This project explores the potential of bio-inspired honeycomb structures for aerospace applications, focusing on the structural advantages of a trabeculae honeycomb design inspired by beetles. Initially, the research involved analyzing conventional honeycomb structures and their applications, followed by a detailed study of various bio-inspired designs. Through extensive literature review, the trabeculae honeycomb structure was identified as a promising candidate due to its superior mechanical properties. The trabeculae honeycomb structure was modelled using CAD software and 3D-printed using PLA material. The structure is made up of a number of polygonal cells strengthened with trabeculae-like struts positioned at the vertices, similar to the natural architecture of Elytron Beetle Trabeculae. This one-of-a-kind arrangement increases compressive and bending strength, reduces buckling, and provides multi-directional stress distribution while keeping a lightweight profile. Finite Element Analysis and experimental tests, including compression, buckling, and bending, were conducted to evaluate the performance of the trabeculae design. The experimental validation was performed using a digital Universal Testing Machine to ensure precise measurement of mechanical behavior. The results demonstrated that the trabeculae honeycomb structure exhibits enhanced stiffness, reduced deformation, and improved energy absorption compared to conventional designs, making it highly suitable for weight-critical aerospace applications. This study highlights the potential of bio-inspired designs in advancing structural performance and material efficiency in the aerospace sector.

Enhancement of heat transfer rate through fins is one of the prevalent options, and the highly adaptable design of fins enables their application in many systems, such as radiators and electronic cooling devices. Pyramidal spine fins (PSF) are designed to enhance heat transfer and provide better performance compared to other fin designs. Due to their effectiveness, these fins are implemented in heat sinks. Motivated by this practical application, the current study examines the thermal behavior of a wetted PSF, taking into account the effects of both convection and radiation mechanisms. The highly nonlinear energy equation of PSF is converted into dimensionless form using appropriate dimensionless terms. To get the solution for the resultant equation, the Schröder polynomial collocation method (SPCM) is applied. The impact of important parameters on the thermal profile, heat transfer rate, and efficiency of PSF is illustrated graphically to address the thermal performance. The study reveals that increasing the value of the radiation-conduction parameter from 0 to 0.2 and the conduction-convection parameter from 0 to 0.5 enhances the heat transfer rate by approximately 1.35% and 28.08%, respectively. Additionally, a larger rate of heat transmission of about 2.23% is seen in the wetted PSF compared to the dry PSF.

The thermal efficiency of tetra-hybrid nanofluids exposed to a horizontal magnetic field over a stretched revolving disk has significant potential for enhanced cooling and energy-related applications. Such fluids, formed by dispersing multiple nanoparticles within a base fluid, offer enhanced heat transfer suitable for turbine blade cooling, compact electromagnetic heat exchangers, and biomedical thermal control systems. In this study, the three-dimensional flow of a tetra-hybrid nanofluid over a rotating stretchable disk is analyzed by accounting for the combined influence of a horizontal magnetic field, porous medium, thermal radiation, and internal heat sink/source under convective boundary conditions. The governing equations are transformed into ordinary differential equations (ODEs) and solved numerically using the Runge–Kutta–Fehlberg–Fourth–Fifth (RKF-45) method. To maximize the heat transfer rate, the Taguchi-based statistical method, combined with signal-to-noise ratio analysis and analysis of variance (ANOVA), is employed. The results reveal that increasing magnetic field strength and porosity significantly suppress both tangential and radial velocities due to enhanced resistive forces. Quantitatively, the optimization predicts a maximum Nusselt number of 10.4844123215026. The ANOVA results show that the rotational parameter dominates heat transfer enhancement with a contribution of 86.86%, while the Biot number has a minimal influence of only 0.30%. These findings provide useful design guidance for controlling thermal performance in magnetically regulated cooling systems and high-efficiency thermal management devices.

