Organic fiber-based biocomposites have gained prominence in a variety of sectors over the last four to five years due to their exceptional mechanical and physical properties. Natural fiber-based composites are increasingly being employed in autos, ships, airplanes, and infrastructure projects. The current study will look at the effect of nanotitanium oxide (TiO2) fillers on the properties of hybridised jute-hemp-based composites. In this work, TiO2-filled biocomposites were created using the hand layup method in hybrid jute-hemp composites containing jute fiber mats, woven hemp mats, and epoxy resin. After nanotitanium oxide fillers were injected in various weight proportions, the mechanical properties of fiber-reinforced polymers were investigated. The mechanical properties of laminated composites were tested using the ASTM standard. Compared to 2 and 4 wt.% of TiO2, the 6 wt.% was provided the highest mechanical strength. Among the different types of specimen, the E-type specimen (30 wt.% of hemp, 7 wt.% of jute, 57 wt.% of epoxy, and 6 wt.% of TiO2) gives their highest contribution, i.e., for tensile 24.21%, for flexural 25.03%, and for impact 24.56%. The scanning electron microscope was utilized to analyse the microstructures of nanocomposites.

No abstract

No abstract

On-grid predictive energy management using machine learning is presented in this paper. A photovoltaic array considered in this study is one of the kinds of a renewable sources of energy, where the battery bank acts as a technology for energy storage, in order to optimise energy exchange with the utility grid using logistic regression. The model of prediction can accurately estimate photovoltaic energy output and load one step ahead using a training technique. The optimization problem is constrained by the maximum amount of CO2 produced and the maximum amount of charge stored in a battery bank. The proposed model is tested on dynamic electricity costs. Compared with existing energy systems, the proposed strategy and prediction model can handle more than half of the annual load need.

Magnesium (AZ31) is an excellent choice for a bionic implant. To enhance biocompatibility, the hardest graphene nanoparticles were reinforced with biocompatible materials. In this paper, biocompatibility composite material is produced by stir-casting nanoshell particles reinforced with various weight percentages (0, 1, 2, 3, and 4 wt. percent) of AZ31 magnesium alloy. To understand the mechanical properties of the composite material, results of which are compared to the base alloy (AZ31) are used. The study mentioned how AZ31 magnesium alloy, reinforced with reinforcing particles, may be used to create implant-related human bone materials. Magnesium alloy reinforced with reinforcing particles is described in the study.