ABSTRACT The objective of this research is to enhance the mechanical and thermal characteristics of jute fiber reinforced polymer (JFRP) composites for environmentally friendly structural uses by integrating statistical optimization methods with experimental assessment. JFRP laminates were fabricated using the hand lay-up technique by varying key design parameters such as fibre volume fraction, curing conditions, and fibre surface treatment. In accordance with ASTM recommendations, tensile, flexural, and impact tests were employed for mechanical characterization, while thermogravimetric analysis (TGA) was utilized to evaluate thermal stability. The best set of process parameters for optimizing strength and thermal stability while decreasing density and water absorption was found using a multi-objective optimization technique based on Response Surface Methodology (RSM) combined with Analysis of Variance (ANOVA). The results indicate that fibre surface treatment significantly improves interfacial bonding, leading to enhanced tensile and flexural properties. Thermal analysis reveals improved degradation temperature and stability with increasing fibre content up to an optimal level. The optimization model predicts an optimal fibre volume fraction in the range of 35–40%, achieving a balanced improvement in mechanical performance and thermal resistance with minimal weight increase. Experimental validation confirms the reliability of the developed model, with prediction errors below 5%. These findings demonstrate the potential of JFRP composites as sustainable alternatives for structural applications.
ABSTRACT Wearable platforms that offer high electromagnetic sensitivity, mechanical flexibility and intelligent interpretation and analysis of physiological signals are needed for continuous and non-invasive cardiovascular monitoring. This research introduces a new graphene-based terahertz (THz) metamaterial wearable nanosensor with an architecture of Complementary Split-Ring Resonator (CSRR), electromagnetic-mechanical multiphysics modeling, and artificial intelligence to continuously monitor cardiovascular health. The proposed sensor is a monolayer graphene CSRR patterned on a 50 μm polydimethylsiloxane (PDMS) substrate, which allow for conformal epidermal sensing with excellent electromechanical stability. The finite element multiphysics simulations show a sharp resonance frequency at 1.20 THz with a high quality factor of 48.2 and the simulations indicate a highly linear shift of resonance frequency with tensile strain applied to the entire range from 0 to 12%, with a strain sensitivity of 15.1 GHz/% and a strain transfer efficiency of 98.4%. The sensor’s ability to detect simulated hemodynamic blood-volume changes is also confirmed by a multilayer skin–tissue phantom, using a sensitivity of 3.57 GHz/Δε. A machine learning framework was trained using 2500 simulated terahertz reflection spectra that successfully predicted cardiovascular parameters with R2 = 0.994, MAE = 0.14%, RMSE = 0.19% and MAPE = 1.12% in the case of arterial s train estimation, enabling automated physiological assessment. The key novelty of this work is the consistent implementation of graphene based THz metamaterials, multiphysics finite element analysis (FEA) of the model, simulation of realistic tissues and phantoms, and AI based spectral interpretation in a single computational system for continuous cardiovascular monitoring. The computational results presented here provide a strong design basis for an experimental realization of intelligent, flexible and non-invasive wearable biosensors for personalized cardiovascular diagnostics in the future.
ABSTRACT Fires necessitate urgent prevention and suppression efforts. The volumetric fire extinguishing methods, such as aerosol forming extinguishing compositions (AFCs), offering a promising alternative to environmentally harmful halons. This study investigates the practical impact of the combustion products of KNO3-based AFCs, with phenol-formaldehyde resin, and copper oxide (CuO) additive, on the environment and human health in enclosed spaces. Experimental investigations included measuring burning rates, gaseous combustion products (Total Volatile Organic Compounds – TVOC, PM2.5, PM10, CO, CO2), and solid-phase product parameters (pH, electrical conductivity). Results demonstrate that adding CuO significantly increases the burning rate. TVOC levels initially exceed indoor air quality safety limits, with higher CuO concentrations leading to slower decreases in these levels. PM2.5 and PM10 concentrations reach “hazardous” levels rapidly and persist, indicating effective aerosol spread for fire suppression but posing serious health risks such as respiratory issues. Carbon monoxide (CO) concentrations are initially high, exceeding safety standards. The solid combustion residues produced alkaline aqueous solutions with relatively high electrical conductivity, indicating the presence of a highly conductive electrolyte that may create conditions favorable for electrochemical corrosion.
ABSTRACT This study investigates the application of β-zeolite-supported bimetallic catalysts in the methanol production from methane reaction. β-zeolite with a Si/Al ratio of 25 was synthesized via the hydrothermal method, and Cu-β, Fe-β, and Cu-Fe-β catalysts were prepared using the wet impregnation technique. Structural characterization of the catalysts was performed using SEM, EDS, XRD, FTIR, BET, NH3-TPD and XPS to characterize the catalysts. The results indicated that the metal components were successfully and uniformly loaded onto the β-zeolite surface. The synergistic effect of the Cu-Fe bimetallic loading reduced pore blockage, introduced new effective acidic sites, and optimized the pore structure to enhance mass transfer efficiency. It effectively regulates the electronic structure and valence state distribution of the metal active sites, optimizing the distribution and electronic structure of these active sites on the catalyst surface. The catalytic performance of the three catalysts was evaluated in a miniature fixed-bed reactor under varying temperatures and reaction times. Activity tests revealed that copper-active metals exhibited superior activity compared to iron-active metals during methanol production via methane partial oxidation within shorter reaction times. Performance of all catalysts improved with increasing temperature. Among the three metal-zeolite catalysts, Cu-Fe-β yielded the highest methanol yield, reaching 17.78 μmol/gcat/h at 340 °C. This study demonstrates the promising application potential of β-zeolite-supported Cu-Fe bimetallic catalysts in methane-to-methanol conversion, providing theoretical guidance for the design and development of highly efficient catalysts.
ABSTRACT The escalating demand for lightweight, high performance materials for the automotive sector has accelerated the development of hybrid composites. This study explores the mechanical and thermal behavior of epoxy based composites reinforced with a combination of flax and aramid fibers. Five hybrid configurations were developed by varying the fiber ratios and the experimental investigation includes tensile, flexural, compression, impact, water absorption, thermal stability, and hardness tests to assess the performance of the composites. Among all formulations, Combination 4 (67% epoxy, 9% flax, and 24% aramid) delivered the most balanced performance, exhibiting a tensile strength of 42.494 MPa and a flexural strength of 171.493 MPa. These values are substantially higher than representative properties reported for commonly used engineering thermoplastics such as Acrylonitrile Butadiene Styrene (ABS) in published literature. Microstructural evaluation via Scanning Electron Microscopy (SEM), thermal analysis through Thermogravimetric Analysis (TGA), and Shore D hardness tests confirmed the superior integrity and heat resistance of this configuration. The findings reveal combination No.4 as a strong, thermally stable, and weight efficient replacement for conventional polymer materials used in automotive structural components.
