Search Results (486)

This paper proposes a Hybrid Recursive Trigonometric (HRT) technique for FPGA-based direct digital frequency synthesizers. The HRT technique integrates a recursive cosine generator with periodic reinitialization via a second-order Taylor polynomial to reduce cumulative errors without requiring ROMs or iterative CORDIC units. A resource-efficient combinational architecture is implemented and validated on the Lattice iCE40HX1K FPGA. The effectiveness of the proposed HRT technique is evaluated through simulation and FPGA-based experiments, with respect to spectral accuracy and resource efficiency, particularly for fixed-point cosine waveform synthesis in low-resource digital systems. Simulation results show that the system has a spurious-free dynamic range (SFDR) of −86.09 dBc and signal-to-noise ratio of 52.74 dB using 16-bit fixed-point arithmetic. Experimental measurements confirm the feasibility, achieving −58.86 dBc SFDR. Full article

This study investigates the capillary performance and wetting behavior of SLA (Stereolithography) 3D-printed porous structures, focusing on TPMS (triply periodic minimal surfaces)-Gyroid, Octet, Diamond, and Isotruss lattice designs. High-speed imaging was used to analyze droplet interactions, including penetration, spreading, and contact angles, with 16 μL water droplets dropping from 30 mm at 0.77 m/s. Results showed variable contact angles, with Isotruss and Octet having higher angles, while Diamond faced measurement challenges due to surface roughness. Numerical simulations of TPMS-Gyroid of 2 mm³ unit cells validated the experimental results, and Diamond, Octet, and Isotruss structures were simulated. Capillary performance was assessed through deionized (DI) water weight–time (w-t) measurements, identifying that the TPMS-Gyroid structure performed adequately. Structures with 4 mm³ unit cells had low capillary performance, excluding them from permeability testing, whereas smaller 2 mm³ structures demonstrated capillary effects but had printability and cleaning issues. Permeability results indicated that Octet performed best, followed by Isotruss, Diamond, and TPMS-Gyroid. Findings emphasize unit cell size, beam thickness, and droplet positioning as key factors in optimizing fluid dynamics for cooling, filtration, and fluid management. Full article

In this paper, voxel-based Asymptotic Homogenization (AH) is employed to calculate the thermal expansion and thermal conductivity characteristics of lattice materials that have a Representative Volume Element (RVE) with non-orthogonal periodic bases. The non-orthogonal RVE of the cellular lattice is discretized using voxel elements (iso-parametric hexahedral element, on a cartesian grid). A homogenization framework is developed in python that uses a fast-nearest neighbor algorithm to approximate the (non-orthogonal) periodic boundary conditions of the discretized RVE. Validation studies are performed where results of the homogenized Thermal Expansion Coefficient (TEC) and thermal conduction performed in this paper are compared with results generated by commercially available software. These included comparison with the results for (a) bi-material unidirectional composite with orthogonal RVE cell envelope; (b) bi-material hexagon lattice with orthogonal cell envelope; (c) bi-material hexagon lattice with non-orthogonal cell envelope; and (d) bi-material square lattice. A novel approach of visualizing the contribution of each voxel towards the individual terms within the homogenized thermal conductivity matrix is presented, which is necessary to mitigate any potential errors arising from the numerical model. Additionally, the effect of the thermal expansion and thermal conductivity for bi-material hexagon lattice (orthogonal and non-orthogonal RVE cell envelope) are presented for varying internal cell angles and all permutations of material assignments for a relative density of 0.3. It is found that when comparing the non-orthogonal RVE with the Orthogonal RVE as a reference model, the numerical error due to approximating the periodic boundary condition for the non-orthogonal bi-material hexagon is generally less than 2% as the numerical error is pseudo-cyclically dependent on the discretization along the cartesian axis. Full article

In this study, we introduce a novel interdisciplinary framework that applies concepts from statistical physics, specifically lattice-gas models, to the classical order lot-sizing problem in supply chain management. Traditional methods often rely on heuristic or deterministic approaches, which may fail to capture the inherently probabilistic and dynamic nature of decision-making across multiple periods. Drawing on structural parallels between inventory decisions and adsorption phenomena in physical systems, we constructed a mapping that represented order placements as particles on a lattice, governed by an energy function analogous to thermodynamic potentials. This formulation allowed us to employ analytical tools from statistical mechanics to identify optimal ordering strategies via the minimization of a free energy functional. Our approach not only sheds new light on the structural characteristics of optimal planning but also introduces the concept of configurational entropy as a measure of decision variability and robustness. Numerical simulations and analytical approximations demonstrate the efficacy of the lattice gas model in capturing key features of the problem and suggest promising avenues for extending the framework to more complex settings, including multi-item systems and time-varying demand. This work represents a significant step toward bridging physical sciences with supply chain optimization, offering a robust theoretical foundation for both future research and practical applications. Full article