Natural fillers and fibers exhibit high variability in their mechanical properties, while traditional deterministic FEM is unable to capture this inherent uncertainty in composite materials. The uniqueness of the presented work lies in its integration of a stochastic thermally induced free vibration of an elastically supported multiphase composite plate (ESMPCP) reinforced with date seed powder and short glass fiber on elastic foundations. The stochastic natural frequencies characterized by mean and coefficient of variation (COV) have been computed numerically for the first time using a MATLAB code based on a finite element model, first-order perturbation technique (FOPT), and first-order shear deformation theory (FSDT). The effective elastic properties of ESMPCP were predicted using the Mori–Tanaka and Halpin–Tsai models. Various random parameters are investigated for their impact on the vibrational characteristics. Findings show that increasing the shear parameter ([Formula: see text]) leads to a 67.8% rise in the mean frequency of ESMPCP, reflecting the better resistance against vibration of the shear parameter relative to the Winkler parameter ([Formula: see text]) alone. Also, increasing the date seed filler content (10–40%) raises the mean frequency by about 40% and decreases the COV, making it suitable for vibration-sensitive applications.

Gelatin is a versatile natural biopolymer widely applied in food, pharmaceutical, and biomedical fields. Yet, its brittleness and moisture sensitivity restrict broader use in sustainable materials. While glycerol has long been the standard plasticizer, the search for eco-friendly alternatives remains pressing. In this study, gelatin interactions with natural plasticizers were examined using Density Functional Theory (B3LYP/6-31G**) and Molecular Dynamics (GROMACS, OPLS-AA, 100[Formula: see text]ns trajectories in explicit water). Plasticizers included polyols (sorbitol, mannitol, erythritol), organic acids (citric, succinic), amino acids (glycine, arginine), and amides (urea, thiourea). Hydrogen-bonding patterns, binding free energies, and electronic properties were systematically evaluated. All plasticizers formed stable H-bond networks with gelatin. Sorbitol and arginine generated the highest number of bonds (10–12 per cluster), while citric acid provided strong cross-linking. Normalized interaction energies reached [Formula: see text][Formula: see text]kcal/mol, confirming thermodynamic stabilization. Thiourea showed unique sulfur-mediated coordination, suggesting enhanced flexibility. MD simulations confirmed complex stability (RMSD[Formula: see text][Formula: see text][Formula: see text]0.25[Formula: see text]nm, stable radii of gyration), with [Formula: see text] ranging from [Formula: see text][Formula: see text]kcal/mol (urea) to [Formula: see text][Formula: see text]kcal/mol (glycerol). Agreement with literature data supports the predictive power of the approach. For the first time, combined DFT and MD modeling were applied to gelatin–plasticizer systems, offering molecular insights to guide the design of biodegradable, tunable gelatin-based films for food, packaging, and biomedical applications.

We systematically investigated the electronic, optical, and strain-dependent properties of the WSi 2 N 4 /g-GaN van der Waals heterostructure (vdWH) using first-principles calculations. The heterostructure exhibits an indirect band gap of 1.89 eV with type-I band alignment, indicating its potential for high-performance optoelectronic applications. A net charge transfer of 0.103 |e| from WSi 2 N 4 to g-GaN induces charge redistribution, generating a strong built-in electric field that significantly enhances charge carrier transport. Furthermore, tensile strain can induce a transition from indirect to direct band behavior. Meanwhile, the inherent type-I alignment reversibly transformed to type-II under a small compressive strain of -1% or near-zero tensile strain. Notably, the sharp shift indicates high strain sensitivity, enabling precise control over the transition of band alignment type. The heterostructure demonstrates enhanced absorption in both visible and ultraviolet regions compared to its constituent monolayers. Under tensile strain, the optical absorption coefficient exhibits a systematic enhancement, accompanied by a significant redshift in the absorption peak position and a substantial broadening of the absorption spectrum. Conversely, compressive strain leads to band gap widening and a consequent reduction in optical absorption efficiency. These results collectively highlight the exceptional strain-tunable properties of the WSi 2 N 4 /g-GaN vdWH, making it particularly promising for applications in optoelectronic devices and photocatalytic systems.

