This study investigates the peeling behavior of thin semiconductor chips during the laser transfer process for high-speed placement of chips thinner than 100 μm. A three-layer model consisting of chip, release layer, and glass substrate was analyzed using finite element simulation with a cohesive zone model (CZM). Material properties of both chip and release layer, including elastic and plastic behavior, were incorporated. Laser irradiation was modeled as transient load applied at the chip center or corner. Central loading reproduced the experimental detachment diameter, while corner loading initiated later but propagated more rapidly, resulting in a larger final peeling length. Although quantitative differences remained, the analysis successfully captured the experimental trends. The proposed approach provides useful insights for optimizing material properties included adhesive conditions and loading conditions, and contributes to the development of efficient, low-damage transfer processes for thin chips.

Printed circuit boards (PCBs) used in electronic devices are often subjected to random vibrations during transportation, which can cause fatigue failure at the terminals of mounted components. Accurate prediction of vibration-induced stresses is essential for reliable design and lifetime estimation. Since the main source of stress is deformation caused by the board’s vibration modes, the accuracy of deformation prediction directly affects the fatigue life evaluation. However, conventional models assuming uniform isotropic material properties cannot sufficiently capture the local stiffness variations caused by copper wiring patterns, resulting in reduced accuracy, especially for higher-order vibration modes. This study proposes a finite element modeling approach that incorporates local stiffness by dividing the PCB surface into a grid and applying binarization processing to identify copper pattern regions. Equivalent material properties reflecting copper stiffness are assigned accordingly. Furthermore, fatigue life under random vibration is predicted using Dirlik’s method for stress spectral analysis combined with the Corten-Dolan method for material fatigue correction. This approach significantly improves the accuracy of fatigue life prediction. The proposed model achieved good agreement with measured natural frequencies and mode shapes, and fatigue life predictions closely match experimental results.

Research on streamer discharges has long been conducted, mainly to elucidate dielectric breakdown phenomena. However, the streamer propagation is extremely fast, making it difficult to obtain sufficient spatiotemporal resolution in experimental measurements. Thus, simulation is evidently useful, but the electric field at the streamer head is so high during propagation that the calculations require a mesh with element sizes on the order of a few micrometers. Reducing the model scale has become a critical challenge. In this paper, we present an adaptive mesh refinement (AMR) approach and demonstrate its application to streamer propagation simulation in atmospheric air. Its effectiveness is evaluated by comparing it with conventional calculation methods.

Coupled simulations of vibration of a violin and acoustic radiation around it were conducted for antique violins such as Stradivari and Guarneri del Gesu. The detailed 3D geometric data for the violin were obtained by using a micro-CT scanner. Importing the geometric data of parts of the violin as top/back plate, bridge, sound post, etc. into the COMSOL Multiphysics software, the FEM calculations were conducted. Focused were the vibration in the first cavity mode (A0) and the sound radiation caused by forced oscillation in Stradivari and Guarneri. It was shown that the directions of sound radiations differed between the above two violins and the difference in directivity was observed at a higher frequency.

The purpose of this study is to design and manufacture of products applied 1/f fluctuation. In this study armrest , handrail, spoon were taken up as the manufacture and electro-cardiogram , heart rate, pulse wave are taken up as the human functions.

We propose a single vibration model, The state of the single vibration reflecting the reflector and repeatedly reciprocating was expressed for each step using the single vibration model, and the state of the whole mode was calculated by summing it. By repeating the reflection with the reflector, the energy of the vibration is stored between the reflectors. The formula can be expressed as the sum of the expansion formulas up to the nth order, but the final formula is described in detail so that it can be developed in an easy-to-understand form. And the effect of energy storage is shown in a graph in detail. This energy storage is a peculiar property of wave devices. The energy stored by reflection is stored in the increase in the applied voltage of the input electrode. This form of energy storage is formed by the repeated reflection of the waves and their sum.

In this work, multi-objective formulation for evolutional topology optimization is introduced considering an objective function and regularization term. This formulation makes it possible to obtain various resultant shapes in one optimization run without setting appropriate regularization coefficient. The method is applied to a magnetic shield design problem. The effect of multi-objective optimization is discussed.