The proliferation of electromagnetic wave applications has accentuated electromagnetic pollution concerns, highlighting the critical importance of electromagnetic wave absorbers (EMA). This study proposes innovative I-Wrapped Package Lattice electromagnetic wave absorbers (IWP–EMA) based on the triply periodic minimal surface (TPMS) lattice structure. Through a rational design of porous gradient structures, broadband wave absorption was achieved while maintaining lightweight characteristics and mechanical robustness. The optimized three-dimensional configuration features a 20 mm thick gradient structure with a progressive relative density transition from 10% to 30%. Under normal incidence conditions, this gradient IWP–EMA basically achieves broadband absorption with a reflection loss below −10 dB across the 2–40 GHz frequency band, with absorption peaks below −19 dB, demonstrating good impedance-matching characteristics. Additionally, due to the complex interactions of electromagnetic waves within the structure, the proposed IWP–EMA achieves a wide-angle absorption range of 70° under Transverse Electric (TE) polarization and 70° under Transverse Magnetic (TM) polarization. The synergistic integration of the TPMS design and additive manufacturing technology employed in this study significantly expands the design space and application potential of electromagnetic absorption structures. Full article

This study presents a multi-objective optimization framework for designing cylindrical triply periodic minimal surface (TPMS) lattices tailored for bone implant applications. Using an artificial neural network (ANN) as a surrogate model trained on simulated data, four key properties—ultimate stress (U), energy absorption (EA), surface area-to-volume ratio (SA/VR), and relative density (RD)—were predicted from seven lattice design parameters. To address anatomical variability, a novel implant size-based categorization (small, medium, and large) was introduced, and separate optimization runs were conducted for each group. The optimization was performed via the NSGA-II algorithm to maximize mechanical performance (U and EA) and surface efficiency (SA/VR), while filtering for biologically relevant RD values (20–40%). Separate optimization runs were conducted for small, medium, and large implant size groups. A total of 105 Pareto-optimal designs were identified, with 75 designs retained after RD filtering. SHapley Additive exPlanations (SHAP) analysis revealed the dominant influence of thickness and unit cell size on target properties. Kernel density and boxplot comparisons confirmed distinct performance trends across size groups. The framework effectively balances competing design goals and enables the selection of size-specific lattices. The proposed approach provides a reproducible pathway for optimizing bioarchitectures, with the potential to accelerate the development of lattice-based implants in personalized medicine. Full article

Interpenetrating phase composites (IPCs) have demonstrated tremendous potential across various fields, particularly those based on triply periodic minimal surface (TPMS) structures, whose uniquely interwoven lattice architectures have attracted widespread attention. However, current research on the dynamic mechanical properties of such IPC remains limited, and their impact resistance and damage mechanisms are yet to be thoroughly understood. In this study, a novel design of two volume fractions of IPCs based on the TPMS IWP configuration is developed using Python-based parametric modeling, with the Ti6Al4V alloy TPMS scaffolds fabricated via selective laser melting (SLM) and the AlSi12 reinforcing phase through infiltration casting. The influence of Ti alloy volume fraction and strain rate on the dynamic mechanical behavior of the Ti/Al IPC is systematically investigated using a split Hopkinson pressure bar (SHPB) experimental setup. Microscopic characterization validates the effectiveness and reliability of the proposed IPC fabrication method. Results show that the increasing Ti alloy volume fraction significantly affects the dynamic mechanical properties of the IPC, and IPCs with different Ti alloy volume fractions exhibit contrasting mechanical behaviors under increasing strain rates, attributed to the dominance of different constituent phases. This study enhances the understanding of the dynamic behavior of TPMS-based IPCs and offers a promising route for the development of high-performance energy-absorbing materials. Full article

