This study aims to investigate the thermohydraulic performance of silver nanofluids with different surface modifications (citrate, lipoic acid, and silica) in turbulent convective heat transfer applications. Three silver nanofluids were prepared, each modified with citrate, lipoic acid, or silica coatings. The nanofluids were characterized for stability using zeta potential measurements and evaluated in a smooth brass tube under turbulent flow conditions. The experimental setup involved measuring the temperature, pressure, and flow rate to assess heat transfer coefficients, pressure drops, and friction factors. The results were compared with distilled water as the base fluid and validated against theoretical models. The silica-shelled nanofluid (Ag/S) exhibited a significant 35% increase in the average heat transfer coefficient compared to distilled water, while the citrate-coated (Ag/C) and lipoic acid-coated (Ag/L) nanofluids showed slight decreases of approximately 0.2% and 2%, respectively. The Ag/S nanofluid demonstrated a 9% increase in the mean Nusselt number, indicating enhanced heat transfer capabilities. However, all modified nanofluids experienced higher pressure drops and friction factors than the base fluid, with the Ag/S nanofluid showing the highest increase in viscosity (11.9%). Surface modifications significantly influence the thermohydraulic performance of silver nanofluids. The silica-shelled nanofluid shows the most substantial enhancement in heat transfer, making it a promising candidate for applications requiring efficient thermal management. However, the increased hydraulic costs associated with higher-pressure drops and friction factors must be carefully managed. Further research is needed to optimize these nanofluids for specific industrial applications, considering long-term stability and the effects of different nanoparticle concentrations and geometries.

Hybrid natural/synthetic fiber laminates were examined as a practical process to cut mass, reduce material footprint, and meet structural demands while addressing sustainability targets. Yet direct, like-for-like comparisons generated under a single process and accompanied by durability measurements were limited, leaving design choices uncertain. This study aimed to fabricate and benchmark five representative laminates—C1: flax/epoxy, C2: jute/glass/epoxy, C3: hemp/carbon/epoxy, C4: flax/glass/bio-epoxy, and C5: kenaf/basalt/polyester—under a controlled hot-press schedule with a fixed cavity and verified fiber volume fraction. Panels were characterized using ASTM D3039 tension, ASTM D790 flexure, instrumented impact, 168 h water immersion, and thermogravimetric mass retention. The results were normalized to enable direct multi-criteria comparison, and a model was calibrated to predict tensile strength. C3 delivered the highest strengths (tension ≈ 120 MPa; flexure ≈ 126 MPa), while C5 showed the greatest impact capacity (≈60 kJ/m²). End-of-test water uptake at 168 h was C1 ≈ 3.4%, C2 ≈ 2.6%, C3 ≈ 1.4%, C4 ≈ 2.1%, and C5 ≈ 2.3%. The tensile predictor was fitted to panel means, with an R² of 0.988, and maintained an R² of 0.96 under leave-one-configuration-out testing. These results indicated that carbon-containing hybrids played the most critical roles in terms of stiffness, with kenaf/basalt being most suitable for stiffness-critical components at a similar density, and flax/glass with a bio-resin maximized the sustainability score while maintaining adequate strength. Future research should focus on enhancing specific strength at high renewable content through interface treatments, and extended modeling to improve flexure and impact responses.

Electrical discharge machining of titanium alloys requires a balanced selection of machining parameters, as high discharge intensity can improve material removal while increasing electrode wear, overcut (OC), energy consumption, and surface damage. This work investigates the sustainable EDM of Ti-6Al-4V using deionized water as the dielectric medium and copper/brass electrodes. Peak current ( I p ) , pulse-on time ( T on ) , and gap voltage ( V g ) were varied using a central composite design, and the responses were evaluated as material removal rate (MRR, m m 3 mi n − 1 ), tool wear rate (TWR, mi n − 1 ), OC ( µ m), and discharge energy (J puls e − 1 ). MRR was calculated from workpiece mass loss and titanium alloy density, while TWR was calculated from electrode mass loss, electrode density, and machining time. Response surface methodology was used for factor screening, and artificial neural network modeling was used to predict nonlinear machining responses. Particle swarm optimization was then applied, using the trained ANN as the fitness evaluator, with TLBO as the benchmark optimizer. The optimized copper-electrode condition was I p = 7 A, T on = 70 µ s, and V g = 45 V, producing MRR of 6.1 m m 3 mi n − 1 , TWR of 0.003 m m 3 mi n − 1 , and surface roughness of 1.4 µ m. SEM and wear-track analysis confirmed the need to include surface integrity and tribological response during EDM parameter selection. Future innovation will extend the quantitative range of recast-layer thickness and surface chemistry, and evaluate real-time discharge monitoring for scalable industrial EDM control.