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.

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.

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.

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.

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.

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.

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.)

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.

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.

Nano-copper (nano-Cu) sintering is a promising lead-free interconnection technology for advanced electronic packaging due to its high electrical conductivity. However, practical applications are hindered by oxidation and limited sintering efficiency. Carbon nanotube (CNT) doping has been proposed to modify sintering behavior by influencing diffusion and interfacial interactions. In this study, molecular dynamics (MD) simulations and experiments were combined to investigate the effects of CNT doping on nano-Cu sintering and interconnection performance.Two MD models were constructed: a Cu NP–CNT dual-particle model to examine interfacial interactions, and a multi-particle model to evaluate overall sintering dynamics. Results show that Cu nanoparticle size significantly affects sintering, with 4 nm particles exhibiting optimal energy reduction at 500 K, while 2 nm particles show stronger bonding at 700 K due to partial melting. CNT doping in the multi-particle system increased defect density, improving bonding strength but compromising electrical and thermal conductivity.Experimentally, nano-Cu pastes doped with various CNT types and contents were tested. A 1 wt% CNT addition enhanced shear strength, while higher contents led to agglomeration, reduced uniformity, and degraded electrical performance. SEM revealed CNT accumulation at sintering necks, and XPS indicated potential interfacial reactions involving functional groups on CNTs.Overall, CNTs play a dual role in nano-Cu sintering—enhancing mechanical performance via defect formation but reducing conductivity due to interfacial resistance. Optimizing CNT surface chemistry and dispersion is essential to balance mechanical and electrical properties in future interconnect applications.

Cold atmospheric plasma (CAP) is widely used in domains such as disinfection, surface treatment and food preservation. When generated in air, CAP is rich in reactive oxygen and nitrogen species (RONS), such as ozone (O3). A dielectric barrier discharge (DBD) is a reliable method to create CAP. We developed a double-sided (twin) surface DBD with novel ‘interfractal’ electrode geometries. This fractal configuration creates stronger electric fields than the customary interdigital line geometry. So, CAP is produced more effectively, resulting in higher RONS concentrations. The performance of interfractal electrodes was compared to that of interdigital electrodes (IDE) in atmospheric air. Nanopulsed powering was used, since it is the most efficient for powering DBDs. Electrical and chemical characteristics (such as ozone level) were assessed. The results show that interfractal electrodes enhance the electric field, conduction current and ozone yield.

Underfill has an important role in the reliability of flip-chips, but voids formed during manufacturing can initiate fractures. Simulations can be used to predict when and where the fracture takes place. However, traditional mesh-based methods suffer from mesh distortions, require remeshing, and have long preprocessing times. In this work, the Material Point Method (MPM) is used to study the effect of the void size and relative distance on fracturing in the underfill. We find MPM can predict crack propagation without prior knowledge of the path, reduce preprocessing time, and eliminate remeshing. Therefore, this work aims to show MPM makes for an effective and efficient alternative to traditional simulation methods. Simulations are performed with MPM to investigate the effect of void size and distance between voids on crack propagation in the underfill. The results show that fractures occur later when the distance between voids is larger, but the rate of damage is significantly faster once a crack is formed. Larger void sizes increase the rate of damage, but no significant effect on crack initiation was found. These results show that the meshless material point method is a promising alternative for simulating fractures in the underfill.

In harsh offshore environments, large-area sintered nano-copper (Cu) interconnections, which serve as die attachment material or thermal interface material (TIM), are prone to degradation from hydrogen sulfide (H2S) corrosion. This study introduced a film-forming technique based on atmospheric pressure plasma jet (APPJ) to improve the corrosion resistance of large-area sintered nanoCu joint. The corrosion protection mechanism against H2S-containing atmospheric corrosion was investigated using both experimental methods and density functional theory (DFT) simulations. The key findings were as follows: (1) The deposition film, primarily composed of a Si-O3 network, effectively protected sintered Cu plate from corrosion by H2S gas, and maintaining the mechanical performance of sintered Cu joint after 384 h of H2S testing. (2) The dissociation products of the APPJ-treated precursor hexamethyldisiloxane (HMDSO), −OSiCH3 and −OSi(CH3)3, formed stable chemical bonds on the sintered nanoCu surface, resulting in the formation of −OSiCH3(O-CH3)2 fragments. (3) The −OSiCH3(O-CH3)2 fragments were unreactive toward to corrosion agents such as H2S, O2, and H2O, and also serving as a barrier to block their access to the sintered nanoCu surface. This study provided a comprehensive understanding of the corrosion protection mechanism of sintered nanoCu using APPJ-deposited films, offering valuable insights for improving the reliability of power electronics.