Medium- and large-scale heat sinks are critical for thermal load management in high-performance systems. However, their high heat flux densities and limited space complicate cooling, leading to risks of overheating, performance degradation, or failure. This study employs the Cascaded Lattice Boltzmann Method (CLBM) to enhance their thermal performance. This numerical approach is known for being stable, accurate when dealing with complex boundaries, and efficient when computing in parallel. The numerical code was validated against a benchmark configuration and an experimental setup to ensure its reliability and accuracy. While previous studies have explored mixed convection in cavities or heat sinks, few have addressed configurations involving side air injection and boundary conditions periodicity in the transition-to-turbulent regime. This gap limits the understanding of realistic cooling strategies for compact systems. Focusing on mixed convection in the transition-to-turbulent regime, where buoyancy and forced convection interact, the study investigates the impact of Rayleigh number values ($5\times {10}^7$ to $5\times {10}^8$) and Reynolds number values (${10}^3$ to $3\times {10}^3$) on heat transfer. Simulations were conducted in a rectangular cavity with periodic boundary conditions on the vertical walls. Two heat sources are located on the bottom wall ($T_h$ = 50 °C). Two openings, one on each side of the two hot sources, force a jet of fresh air in from below. An opening at the level of the cavity ceiling’s axis of symmetry evacuates the hot air. Mixed convection drives the flow, exhibiting complex multicellular structures influenced by the control parameters. Calculating the average Nusselt number (Nu) across the surfaces of the heat sink reveals significant dependencies on the Reynolds number. The proposed correlation between Nu and Re, developed specifically for this configuration, fills the current gap and provides valuable insights for optimizing heat transfer efficiency in engineering applications. Full article

The poor magnetic and magneto-optical properties of BiFeO₃, along with its significant lattice mismatch with silicon, have limited its application in silicon-based integrated magneto-optical devices. In this study, co-doping with Sr²⁺ and Ti⁴⁺ ions effectively transformed the trigonal structure of BiFeO₃ into a cubic phase, thereby reducing the lattice mismatch with silicon to 2.8%. High-quality, highly oriented, silicon-based cubic Sr,Ti:BiFeO₃ thin films were successfully fabricated using radio frequency magnetron sputtering. Due to the induced lattice distortion, the characteristic periodic spiral spin antiferromagnetic structure of BiFeO₃ was suppressed, resulting in a significant enhancement of the saturation magnetization of cubic Bi_0.5Sr_0.5Fe_0.5Ti_0.5O₃ (48.0 emu/cm³), compared to that of pristine BiFeO₃ (5.0 emu/cm³). Furthermore, the incorporation of Sr²⁺ and Ti⁴⁺ ions eliminated the birefringence effect inherent in trigonal BiFeO₃, thereby inducing a pronounced magneto-optical effect in the cubic Sr,Ti:BiFeO₃ thin film. The magnetic circular dichroic ellipticity (ψ_F) of Bi_0.5Sr_0.5Fe_0.5Ti_0.5O₃ reached an impressive 2300 degrees/cm. Full article

This study explores the mechanical performance of triply periodic minimal surface (TPMS) and stochastic lattice structures subjected to low-velocity impact. Two structurally promising geometries—one TPMS-based and one stochastic—were tested and compared with the well-established gyroid. Specimens were fabricated using stereolithography (SLA) and subjected to impact energies of 30 J and 40 J to assess the structural response and energy absorption capabilities. Experimental results show that the proposed TPMS structure exhibits higher impact forces compared with the gyroid, which are associated with significant impactor displacement and deep indentation. These samples demonstrated extensive damage, with cracking propagating through the entire core at higher energies, highlighting their susceptibility to structural failure despite their high initial strength. On the contrary, the stochastic structures allowed localized deformation in the impacted region, thus successfully avoiding catastrophic failure. The impact force efficiency was higher for both gyroid and stochastic geometries, with values ranging between 0.6 and 0.7, indicating effective energy absorption with reduced internal stress gradients. Furthermore, the evaluation of damping performance showed that most structures displayed high damping, as minimal energy was transferred back to the impactor. This work highlights the feasibility and functional versatility of TPMS and stochastic geometries for use in impact mitigation, vibration control, and related engineering applications. Full article

A full-cycle, multiscale analysis technique was developed for periodic lattice structures with geometric repetition, aiming for more efficient modeling to predict their failure loads. The full-cycle analysis includes both upscaling and downscaling procedures. The objective of the upscaling procedure is to obtain the effective material properties of the lattice structures such that the lattice structures can be analyzed as continuum models. The continuum models are analyzed to determine the structures’ displacements or buckling failure loads. Then, the downscaling process is applied to the continuum models to determine the stresses in actual lattice members, which were applied to the stress and stress gradient based failure criterion to predict failure. Example problems were presented to demonstrate the accuracy and reliability of the proposed multiscale analysis technique. The results from the multiscale analysis were compared to those of the discrete finite element analysis without any homogenization. Furthermore, physical experiments were also conducted to determine the failure loads. Then, multiscale analysis was undertaken in conjunction with the failure criterion, based on both stress and stress gradient conditions, to compare the predicted failure loads to the experimental data. Full article