This study proposes a fabrication-aware topology optimization framework that simultaneously determines substrate carving and electrode patterning for unimorph-type piezoelectric energy harvesters. The method employs a level-set representation with anisotropic regularization to satisfy Si deep reactive ion etching (DRIE) constraints, and it deliberately leaves the piezoelectric film on the entire substrate so that the balance of residual stresses among the multilayer films is maintained. The optimization minimizes the inverse electromechanical coupling coefficient under target resonant frequency and minimum output voltage requirements. Sensitivities obtained from the adjoint method guide a simultaneous update of the two level-set functions that represent the substrate and the electrode pattern; the iteration proceeds until convergence. A partial short-circuit boundary condition is also introduced: the electric field is constrained to vanish only inside the electrode-sandwiched region of the piezoelectric film, whereas a non-zero electric field persists in regions not covered by the electrodes. Eigenvalue analyses under both open- and short-circuit conditions are solved in a consistent finite-element framework to quantify the resulting frequency shifts. Numerical simulations predict that the proposed design improves the electromechanical coupling coefficient and meets the specified resonance targets without violating fabrication rules; they also suggest a tendency toward cantilever flatness. This point will be verified through prototype fabrication and experimental evaluation in future work. Preliminary numerical findings will be reported in the presentation, and full experimental validation is planned as a subsequent study.

This study presents a novel approach to analyze cure shrinkage stress of ultraviolet (UV) curable adhesives by incorporating curing reaction heat. The exothermic behavior during UV curing was measured using thermocouple temperature measurements under continuous UV irradiation. Results showed sharp temperature increases immediately after curing initiation, reaching peak temperatures around 0.1 degree of cure (gel point), followed by rapid cooling. The volumetric heat generation density was determined through inverse analysis to reproduce the experimental temperature profiles. Cure shrinkage stress calculations incorporating both reaction heat and cure-dependent shift factors revealed that stress decreases during the exothermic reaction phase, with higher peak temperatures leading to lower final curing stresses. This methodology enables prediction of thermal effects on curing stress behavior in precision bonding applications.

In this study, dynamic mechanical analysis was performed on UV adhesives during both the continuous UV irradiation phase and the post-irradiation dark reaction phase. The results showed that the dark reaction continued after UV irradiation ceased, reaching a cure degree of 0.7, though at a slower rate than during continuous irradiation. Relaxation behavior during the dark reaction phase was found to be independent of the curing method (continuous versus dark reaction) and dependent only on the cure degree. Tan δ and stress evolution followed similar patterns regardless of the irradiation conditions. FEM simulations successfully reproduced the experimental observations, demonstrating their potential for predicting relaxation behavior during dark reaction curing.

Thermal Interface Material (TIM) development with high thermal conductivity is necessary for power module of automobile. However, the mechanism analysis of heat transfer between filler and resin in TIM is not sufficient. In this study, the three-dimensional heat conduction was visualized, and the heat transfer coefficient of the interface was quantified as an experimental value. The heat transfer coefficient due to phonon conduction was calculated by the thermal molecular dynamics (MD) method, and the validity was verified. Moreover, based on this method, we calculated the relationship of heat transfer to the density and length of coupling molecules.

In recent years, as electronic components have become smaller and more powerful, more complex designs are required, and design methods that consider the coupling of multiple physical phenomena are needed. In general, electronic lines should have a structure with low electrical resistivity and high heat conductivity. The general-purpose solver in computer aided engineering (CAE) supports various physical problems, such as structure, heat, electricity, and fluids. A lot of CAE software have also a feature of topology optimization. However, the optimization function has been limited regarding physical problems, materials, and objective functions that can be applied. In this study, a multi-physics topology optimization program for electronic lines was developed in combination with general-purpose finite element method (FEM) simulation software. A coupled analysis of steady-state electronic current and heat conduction problem with the effect of Joule heat was considered. And we created to modify the model shape based on the calculation results of electronic potential and temperature. The numerical calculations to verify the program were carried out on a simple L-shaped geometric model. The optimized electronic line structure was designed to minimize electrical resistivity and maximize heat conductivity. The optimized structure showed the material placement that connects the fixed electronic potential part and the input electronic current part in the shortest possible way.