4H-SiC is widely employed in power electronic devices operating under high frequencies, voltages, and temperatures due to its exceptional physical properties. However, its inherent high hardness and elastic modulus induce inevitable residual stress during device fabrication. Raman spectroscopy, which leverages lattice dynamics, offers an effective, non-destructive, rapid, and contactless method for measuring these stresses. Nevertheless, its accuracy critically depends on precisely determining the Raman phonon deformation potential constant. This work investigates mechanically induced Raman shifts in 4H-SiC via first-principles calculations and in-situ Raman spectroscopy under hydrostatic and non-hydrostatic stress conditions. The E2(TO) and A1(LO) phonon modes exhibit sensitivity to hydrostatic stress, whereas A1(LO) remains largely unaffected under shear, reflecting directional vibrational differences. Theoretical predictions and experimental measurements agree well within 16% error, highlighting the effectiveness of Raman-based stress detection for 4H-SiC. This integrated theoretical–experimental approach provides a robust framework for stress and strain analysis, facilitating the design and fabrication of next-generation 4H-SiC electronic devices.

Power electronics devices, pivotal in advancing electronic system technology, are essential for energy saving, enhancing power control efficiency, reducing noise, and minimizing size and volume. The evolution of power modules is based on innovative packaging structures, technologies, and materials. This article provides a comprehensive review of inorganic nonmetallic packaging materials and technologies in power electronics packaging. It first analyzes the packaging structures and trends of power electronics. The article then discusses inorganic nonmetallic encapsulants such as cement and glass in detail. It also reviews traditional ceramic substrates and elaborates on the advantages of multilayer ceramic technologies, including low-temperature co-fired ceramics, as substrates, while looking forward to the commercialization of inorganic composite substrates such as SiCp/Al matrix composites and diamond. Subsequently, the article overviews inorganic nonmetallic fillers for thermal interface materials, emphasizing the application of two-dimensional materials such as graphene and boron nitride, and introduces inorganic nonmetallic phase change materials. Finally, it explores the application and future development trends of inorganic nonmetallic materials in embedded packaging technologies.

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.

Fan-Out Panel Level Package has become a trend in Silicon Carbide MOSFET packaging due to its superior electrothermal performance and cost-effectiveness. However, the increased size of multi-chip embedded FOPLP packaging introduces greater challenges in sample preparation and thermal-mechanical stresses. In this paper, a large-sized (20mm*20mm*0.78mm) FOPLP with 4 SiC MOSFETs embedded is investigated. A three-dimensional thermal-mechanical numerical model is derived based on heat conduction and elasticity theories. It utilized analytical solution of Fourier temperature conduction and finite difference results for thermoelastic models to describe the temperature and deformation distribution during the FOPLP operation. It also reveals the heat coupling issue of multiple chips. Compared with the finite element simulation, the proposed method shows less than 2.5 % error in temperature and 2.3 % error in deformation. The computational speed is one-tenth that of the finite element method, while the memory usage is reduced to one-fifth. To mitigate the influence of chip thermal coupling on temperature and warpage, an optimized layout was employed to achieve temperature uniformity improvement. Finally, FOPLPs with the two layouts were fabricated. The warpage was monitored using a digital image correlation platform. To achieve the same temperature, the current required for the optimized layout was increased by 9 %. The warpage of the optimized layout at 60 °C was reduced by 13.5 %, and at 100 °C it was reduced by 14.7 %, validating the accuracy of the model and the significance of thermal-decoupling.

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.

Triboelectric nanogenerator (TENG), advantageous in high energy density and flexibility, is promising as a sustainable energy source but can hardly be used to power edge devices directly due to its high-voltage AC output and varying capacitive impedance. To address it, this work proposes a power-conditioning interface with a fully integrated dual synchronous switch harvesting on capacitors (D-SSHC) rectifier for triboelectric energy extraction. Furthermore, a full digital duty-cycle-based (DCB) maximum power point tracking (MPPT) algorithm is developed to optimize the energy harvesting efficiency with simple implementation and continuous tracking. Designed and fabricated in a 0.18-μm BCD process, the proposed interface can extract energy at a maximum output voltage of 70 V. According to the measurement results, it achieves 99% MPPT efficiency and an energy extraction improvement of 598% compared to a full-bridge rectifier.