Since 2010, BiCuSeO has emerged as a captivating subject of investigation within the realm of thermoelectric materials. Its allure lies in a remarkable confluence of characteristics: a distinctive natural super-lattice structure, an elevated Seebeck coefficient, and a low thermal conductivity, all of which have collectively piqued the intense interest of scientists worldwide. Over the subsequent eight-year period, an extensive array of research endeavors has been meticulously carried out, delving deep into the multifaceted properties of BiCuSeO and exploring avenues for performance enhancement. In this comprehensive review, we embark on a detailed exploration of the fundamental properties of BiCuSeO, encompassing its preparation methodologies, as well as its thermoelectric and mechanical attributes. A thorough synthesis of diverse strategies for optimizing the composition and structure of BiCuSeO is presented, elucidating how these modifications contribute to the enhancement of its thermoelectric and mechanical performance. Finally, the current state of research on N-type BiCuSeO is systematically summarized, offering a panoramic view of the advancements and challenges in this particular area. Full article

Fibrous biomaterials are essential in biomedical engineering, tissue engineering, and filtration due to their specific transport and mechanical properties. Fluid flow through these materials is critical for their function. However, many biological fluids exhibit non-Newtonian behavior, characterized by micro-rotational effects, which traditional models often overlook. The current study presents a machine learning (ML) framework for the prediction and understanding of hydraulic permeability in fibrous biomaterials with a micropolar fluid. A dataset of 1000 numerical simulations was generated by varying the micropolar fluid properties and the fiber volume fraction in a periodic porous structure with nine parallel cylindrical fibers in a square lattice. Six powerful ML algorithms were deployed: Decision Trees (DT), Random Forests (RF), XGBoost, LightGBM, Support Vector Regression (SVR), and k-Nearest Neighbors (kNN). The balance of predictive capacity to unseen data values (tracking $R^2$ values and error metrics) with computational efficiency for all algorithms was assessed. The best-performing ML algorithm was subsequently used to interpret the decisions made by the model using Shapley Additive exPlanations (SHAP) analysis and understand the role of feature importances. The SHAP findings highlight the potential of ML in capturing complex fluid interactions and guiding the design of advanced fibrous biomaterials with optimized hydraulic permeability. Full article

Critical-sized bone defects or CSDs result from bone loss due to trauma, tumor removal, congenital defects, or degenerative diseases. Though autologous bone transplantation is the current gold standard in treating CSDs, its limitations include donor-site morbidity, unavailability of donor bone tissues, risk of infection, and mismatch between the bone geometry and the defect site. Customized scaffolds fabricated using 3D printing and biocompatible materials can provide mechanical integrity and facilitate osseointegration. Ti-6Al-4V (Ti64) is one of the most widely used commercial alloys in orthopedics. To avoid elastic modulus mismatch between bones and Ti64, it is imperative to use porous lattice structures. Ti64 scaffolds with diamond, cubic, and triply periodic minimal surface (TPMS) gyroid lattice architectures were fabricated using selective laser melting (SLM)with pore sizes ranging from 300 to 900 μm using selective laser melting and evaluated for mechanical and biological performance. Increasing pore size led to higher porosity (up to 90.54%) and reduced mechanical properties. Young’s modulus ranged from 13.18 GPa to 1.01 GPa, while yield stress decreased from 478.16 MPa to 14.86 MPa. Diamond and cubic scaffolds with 300–600 μm pores exhibited stiffness within the cortical bone range, while the 900 μm diamond scaffold approached trabecular stiffness. Gyroid scaffolds (600–900 μm) also showed modulus and yield strength within the cortical bone range but were not suitable for trabecular applications due to their higher stiffness. Cytocompatibility was confirmed through leachate analysis and DAPI-stained osteoblast nuclei. The biological evaluation reported maximum cell adherence in lower pore sizes, with gyroid scaffolds showing a statistically significant (p < 0.01) increase in cell proliferation. These findings suggest that 300–600 μm lattice scaffolds offer an optimal balance between mechanical integrity and biological response for load-bearing bone repair. Full article

The design of scaffolds and prostheses benefits from the opportunities provided by additive manufacturing technologies. Specifically, scaffold design using cellular structures based on lattices has become a significant focus. These lattice-based scaffolds exhibit intricate and complex shapes with controlled macro-porosity. In this study, a method is presented that enables the modeling of a graded-density lattice structure for material extrusion additive manufacturing, without relying on a geometric lattice model. The methodology utilizes computed tomography (CT) scans as inputs to obtaining a 3D scalar field and a surface model. The lattice structure is designed and generated within the computer-aided manufacturing (CAM) software, ensuring consistent machine toolpaths. The 3D scalar field, representing a relative density map derived from CT Hounsfield units, drives the variation of the extrusion parameters generated by the CAM, achieving a graded-density lattice. To demonstrate the effectiveness of the method, a section of a human femur bone with a lattice with a triply periodic minimal surface (TPMS) gyroid pattern was designed and 3D-printed, replicating the relative density of the target tissue. Full article