This study investigates the fatigue life of automotive connector solder joints under combined thermal and vibration loading, considering microstructural coarsening that occurs during service. A unified fatigue life calculation framework was established based on FEM simulations incorporating microstructure-dependent constitutive models and fatigue laws. By updating the microstructure over time via user subroutines, both thermal and vibration damage were evaluated and combined to predict total life. The results revealed that microstructural coarsening significantly reduces fatigue life and that the influence of vibration damage, initially negligible, becomes dominant as coarsening progresses. These findings highlight the importance of accounting for microstructural evolution in fatigue reliability assessment under combined loading.

High-resolution 3D microscale finite element models were developed based on FIB-SEM observations to accurately reproduce the complex pore structure of sintered Ag nanoparticle bodies. Then, numerical material testing simulations were conducted to analyze tensile behavior. The elastic analysis successfully reproduced the experimental elastic modulus of 39.3 GPa, confirming that the elastic properties are primarily determined by the pore structure rather than simple porosity correction. However, elasto-plastic analysis considering local stress concentrations and yielding could not fully capture the nonlinear behavior observed experimentally in the low-strain region. The results suggest that structural factors alone cannot explain the nonlinearity, indicating that material factors such as grain boundaries formed during sintering significantly influence the mechanical response and require further investigation.

In this study, a constitutive model is proposed to reproduce the Payne effect in filled rubber by separating the linear viscoelastic response into two Maxwell-type components: a large-strain viscoelastic model based on the Simo framework and a viscoplastic model based on the micro-sphere approach. The model parameters are identified from dynamic mechanical analysis (DMA) tests, including frequency–temperature sweep and strain amplitude–mean strain sweep. Using parameters calibrated only at 25 °C and 20 Hz, the model accurately predicts strain amplitude and mean strain dependence under different temperatures and frequencies. Despite its simple structure, the proposed model achieves both high predictive capability and thermodynamic consistency with computational efficiency. Finite element method (FEM) implementation examples will be presented during the conference.

The influence of test temperature on the fatigue crack growth (FCG) behavior of styrene-butadiene rubber (SBR) filled with 15 vol.% carbon black was investigated using a custom-built fatigue tester equipped with a temperature-controlled chamber. A pure shear specimen with dimensions of 146 mm × 15 mm × 2 mm was employed, and FCG experiments were conducted in air at 25, 45, and 60 °C under a test frequency of 5 Hz and a strain ratio of 0.1. The FCG behavior measured with the custom-built tester was in good agreement with that obtained from a conventional tester, demonstrating the reliability of the custom-built system. The FCG rate increased exponentially with temperature. At a tearing energy of approximately 1000 N/m, the FCG rate followed an Arrhenius-type dependence, and the apparent activation energy was estimated to be 73 kJ/mol.

The Incremental Variational Formulation (IVF) provides a thermodynamically consistent framework for inelastic analysis, however evaluating stresses and the consistent tangent modulus ordinarily demands cumbersome higher-order tensor differentiation. To remove this bottleneck, we embed the Complex-Step Derivative Approximation (CSDA) which delivers high-precision first- and second-order derivatives directly into IVF, thereby creating a high-fidelity, implementation-friendly scheme. When applied to a uniaxial tension–unloading simulation of a finite-strain linear viscoelastic solid, the CSDA–IVF response reproduces the reference solution with an average relative error of 0.82%. In addition, Newton–Raphson iterations exhibit clear quadratic convergence, confirming the method’s robust numerical performance. Because CSDA supplies accurate numerical derivatives, analysts are freed from laborious hand-derived tensor calculus and the overhead of configuring automatic-differentiation tools. The proposed CSDA–IVF thus enables straightforward deployment of sophisticated inelastic constitutive models by specifying only the energy potentials, making it well-suited for integration into commercial finite-element platforms.

The performance of the two next-gen tetrahedral smoothed finite element methods (EC-SSE-SRI-T4 and FC-SSE-SRI-T4) is evaluated in nearly incompressible large deformation analyses. There is a trade-off between computational cost and accuracy; thus, using FC-SSE-SRI-T4 instead of EC-SSE-SRI-T4 is expected to reduce computational cost at the loss of certain accuracy in deviatoric strain/stress. By comparing the analysis results with an initial Poisson’s ratio of 0.49, the pros and cons of the two formulations are clarified.

