Medi-Caps University

This experimental study focuses on exploring the mechanical characteristics and characterization of fractured surface of polyethylene terephthalate with 15% carbon fiber (PETCF-15) composite in fused deposition modeling (FDM) process. Extrusion temperature, printing speed, layer thickness and raster angle are considered in this study. Taguchi's design of experiments (L9) is used to perform experiments considering four process parameters: extrusion temperature (275-285 degrees C,), layer thickness (0.1-0.3 mm), print speed (50-150 mm/s), and raster angle (0 degrees-90 degrees). The tensile testing performed in this work is in accordance with the standard tests prepared in the shape of dog-bone style. The printed PETCF-15 specimens exhibited the maximum tensile strength 62 N/mm2, a yield strength of 15.81 N/mm2 and maximum strain value of 10.9 %, as determined from the experimental results. The weighted grey Taguchi method is used to determine the optimum parametric setting values that would correspond to maximum tensile strength, yield strength, and elongation at break. The tests revealed that the best combinations are extrusion temperature of 275 degrees C, print speed of 50 mm/s, layer thickness of 0.1 mm with the raster angle at 0 degrees. The extrusion temperature (37.67%) and raster angle (49.88%) are identified as the most influential parameters affecting the grey relational grade, as determined through grey relational analysis. The experimental results obtained were verified with finite element analysis using ABAQUS. Fracture surfaces after tensile tests are analyzed using a scanning electron microscopy (SEM) that allows understanding of failure modes and the microstructure of the fractured surface. The strong correlation between experimental, numerical, and microstructural results validates the robustness of the approach and confirms the potential of optimized PETCF-15 components for high-performance structural applications in the aerospace and automotive sectors.

The increasing use of renewable energy, particularly photovoltaic (PV) systems, creates issues for grid stability and reactive power management. Variable loads and fluctuating solar irradiation can lead to voltage instability, power losses, and low quality power. Traditional energy storage and control strategies often struggle under changing system conditions. To address these issues, this paper proposes a hybrid method for improving grid stability reactive power management in PV and Superconducting Magnetic Energy Storage Inverters (SMES) using a hybrid approach. The proposed hybrid approach is a combined performance of both the Giraffe Kicking Optimization Algorithm (GKOA) and Higher-Order Topological Neural Networks (HOTNN), named GKOA-HOTNN. The primary aim of the proposed approach is to distribute the necessary reactive power from the PV and SMES power inverters locally. The proposed GKOA algorithm is employed to optimize the reactive power distribution and enhance the performance of grid stability in PV and superconducting magnetic energy storage systems. HOTNN is used to estimate the charging and discharging process of superconducting magnetic storage systems and electric vehicles (EVs). The performance of the proposed technique is evaluated and compared with other existing methods on the MATLAB platform, including Random Forest Cuckoo Search Optimization (RF-CSO), Particle Swarm Optimization (PSO), and Scaled Conjugate Artificial Neural Network (SC-ANN), proposed method achieves a power loss of 1 kW and an efficiency of 98

The sixth generation (6G) of wireless communication envisions a diverse range of use cases, including high-mobility vehicular networks, non-terrestrial satellite links, and ultra-reliable low-latency communication scenarios. Conventional multicarrier waveforms, such as orthogonal frequency division multiplexing (OFDM), demonstrate constraints in highly dynamic and Doppler-rich settings, presenting difficulties in achieving 6G performance standards. In this context, orthogonal time frequency space (OTFS) modulation has emerged as a promising candidate due to its delay-Doppler domain processing and robustness to time-variant channel impairments. This paper provides a unified performance evaluation of OTFS for 6G, investigating its bit error rate (BER), energy efficiency (EE), and peak-to-average power ratio (PAPR) under realistic channel models. EE analysis reveals a strong dependency on circuit power consumption and hardware efficiency, where OTFS maintains superior EE across mobility regimes, particularly in vital vehicular-to-everything (V2X) links. Finally, PAPR evaluations highlight the trade-off between transmit efficiency and signal quality, with OTFS offering a manageable PAPR profile that can be optimized through pulse shaping and power control techniques. Evaluating BER, EE, and PAPR for OTFS under realistic 6G channel models provides a unified perspective on its practical deployment potential. These results underline OTFS as a promising modulation candidate for 6G systems, balancing reliability, energy sustainability, and hardware feasibility in high-speed vehicular networks.

Polycrystalline silicon (poly-Si) solar cells remain the foundation of terrestrial photovoltaic energy production due to their cost effectiveness, mature manufacturing processes, and proven reliability. However, their outdoor power conversion efficiency is limited by significant optical reflection losses at the air–semiconductor interface, particularly under AM1.5 solar irradiance, which reduces light absorption and charge carrier generation. Antireflection coatings (ARCs) have emerged as an effective solution to mitigate these losses by enhancing light transmission into the active layer. This review evaluates a broad range of ARC materials including conventional options like SiNx, TiO2, and MgF2, as well as emerging zinc based, polymeric, and hybrid coatings and their impact on the optical and electrical performance of poly-Si solar cells. Emphasis is placed on optimizing refractive index, layer thickness, and spectral alignment with the AM1.5 spectrum to minimize reflectance. The influence of deposition techniques such as sputtering, physical vapor deposition (PVD), chemical vapor deposition (CVD), spin coating, dip coating, and sol–gel methods on coating quality, morphology, and interface passivation is also discussed. These factors directly affect key electrical parameters including short circuit current density (JSC), open circuit voltage (VOC), fill factor (FF), and overall efficiency (PCE). While theoretical studies on light interference and carrier dynamics were not covered, modelling efforts are included to analyze reflection, transmission, and resulting solar cell characteristics. Additionally, considerations such as long-term stability, thermal durability, environmental resistance, and material compatibility are highlighted as critical for practical deployment. Overall, this review offers a comprehensive perspective on the materials science, device engineering, and performance outcomes of ARCs for poly-Si solar cells, aiming to guide future research and industrial optimization toward high efficiency outdoor photovoltaics.