Artificial intelligence based prediction and multi-objective RSM optimization of tectona grandis biodiesel with Elaeocarpus Ganitrus.

Meta-heuristic optimization algorithms are widely applied across various fields due to their intelligent behavior and fast convergence, but their use in optimizing engine behavior remains limited. This study addresses this gap by integrating the Design of Experiments-based Response Surface Methodology (RSM) with meta-heuristic optimization techniques to enhance engine performance and emissions characteristics using Tectona Grandi's biodiesel with Elaeocarpus Ganitrus as an additive. Advanced Machine Learning (ML) models, including Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), and Random Trees (RT), were employed for predictive analysis, with ANN outperforming RSM in accuracy.

A review on sustainable management strategies for navigating the piling e-waste crisis and associated environmental threats.

In today's fast-paced technological era, multifaceted technological advancements in our contemporary lifestyle are surging the use of electronic devices, which are significantly piling e-waste and posing environmental concerns. This stock of e-waste is expected to keep rising up to 50 mt year. Formal recycling of such humongous waste is a major challenge, especially in developing nations.

Exploring the Electrochemical Performance of Molybdenum Disulfide Nanoparticles Entrenched in Miscible Poly(methyl methacrylate)-Poly(lactic acid) Blends as Freestanding Electrodes for Supercapacitors.

The focus of the study in this article is analyzing the electrochemical properties of molybdenum disulfide on miscible poly(methyl methacrylate)-poly(lactic acid) blends for supercapacitors. The interaction between molybdenum disulfide and miscible poly(methyl methacrylate)-poly(lactic acid) blends, affinity toward water, surface morphology, and mechanical properties are inspected by Fourier transform infrared spectroscopy, water contact angle, scanning electron microscopy, and universal testing machine, respectively. Among the developed membranes, 0.