The phase-field fracture (PFF) model is attracting attention as a powerful tool for predicting complex fracture modes, but its accuracy relies on the accurate calibration of material parameters. On the other hand, the digital image correlation (DIC) method, which enables full-field measurement on the target surface through image analysis techniques, is utilized to capture deformation and fracture phenomena in various materials. This study proposes a robust framework to estimate parameters of the PFF model for ductile fracture based on a Bayesian data assimilation method that utilizes the strain field on the surface captured using the DIC method. To validate the proposed method, we conducted a uniaxial tensile test on a notched A5052-0 specimen and inversely calibrated the critical energy release rate. The proposed method successfully identified an optimal parameter by minimizing a cost function based on the difference between the experimental and simulated strain distributions. The validity of the estimated parameter was confirmed by a PFF simulation, which demonstrated a qualitative match in fracture behavior and a good quantitative agreement in the force-displacement response compared to the experiment. This work demonstrates the effectiveness of combining DIC measurements and data assimilation for calibrating PFF models.

SiC bipolar devices, as a representative of next-generation power devices, concerns over the increase in electrical resistance as single Shockley stacking faults (SSFs) expand, depending on the device design. Since the SSF expansion depends on multiphysical aspects including electrical, thermal, and stress states, the analysis and evaluation methods for the packaging structure of power modules are important for reliability design of power modules. We propose a reliability design method that uses the probability of SSF expansion as an indicator. It depends on the combines method with multiphysical finite element method (FEM) analysis accounting for electrical, thermal, and stress conditions and with a phase field (PF) model based on time-dependent Ginzburg-Landau (GL) equations. Estimating the probability of SSF expansion rate on the response surface under the mutiphysical inputs from FEM, the proposed reliability design method can be used effectively in the design process by changing the various design variables including distribution.

A coupled diffusion–stress model is constructed to simulate lithium concentration dynamics and the resulting mechanical stress within graphite particles. The objective is to quantitatively assess the impact of particle size on internal stress development. These insights are expected to support the microstructural design of negative electrode materials in lithium-ion batteries.

In this study, we conduct simulations to reproduce the initial shape formation process during the etching of aluminum electrolytic capacitors, based on a reaction rate model that depends on both the H⁺ ion concentration and the surface geometry. By introducing a model in which the dissolution rate varies between facet and edge regions, we demonstrate that cubic pit shapes can be reproduced.

In this study, we performed a pitting corrosion simulation that considers the cathode environment, specifically pH and the diffusion-limited current density. First, the cathode polarization curve was modeled based on the Butler-Volmer and Nernst equations. Next, using a zooming method, the results from a global domain electric field analysis that incorporated the modeled cathode curve were used to conduct a local analysis of pitting corrosion propagation.

In this study, we develop a microstructure prediction model that bridges a multi-phase-field method incorporating a nonlinear preconditioning with the temperature field obtained from thermal-fluid simulations, in order to accurately predict microstructural changes under various scanning strategies in metal additive manufacturing. The introduction of the nonlinear preconditioning improves the anisotropy of the grid and enables application to a wide range of scanning strategies. Furthermore, coupling with thermal-fluid simulations allows accurate reproduction of the complex temperature distribution induced by the laser heat source. Using this method, we perform high-accuracy microstructure prediction in metal additive manufacturing.

In this study, we developed a quantitative phase-field model for rapid solidification. The model properly accounts for solute trapping and solute drag, while accurately reproducing the solute conservation law at the moving interface and the Gibbs-Thomson effect in the thin-interface limit. In this presentation, we will particularly discuss how this model incorporates the characteristics of both the WBM and KKS models for description of thermodynamic state. This feature offers an advantage in describing rapid solidification.

A merging and jumping phenomenon of microscopic droplets on fine-structured and hydrophobic solid surfaces is investigated through a two-dimensional computational fluid dynamics (CFD) simulation of the droplets motion based on phase-field modeling (PFM). In the PFM-CFD framework, the Cahn–Hilliard (CH) equation is adopted to calculate the advection and construction of fluid interfaces between two phases. A finite element method (FEM)-based commercial software is used to numerically solve a set of the Navier–Stokes (NS) equations of two-phase fluid motion and the CH diffuse-interface advection equation for an immiscible incompressible isothermal gas-liquid flow system. The CFD simulation results are evaluated in comparison with available experimental data to optimally design a novel vapor chamber which can enhance dropwise condensation heat transfer with nano/micro-structured super-hydrophobic solid surface for cooling electronic devices more efficiently.

