The New Horizon College of Engineering (NHCE) is an autonomous private engineering college located near Marathahalli, in Bangalore, India. Established in 2001, the college is part of the New Horizon Educational Institution which was established in 1970.
The novel and sustainable biomaterials at biotechnology and healthcare had necessitated breakthroughs in their engineering performance. The inherent limitations of biomaterials, in absence of synthetic supports or reinforcements, provide significant obstacle. Thus, there an increasing demand for creation of comprehensive eco-friendly materials. This work aims to improve mechanical properties of Date palm seed by heat treatment. The study utilizes genetic algorithms and Taguchi optimization method to identify ideal combination of holding time and heating temperature, with objective of maximizing hardness and tensile strength. The outcomes indicate effectiveness of proposed approach, showing an optimal TS of 7.62 MPa treatment temperature 60 °C for 100 min. The optimal hardness of 65.43 Hv were attained at heat treatment temperature of 120 °C for a duration of 100 min. Research additionally examines chemical alterations by Fourier transform spectroscopy. Regression models for hardness and tensile strength have been constructed, and global optimum were determined utilizing genetic algorithm solver. This study’s outcomes reveal substantial enhancements at mechanical properties of biomaterials, underscoring suitability for rigorous engineering uses. Refined heat treatment settings provide improved biomaterials performance and present potential opportunities for the creation of stronger and more durable materials. This research advances biomaterials Engineering, facilitating production and design of environmentally friendly materials by enhanced mechanical qualities, thereby meeting persistent demand for new solutions across multiple industries.
An insulator is one of the crucial parts of the high-voltage overhead cables. Leakage currents may circulate on the insulator’s surface as a result of external factors and contaminants adhered to the surface. Large leakage currents (LC) have the potential to produce flashover, heat losses and surface damage to the insulator. In order to prevent early flashover, this research offers a method that measures the severity of the insulator surface using harmonic measurements of leakage currents. In this work, on 11 kV polymer insulators, the leakage currents were assessed at various equivalent soluble deposit density (ESDD) levels. Discrete Wavelet transform topology is incorporated to extract features from the LC signal. Random forest (RF) with fuzzy inference system (FIS) using a diverse range of LC signals collected over an extended period is incorporated. From results, it is evident that the suggested pollution severity classifier, is highly effective with an accuracy about 95
Shell and tube heat exchangers (STHEs) are familiar for large-scale industrial applications due to their improved heat transfer area, ease of adoption of high temperatures and pressures, and flexible flow setup. However, uneven heat flow, variations in specific surface area, and limitations in heat capacity all contribute to the reduced thermal performance of a heat exchanger. The research objectives are to enrich the overall heat transfer and exergy efficiency behaviour of a shell and tube heat exchanger (STHE) with modified tube geometry. The effectiveness of circular, square, and polygon tube surface configuration on heat transfer rate, energy release rate, variations in heat capacity, and exergy behaviour of STHE is evaluated under natural convection. During the evaluation, a paraffin-based phase change material (PCM) was used as an energy storage medium, filled in a tube, and water served as the heat transfer fluid (HTF). With the significance of evaluated results, the circular tube geometry is found higher heat transfer rate (122.3 W), a higher energy release rate (0.052 kWh), and better heat capacity of PCM. Similarly, the exergy efficiency of a circular pipe is found to be 23.4 %, and 39.5 % superior to that of a square tube. Furthermore, the COMSOL Multiphysics simulation software was used to analyze the temperature distribution between the tube configuration and the PCM. Hence, the heat storage efficiency was validated using the simulation results, and the standard deviations were calculated as approximately 1.15, 0.85, and 1.2 for the circular, square, and polygon-tube configurations, respectively. Research has shown that the circular tube with PCM exhibits superior heat transfer performance and high exergy efficiency compared to other tube configurations, making it a suitable choice for heat exchanger applications.
Early identification of brain tumors requires sensors capable of detecting subtle refractive index variations associated with pathological tissue changes in a label-free and non-invasive manner. Surface Plasmon Resonance (SPR) sensors utilize the surface plasmons excited by incident light to measure changes in the dielectric properties of thin layers placed adjacent to metal surfaces thus they are highly sensitive to dielectric property changes which makes them excellent platforms for biomedical diagnostics. In this work, a THz metasurface SPR sensor is designed and validated that incorporates a graphene base with gold (Au) and MoS₂ coated resonators arranged in a compact A-shaped metasurface configuration. The hybrid material used for the resonators, along with the resonator’s geometry, were both optimized to provide enhanced confinement and tunability of the electromagnetic fields within the terahertz frequency range. Simulation results indicate that the proposed sensor provides a maximum sensitivity of 2308 GHz/RIU with a stable FWHM of 0.111 THz and a peak FOM of 20.79 RIU− 1 across the refractive index range. A machine learning algorithm was applied as a data-driven analytical tool for modeling the relationships between sensor operating parameters and sensor responses, indicating correlation coefficients (R2) of unity for the simulated data sets. These results demonstrate that the proposed metasurface sensor offers a robust and high-performance design for RI based sensing. The findings presented are based on numerical validation and the demonstrated sensing parameters indicate that the design has a strong potential for future experimental prototype and early-stage brain tumor biomarker sensing contributing to SDG 3 (Good Health and Well-Being) through improved early diagnostic capability.
A holistic understanding of battery evolution, from early conceptual descriptions in ancient Vedic texts to contemporary solid-state architectures, reveals the critical role of materials chemistry in advancing safer and more sustainable energy-storage technologies. In this context, the review systematically analyses polymer-salt-based electrolytes as pivotal enablers of next-generation solid-state systems, emphasizing their favourable mechanical compliance, tunable physicochemical properties, and potential for environmentally responsible design. Polymer electrolytes are classified into solid, gel, composite, and bio-derived systems, and their microstructural features are correlated with electrochemical functionality. Particular attention is given to the influence of coordinating salts, plasticizers, nanofillers, and cross-linking frameworks on ion dissociation, polymer-ion coordination strength, segmental relaxation dynamics, and the formation of continuous conductive pathways. Fundamental ion-transport models, including segmental-assisted motion, free-volume hopping, vehicular migration, and percolation-driven conduction, are examined to elucidate charge mobility within polymer matrices. Advanced characterization techniques such as EIS, DSC, TGA, LSV, and broadband dielectric analysis are highlighted for their capability to quantify charge transport, assess thermal-electrochemical stability, and uncover structure-property relationships. Battery performance metrics are critically evaluated with respect to electrolyte architecture and materials design. The review further addresses ecological challenges associated with conventional battery components and presents emerging sustainable strategies, including bio-polymeric electrolytes and non‑lithium solid-state chemistries, reinforcing the importance of green materials engineering in future energy-storage ecosystems.