This research uses machine learning (ML) techniques — ANN, MLR, RF, and SVR — to predict GAP’s pull-out capacity based on key parameters such as pile diameter, relative density, liquid limit, plastic limit, plasticity index, specific gravity, and [Formula: see text] ratio. A dataset from previous experimental studies is used to train and test these models, with their performance assessed using statistical metrics like [Formula: see text], NSE, PBIAS, MSE, and RMSE. [Formula: see text]-fold cross-validation was employed to evaluate the efficacy of the models. Visual comparison tools, such as regression plots, residual distribution, Taylor diagram and violin plots, were adopted for comprehensive model evaluation. Feature importance and the sensitivity of each input parameter on pull-out capacity were identified with RF and ANN, while SHAP plots help interpret the ANN predictions. The workflow uses python environment to implement training and validating the model. Artificial Neural Network (ANN) model with a ReLU activation function was identified as the best-performing method among all tested algorithms. Additionally, ML models are compared with two empirical equations for predicting pull-out capacity. Empirical equations can accurately predict the smaller pull-out value, but for larger values, these equations have not been able to converge. The SVR model performed worse than the empirical equations. However, ML models — except for SVR — exhibited high [Formula: see text] values, indicating greater accuracy. Feature Importance and SHAP analysis results show pile diameter as the most influential factor, followed by [Formula: see text] and soil consistency indices. Pile with optimum diameter with [Formula: see text] ratio[Formula: see text]8–10 and high density granular material ([Formula: see text]%) with moderate plastic clay yields the most favorable pull-out resistance, providing a guide for design and optimization of GAP in field conditions.

This paper presents a Differential Evolution (DE)-optimized Ni–graphene–AlN metasurface solar absorber designed for efficient light trapping across the 300–850[Formula: see text]THz (visible–NIR) range. The multilayer architecture, consisting of nickel rod resonators, an aluminum nitride dielectric spacer, and a graphene interlayer, was optimized using a DE algorithm that simultaneously tuned the thicknesses of all layers to maximize broadband absorption. The optimized design achieves an average absorption of 98.17%, representing a 10.17% improvement over the initial configuration. Electric field analysis reveals hybrid plasmonic coupling between localized surface plasmons in the Ni rod resonators and surface plasmon polaritons in graphene, leading to strong field confinement and impedance matching. The absorber exhibits polarization-insensitive and angularly robust performance up to [Formula: see text] and achieves approximately 45% lower computational cost than exhaustive parametric sweeps, demonstrating both high efficiency and optimization scalability.

Multidirectional structural analysis plays a critical role in meeting performance requirements such as temperature distribution, vibration control, and stress management in multiple directions, particularly for advanced engineering applications. This work investigates the bending and vibration responses of a porous multidirectional circular functionally graded (PMCF) plate using the Isogeometric analysis (IGA) framework. The spatial variation of the material properties within the plate is modeled using a modified power-law distribution, enabling accurate representation of the gradation in both radial and thickness directions. The equations that govern the system are formulated based on the Mindlin–Reissner plate theory using energy principles. To satisfy the continuity requirements inherent to the FSDT model, improved inter-element continuity properties of Non-Uniform Rational B-Spline (NURBS) basis functions are leveraged within the IGA framework. The proposed numerical formulation is validated through comprehensive convergence and verification studies, confirming its effectiveness and accuracy. The Structural behavior in static and vibratory conditions of the PMCF plate is thoroughly investigated for a range of boundary conditions, porosity levels, material gradation profiles, and thermal loading cases. This work advances the analysis of functionally graded structures with complex, multidirectional property variations, providing a robust numerical tool for engineering design.

Radiative cooling for buildings, which leverages long-wave infrared (LWIR) toward the sky, offers innovative solutions for passive thermal regulation. However, traditional passive radiative cooling systems, characterized by static thermal emissivity ([Formula: see text], fail to automatically regulate LWIR thermal radiation across varying hot/cold seasons, exacerbating extra cooling/heating costs. In this study, we developed a photonic structure incorporating thermochromic vanadium dioxide and germanium. This structure can intelligently regulate [Formula: see text] based on ambient temperature, turning “on” and “off” radiative cooling in the atmospheric transparency window due to the metal-insulator transition of VO 2 . We crafted a meta-surface consisting of an alternating three-layered dielectric/metal of VO 2 /Ge composition using the principles of slow-light waveguide and Fabry–Perot resonators. This design achieves near-unity absorption of unpolarized light, offering a more efficient cooling effect with a simplified structure. The [Formula: see text] is adjusted at the critical phase transition temperature within the 8–13[Formula: see text][Formula: see text]m wavelength range. Notably, [Formula: see text] can reach up to 0.998 above the critical phase transition temperature and drop to as low as 0.1 below it. Besides, the net cooling power of a metallic VO 2 -based structure can attain 127.52[Formula: see text]W/m 2 , which is 3–4 times greater than that of an insulating VO 2 -based system. This work provides a promising prospect for temperature-adaptive radiative cooling via regulating [Formula: see text] with a photonic structure for all-season applications.