealing that as grains grow, the overall von Mises stress in the structure decreases; high-modulus grains retain relatively higher local stresses, while low-modulus, low-stress grains exhibit faster growth rates. Electrical I–V measurements confirmed stable ohmic behavior, despite a drop in insulation resistance. These integrated experimental and computational insights provide theoretical guidance for optimizing TGV interposer design and ensuring long-term operational reliability in heterogeneous integration technologies. (Figure presented.)

Control theory underpins the stabilization of dynamic systems, including cardiac tissue, where disruptions in electrical conduction cause arrhythmias. Current treatments either act rapidly but without precision or deliver targeted interventions that cannot adapt in real time. We present an integrated platform combining optical voltage mapping (OVM), machine learning (ML), and optogenetics for autonomous, real-time detection and correction of cardiac rhythm disorders in vitro. OVM provides high-resolution membrane potential visualization; the ML module identifies arrhythmic events and drives microLED-based light patterns restoring normal conduction; and optogenetics enables light-based modulation of excitable cells. This integration of electrical, optical, and bioelectrical domains through a unified computational control layer enables adaptive, closed-loop rhythm stabilization, a significant advance in real-time electrophysiological interventions. Because inference and actuation run in real time on modest hardware, the same control loop could be embedded into miniaturized devices or microcontrollers, accelerating the transition from in-vitro to in-vivo automated rhythm management.

Residual stress and thermally induced warpage are critical reliability concerns in power electronic packaging, particularly when employing sintered copper nanoparticle (Cu NP) interconnects. While these interconnects provide high thermal and electrical performance, they also introduce significant interfacial stresses during bonding that alter mechanical behavior during service. This study develops an integrated confocal Raman–analytical modeling framework to directly quantify and mechanistically interpret these stresses in a representative SiC/Sintered Cu NPs/Active Metal Brazing ceramic substrate (AMB) stack. Raman spectroscopy reveals a compressive interfacial stress field peaking at −334 MPa near the chip center with localized hotspots linked to microporosity. Complementary in-situ Moiré interferometry tracked warpage evolution during thermal cycle (30–310°C). Coupling this stress measurement with a three-dimensional thermoelastic model, and explicitly assigning the bonding temperature as the stress-free reference, enables accurate reproduction of the temperature-dependent warpage trajectory. The model predictions align with experimental interferometry within < 5% deviation. These results demonstrate that incorporating residual stress is essential to realistically capture thermo-mechanical evolution. The proposed Raman–model paradigm advances beyond prior purely numerical or purely experimental efforts by bridging quantitative stress mapping with predictive warpage modeling. This methodology provides essential insights for thermal-induced residual stress and warpage managements in high-temperature power electronics packaging, providing a stress-informed foundation for reliability assessment and design optimization.

The Electronics Editorial Office retracts the article “Effects of Current Filaments on IGBT Avalanche Robustness: A Simulation Study” [1], cited above. Following publication, the authors contacted the Editorial Office regarding errors identified in the simulation model and analysis presented in the article [1]. Adhering to our standard procedure, an investigation was conducted by the Editorial Board that confirmed that the simulation presented in this paper is incorrect due to the use of incorrect material parameters: Silicon Carbide (SiC) parameters were used, instead of Silicon (Si). Consequently, the conclusions drawn from this simulation are invalid and cannot be relied upon. As a result, the Editorial Office, Editorial Board, and the authors have concluded that this error undermines the validity and accuracy of the findings, and have decided to retract this article [1] as per MDPI’s retraction policy (https://www.mdpi.com/ethics#_bookmark30). This retraction was approved by the Editor-in-Chief of the journal Electronics. The authors agree to this retraction.

With the miniaturization and high-power requirements of microelectronic devices, the current density carried by interconnects in packaging structures continually increases and reaches the threshold of electromigration (EM) failure. In this study, we investigated the microstructure evolution and void formation in aluminum (Al) interconnects during EM at three different current densities (1/3/5 MA/cm ²) and proposed a method coupling the fully coupled theory with an optimized atomic flux divergence method. The results show as follows. First, for the interconnects in integrated circuits, current density is the main factor affecting the EM lifetime of the interconnects in a certain temperature range. With the gradual increase of current density, the contribution of thermal transfer on EM cannot be ignored. The atomic concentration gradient and stress gradient can inhibit EM failure. Second, the increase of length and the decrease of width of interconnect will lead to the increase of atomic flux inside the structure, resulting in the accumulation of voids and atoms. Third, the structure is dynamically reconstructed after deleting the atoms below the failure threshold and the simulation results agree well with the experimental results. Compared with the traditional atomic flux divergence method, the improved atomic flux divergence method based on the fully coupled theory can better fit the change trend of atomic concentration after interconnect failure, and the failure time error is reduced by about 10%.

This paper investigates the effects of three ageing factors (chemical, humidity, and temperature) and their interactions on the physical properties and degradation of silicone sealant used in microelectronic applications. The thermal degradation of silicone sealants was investigated by exposing samples to temperatures in the range of 150 up to 175 °C. Also, a set of samples were aged at 40 °C in a salt spray set-up with 100 % humidity in a salty atmosphere. Results showed detectable changes in the FTIR spectra of aged specimen as compared with the as-received sample. In all accelerated testing conditions, peak intensities decreased with ageing time, inferring that that the surface characteristics of the sealant is affected by ageing. Shear test results showed that with increasing the ageing time, the maximum shear stress in most cases has decreased in all ageing conditions. Also, it appears that samples with longer ageing times have experienced more elongation before failure. Results also show that salt spraying of specimens is associated with a decrease in the mechanical properties of the sealant, indicating the deleterious implications of ionic contaminations for the mechanical properties of samples.