Molecular dynamics simulations show that molecular-scale "slip velocity" occurs in the fluid velocity motion near a solid wall, and it is known that its magnitude depends on the wall roughness as well as the physical properties (intermolecular potential) of the solid and fluid. Immersed-boundary flow analysis based on interface approximation using level sets and phase fields is understood to be a continuous approximation of this phenomenon. In this paper, we numerically verify and consider the reproduction of wall boundary conditions using wall roughness and interface approximation models in immersed-boundary flow analysis.

Fin-integrated phase change material (PCM) devices embedded in panel structures are being explored as passive thermal control systems for managing heat generated by high-power equipment in artificial satellites. In this study, we aim to streamline the design process of fin-integrated PCM devices by developing a surrogate model for coupled thermofluid analysis using Sparse Identification of Nonlinear Dynamics (SINDy). The proposed model demonstrates the ability to predict temperature variations with approximately 2K error in a generic 2D fin-integrated PCM device.

The Monte Carlo (MC) method is most exact but computationally expensive for uncertainty quantification (UQ). Instead, surrogate models can approximate UQ at a lower computational cost. However, as the input uncertainty dimensionality increases, the number of samples required to construct the surrogate models also increases rapidly; thus, the advantage of using surrogate models disappears. Therefore, it is necessary to combine the surrogate models with dimensionality reduction for effective UQ. This study compares the performance of UQ for the direct MC method and four different combinations of surrogate models and dimensionality reduction methods in benchmark test functions. The results clarify the effectiveness of training a surrogate model and a dimensionality reduction technique simultaneously rather than separately.

In the field of aerodynamic design for turbomachinery, automatic optimization techniques have been widely used to maximize performance. However, there are many challenges to achieving rapid development because these techniques often require extensive computational time. To address this issue, this study introduced a novel optimization algorithm known as Factorization Machines with Annealing (FMA) for aerodynamic design using fluid analysis. In the development of a turbo hydrogen compressor, we examined whether combining an optimization algorithm using an annealing machine (FMA) with fluid analysis technology could enable optimized design in a shorter period than conventional optimization systems.

To reduce the computational demand in the best estimate plus uncertainty (BEPU) analysis, an accurate and inexpensive machine learning model is expected to be used to replace the high-fidelity RELAP5 code for rapid determination of the uncertainties on the figure of merit of interest. Quantum circuit learning is an algorithm that can work on NISQ (noisy intermediate-scale quantum) computers. In this paper, the applicability of optimization methods that are popular in deep learning to quantum circuit learning was investigated in order to construct a model that is effective even with the hardware limitations of NISQ computers. Quantum circuits were implemented by Qulacs and defined as a custom layer in PyTorch. SGD was used as an optimization method. When SGD was used, convergence on training data was slow, but generalization performance on non-training data was good. It was concluded that by appropriately selecting the algorithm and the hyperparameters of optimization method of deep learning framework, a learning process can be achieved with good generalization performance and a learning model can be constructed with good prediction accuracy for the 95% cumulative probability value.

Nonlinear structural analysis, which can account for geometrical or material nonlinearities beyond the scope of linear methods, typically incurs high computational costs. Recent advances have shown that quantum computers can accelerate various numerical simulations. Although quantum acceleration of linear structural analysis via the Quantum Linear System Algorithm (QLSA) has been studied, its application to nonlinear structural analysis remains unexplored. Here, we introduce our proposed quantum algorithm for accelerating nonlinear structural analysis, summarizing its key features and performance results from our recent study.

To predict and simulate plasma phenomena, large-scale computational resources have been employed to develop high-precision, high-resolution plasma simulations. However, multi-scale plasma simulations require computational resources that scale polynomially with the number of spatial grids, posing a significant challenge for large-scale modeling. In this study, we present a quantum algorithm for simulating the nonlinear electromagnetic fluid dynamics systems that govern space plasmas. By applying Koopman–von Neumann (KvN) linearization, we map the nonlinear electromagnetic fluid dynamics systems to a Schrödinger equation and evolve it using Hamiltonian simulation via quantum singular value transformation (QSVT). The resulting algorithm reduces the computational complexity from O(N_x⁴) scaling of classical finite volume schemes to O(N_x log N_x), where N_x is the number of spatial grid points per dimension. And numerical experiments quantify behaviors of combined errors of discretization, KvN linearization, and QSVT-Hamiltonian simulation. As a practical demonstration, the method accurately reproduces the Kelvin-Helmholtz instability, underscoring its capability to tackle intricate nonlinear dynamics. These results suggest that quantum computing can offer a viable pathway to overcome the computational barriers of traditional multiscale plasma modeling.