Sintered materials have been widely applied, as an alternative to soldering, for power electronics packaging. One key issue for such die-attach material is to characterize the actual porosity, which is difficult to obtain through SEM cross-section analysis. Therefore, in this work, the optimized Quartet Structure Generation Set (QSGS) algorithm was applied to sintered copper joints under various porosity levels to reconstruct 3D porous structures based on 2D SEM images. Firstly, copper joints with varying porosities were fabricated under different sintering conditions. Reconstructed 3D porous copper models were then generated through the QSGS algorithm to match experimental observations, including porosity and pore size. Finite element analysis (FEA) simulations were further conducted to explore the effects of pores on thermal and electrical performance. This work provides a method for accurately predicting the thermoelectric properties of sintered copper joints and insights for optimizing copper sintering in power electronics applications.

The study focuses on the optical and electrical properties of Tungsten Ditelluride (WTe2), a type II Weyl semimetal, as well as the influence of its self-limiting oxide (SLO) layer that forms during natural oxidation. WTe2 exhibits promising applications in photodetection and energy harvesting due to its unique gapless linear dispersion and Berry-field-enhanced nonlinear optical effects. However, surface oxidation poses a challenge as it degrades the performance of WTe2. By employing spectroscopic ellipsometry and Raman spectroscopy, the progression of the oxide layer’s thickness and its impact on the optical constants of WTe2 were examined. The results revealed a rapid increase in oxide thickness within the first 24 h, and it reached saturation at ∼10 nm after 45 h of atmospheric exposure. Electrical properties were explored using Kelvin Probe Force Microscopy, uncovering a modification in surface potential and Fermi level following oxidation. Additionally, a SLO/WTe2 heterojunction device exhibited a wide region of positive and negative coexisting photocurrent, highlighting the potential for logical operations in ambient air. Finally, the mechanism of operation of the device is discussed. The electrical and optical properties of the pristine, partially oxidized and fully oxidized WTe2 are analyzed using density functional theory calculations. It shows that the SLO layer has a significant effect on the optical and electronic properties, which is instructive for future wavelength-modulated device optoelectronic logic operations.

With the rapid development of new energy vehicles and offshore wind power systems in coastal cities, the application scale of power devices is constantly increasing. However, the corrosion problem of power packaging interconnection materials caused by the humid air and chlorine-rich environment near the sea is gradually emerging. This study addresses the corrosion protection of sintered nano-copper by innovatively employing atmospheric pressure plasma jet (APPJ) technology with hexamethyldisiloxane (HMDSO) as precursor to construct organic-inorganic hybrid hydrophobic coatings on copper surfaces. Experimental results demonstrate that the coating exhibits a three-dimensional crosslinked Si-O network structure. The synergistic effect between surface micron-scale spherical clusters and methyl groups elevates the contact angle by 50 % to 153.1° Electrochemical characterization reveals that the coating positively shifts corrosion potential by 0.035 V and reduces corrosion current density from 6.008×10−7 A/cm2 to 5.542×10−7 A/cm2, while maintaining higher activation energy across the experimental temperature range (30–60℃). EIS tests show that the coating effectively increases the charge transfer impedance of the sample, indicating an improvement in corrosion resistance. The 168-hour immersion test confirms effective barrier against Cl−corrosive attack with preserved substrate integrity. Density functional theory (DFT) simulations elucidate that unsaturated methylated fragments in HMDSO preferentially graft onto copper surface via chemisorption, where strong interfacial bonding energies (-2.26 ∼ -4.38 eV) facilitate cleavage and crosslinking to form stable siloxane networks. This work proposes a novel anti-corrosion surface engineering strategy for copper interconnects, while revealing the plasma-induced interfacial bonding mechanisms of hybrid coatings, providing both theoretical and experimental foundations for developing durable electronic packaging materials.

The degradation mechanisms of silicon carbide (SiC) VDMOSFET and trench metal oxide semiconductor field effect transistor (MOSFET) in a 60Co gamma irradiation environment were investigated. The degradation of electrical characteristics of SiC MOSFET in different working states after irradiation with different total ionizing doses (TIDs) was explored. The defects induced during the irradiation process were studied in annealing experiments conducted after irradiation. The reasons for the degradation of SiC MOSFET caused by TID were revealed, and a prediction model of threshold voltage (Vth) shift was proposed and verified through TCAD simulation. The Vth, breakdown voltage (BV), on-resistance R, input capacitance (Ciss), output capacitance Coss, and reverse transfer capacitance C _rss were measured at different irradiation doses and annealing conditions. Experimental results indicated that the degradation of both Ron and Ciss was primarily caused by the Vth shift. As the doses increased, the shift in Vth gradually reached saturation. Similar trends to VDMOSFET were observed in trench MOSFET but with greater sensitivity to TID. In addition, MOSFETs biased at zero voltage exhibited lower shifts in Vth compared with those under high gate bias conditions. Furthermore, the increase in defects in the gate oxide during irradiation and annealing processes were calculated. Finally, a model predicting Vth shift path was established, and its accuracy and limitations were determined. This study provides valuable insights into the effect of TID on SiC MOSFETs.

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

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