In this study, based on the continuous dislocation theory, we introduce dislocation dipoles into CNT with discrete crystal structures to design nanosprings, propose a method that integrates mechanics and geometry, and analyze the mechanical and geometric properties of nanosprings. In detail, this study investigated the feasibility of designing helical CNTs through spontaneous deformation induced by dislocation dipoles separated from Stone−Wales defects. Analytical models were constructed by systematically introducing dislocation dipoles into (4,4) CNTs of varying lengths. We combined mechanical and geometric methods, performed molecular dynamics simulations to obtain the stable structure of CNTs with dislocation dipoles, and employed differential geometry to investigate the Willmore energy of helically shaped CNTs. The results showed that when dislocation dipoles were introduced into straight CNTs, energy relaxation calculations demonstrated spontaneous deformation, leading to the formation of a spring-shaped CNT. The CNT length and dislocation type significantly affected the spring constant. Longer CNTs exhibited lower spring constants, and an increase in dislocation density led to a higher average potential energy. This study provides unique insights into the control of the CNT shape and mechanical and geometrical properties, contributing to the design of functional materials such as nanosprings.

Semi-crystalline polymer typically exhibits complex viscoelastic-viscoplastic behavior including the double-yielding (DY) phenomenon. Uniaxial tensile tests at different strain rates were performed using PA specimens obtained at different annealing temperatures to evaluate the effect of the strain rate on the DY phenomenon. The slope of the stress-strain curve after the first yield and the distance between the first and second yields increased with decreasing strain rate. In contrast, the maximum stress observed during the DY phenomenon was independent of the strain rate, and uniform deformation continued for a longer strain range at lower strain rates. The viscoelastic-viscoplastic transient network model was generalized to reproduce the experimentally observed time-dependent DY phenomenon. The proposed method requires over 20 material parameters to reproduce complex mechanical behavior including time-dependent DY phenomenon. To obtain parameters accurately reproduce the experimental results, we introduced machine-learning supported Newton-Raphson identification process. The FEM simulation results with material parameters identified by the proposed method could accurately reproduce the experimentally observed mechanical responses.

In rate-independent strain gradient plasticity theories, boundary conditions regarding plastic strain or its gradient must be imposed at the interface between plastic and elastic regions inside the body. Previous studies have attempted to define these conditions based on physical considerations, but the issue remains unresolved. This study analyzes a pure bending problem numerically using a visco-plasticity model with a nearly zero viscosity parameter to detect appropriate boundary conditions for rate-independent cases. It is confirmed that, prior to full yielding over the thickness of bent specimen, the analytical solution assuming a zero plastic strain gradient at the internal interface shows good agreement with the numerical results.

We propose a unique one-dimensional (1D) nonlinear lattice with nonlocality. This lattice is referred to as the umklapp-free lattice (UFL), in which no umklapp processes occur. The absence of umklapp processes is mathematically guaranteed from the viewpoint of crystal momentum. In previous works, a methodology for constructing the UFL was presented, and a UFL with quartic nonlocal nonlinearity was proposed. We newly apply a cubic nonlocal nonlinearity to the UFL, rigorously determined to eliminate umklapp processes. A nonequilibrium steady-state simulation is also performed to evaluate the thermal transport properties of the UFL. It is revealed that thermal resistance, which corresponds to umklapp processes, is suppressed as the range of nonlocality increases.

Mechanical interpretation of flow phenomena in vivo is crucial for understanding pathological changes such as vascular disorders. Recent advances in fluid data assimilation combining clinical medical imaging with computational fluid dynamics (CFD) have enabled the reconstruction of flow fields faithful to observed data. While variational data assimilation effectively estimates physical parameters using CFD, its high computational cost limits clinical application. Physics-informed neural networks (PINNs), which embed physical laws into deep learning, offer a promising alternative, especially when combined with transfer learning (fine-tuning). However, applying fine-tuning directly to patient-specific geometries remains challenging due to the variability of vascular shapes. To address this difficulty, we propose a fine-tuning approach incorporating coordinate transformations. The method’s effectiveness is demonstrated on two-dimensional steady flow problems with simple geometries.

Lung surfactant is a substance that regulates surface tension on the inner surface of alveoli and prevents collapse, but its deficiency in premature infants is a factor that causes respiratory disorders. We investigate the effects of lung microstructure in mouse pups and the differences between the presence and absence of surface tension on the mechanical response by performing finite element analysis. The lung microstructure models are generated based on synchrotron radiation micro-CT images at 0 and 56 days after birth. The surface tension is modeled considering the hysteresis loop. Under positive pressure, the volume strain of 0-day-old mouse pups is larger than that of adult mice. The volume strain is suppressed by the surface tension effects, and its hysteresis loop can be captured with the proposed model. The mechanical response observed in our study may help in understanding the precise setting of ventilators for neonates.

Constructive research is a method for elucidating the mechanisms of phenomena that are difficult to measure. In constructive research, the aim is to elucidate real phenomena by simulating events using available data. Methods for simulating reproduction include humanoid robots and computer simulations. We conducted a study to reproduce swallowing movements using computer simulations and reported an example of simulating organ movements. In this study, in order to examine the suitability of the muscle synergy hypothesis, we estimated muscle activity rates using a musculoskeletal model created based on 4D CT of swallowing and the three-dimensional configuration of muscles, and performed muscle synergy analysis using the estimated muscle activity rates. As a result, multiple spatial patterns were suggested for the muscle synergy model, which we report here with a neurological examination.

Finite element human body models such as the Total Human Model for Safety (THUMS) have been widely used in automotive safety research, and their applications are now expanding into the medical and clinical fields. Spinal deformities, including scoliosis, are among the most important targets for simulation, since their severity is clinically evaluated using the Cobb angle. In this study, we attempted to reproduce scoliosis alignment in the THUMS spinal model by introducing a spinal alignment control method. Two approaches were compared: one based on applying external moments and the other directly prescribing the Cobb angle.

This study aimed to elucidate the mechanical basis for the effectiveness of combining square cross-section slots with nickel–titanium (NiTi) wires in the orthodontic treatment of dental crowding and tooth rotation. To this end, we evaluated the differences in orthodontic forces generated during rotational correction between conventional slots with a rectangular cross-section and those with a square cross-section. Furthermore, we examined how these force differences, arising from variations in slot geometry, may influence orthodontic treatment outcomes.

This study presents a 3D thermal field simulation of aluminum nitride (AlN) physical vapor transport (PVT) process based on Simdroid, the general-purpose multiphysics simulation software. The electromagnetic simulation was conducted to determine the Joule heating distribution using FEM, after which the temperature distribution of the growth system was calculated with the thermal module of the software. The radiation heat transfer was calculated by the view factor method, considering only the surface-to-surface radiation. Additionally, an inverse algorithm was adopted to determine the required power inputs given specified temperature constraints. This simulation process is now seamlessly integrated into the Simdroid, which allows for the convenient simulation of PVT process. The established methodology provides an effective numerical tool for optimizing PVT process parameters, particularly in addressing the dimensional limitations inherent in conventional 2D simulations. This study provides the validation of Simdroid's applicability in PVT thermal design through coupled electromagnetic-thermal simulation, with the separately discussed framework to mass transport, growth kinetics, and thermal stress analysis for PVT process optimization.

Diamond is a promising next-generation semiconductor because of its wide bandgap, high thermal conductivity, and excellent electrical properties. Microwave Plasma Chemical Vapor Deposition (MPCVD) method has been widely used for high-quality diamond epitaxial growth, but the process involves complex interactions among electromagnetic field, plasma dynamics, heat transfer, mass transport, and chemical reactions in the reactor. To analyze these phenomena, we developed a specialized simulation software, DiaDeMoTM, for modeling diamond epitaxial growth using MPCVD method. This software enables quantitative prediction of growth rate of diamond, and support reactor and process optimization. Using DiaDeMo, we investigated effect of pressure and microwave power to plasma density, temperature, radical species distributions, and growth rate on the substrate. Moreover, the simulation results were validated through comparison with optical emission spectroscopy measurements.

In recent years, the interplay of thermal, mechanical stress, and electromagnetic fields in electronic devices and semiconductor packaging has highlighted the growing need for Multiphysics Coupled Analysis (MPA) in integrated evaluations.Traditionally, these fields were analyzed separately using single-physics simulations, but early-stage development often led to missed conditions and repeated analysis, limiting design accuracy.MPA began around 2000 with unidirectional data linkage—electromagnetic to thermal to stress analysis. In the 2010s, GUI-based platforms enabled bidirectional coupling, allowing mutual interactions between physical domains to be considered.Since the 2020s, MPA has become a standard early-stage design tool, enhanced by cloud computing and AI, supporting complex packaging and next-gen high-speed communications.This paper reviews the background of MPA, recent applications, and advances in simulation methods and technologies.

Group IV compound semiconductors such as SiSn, GeSn, and SiGe are attracting attention as materials for electronic and optical devices. Their stable atomic configurations have been investigated in several experiments and theoretical calculations. In this study, we carried out density functional theory (DFT) calculations to examine the stable atomic configurations of Sn atoms in the Si (Ge) bulk up to a 50 % Sn concentration and Ge atoms in the Si bulk up to a 50 % Ge concentration, covering all independent atomic configurations while taking into account the symmetry of the crystal structure models.

SiGe alloys exhibit superior high-temperature thermoelectric performance and have consequently been implemented for decades in radioisotope thermoelectric generators (RTGs) of deep space probes. One of the reasons for their high thermoelectric conversion efficiency is the low thermal conductivity produced by phonon alloy scattering. In recent years, inelastic X-ray scattering experiments on SiGe crystals have revealed a new localized phonon mode in the low-energy range of 2–4 THz, which has been suggested to further reduce the thermal conductivity. Previous molecular-dynamics (MD) studies pointed out that this mode is related to collective vibrations of Si–Ge bonds surrounding Ge clusters; however, simulations of systems containing a wide distribution of cluster sizes could not reproduce the sharp spectral peak observed experimentally. In this work, we carried out MD simulations on systems with unified Ge cluster sizes, and a clear trend was observed that the intensity of the localized phonon mode increased as the cluster size decreased. Moreover, structures containing a high concentration of Ge dimers reproduced not only the sharp localized mode but also an intense Ge–Ge vibrational peak, in excellent agreement with the experimental spectrum. These results indicate that the SiGe alloys examined experimentally likely contained a high concentration of Ge dimers.

GeSn and SiSn are attracting growing attention due to their potential as direct-bandgap semiconductors for optical devices with higher Sn doping. To achieve a higher Sn concentration, thin film growth is carried out using substrates with a larger lattice constant, which imposes tensile stress on the Ge or Si thin films. In this study, we performed density functional theory (DFT) calculations to investigate the effect of Sn and vacancy (V) on the thermal equilibrium concentration of Sn in Ge and Si crystals under isotropic, plane, and uniaxial stresses.

Lightweight and flexible crystalline silicon solar cell modules were fabricated using PET film instead of cover glass. The module was attached to a thin aluminum plate and then the edges of the module were fixed to an aluminum frame. A steel ball drop test was then conducted on this module. The modules with aluminum plates 1mm and 0.5mm thick showed Hertzian fracture mode cracks in the silicon solar cells. In addition to those cracks, modules with an aluminum plate thickness of 0.3 mm showed cracking from the aluminum frame fixing points. This is due to the large deformation of the module caused by the ball drop. These cracks were much longer than Hertzian fracture mode cracks, resulting in a decrease in the output of the solar cells.

Rapid Thermal Process (RTP) treatment of Czochralski-grown Si wafers results in the formation of bulk Vacancy-Oxygen complexes (VO_X). VO₄ has been identified using Fourier Transform Infrared Spectroscopy (FTIR) in Si wafers following RTP. Previously, we investigated a stable structure of VO₄ using DFT calculations. However, since the VO₄ models were created manually, there are probably stable structures that have not yet been identified. In this study, DFT calculations and Genetic Algorithms (GA) were used to investigate stable structures in VO₄. As a result, we found nine metastable VO₄s those are more energetically stable than the metastable VO₄ proposed previously, including three models with unterminated dangling bonds. It is known that the unterminated dangling bonds on the surface of BMDs act as metal gettering effects, and therefore metastable VO₄ with unterminated dangling bonds may exhibit gettering effects on metals.