The current work concentrated on the green synthesis of silver nanoparticles (AgNPs) through the use of aqueous Citruslimon zest extract, optimizing the different experimental factors required for the formation and stability of AgNPs. The preparation of nanoparticles was confirmed by the observation of the color change of the mixture of silver nitrate, after the addition of the plant extract, from yellow to a reddish-brown colloidal suspension and was established by detecting the surface plasmon resonance band at 535.5 nm, utilizing UV-Visible analysis. The optimum conditions were found to be 1 mM of silver nitrate concentration, a 1:9 ratio extract of the mixture, and a 4 h incubation period. Fourier transform infrared spectroscopy spectrum indicated that the phytochemicals compounds present in Citrus limon zest extract had a fundamental effect on the production of AgNPs as a bio-reducing agent. The morphology, size, and elemental composition of AgNPs were investigated by zeta potential (ZP), dynamic light scattering (DLS), SEM, EDX, X-ray diffraction (XRD), and transmission electron microscopy (TEM) analysis, which showed crystalline spherical silver nanoparticles. In addition, the antimicrobial and antioxidant properties of this bioactive silver nanoparticle were also investigated. The AgNPs showed excellent antibacterial activity against one Gram-negative pathogens bacteria, Escherichia coli, and one Gram-positive bacteria, Staphylococcus aureus, as well as antifungal activity against Candida albicans. The obtained results indicate that the antioxidant activity of this nanoparticle is significant. This bioactive silver nanoparticle can be used in biomedical and pharmacological fields.

This paper introduces a numerical methodology for classifying and identifying types of bio-based materials through experimental thermal characterization. In contrast to prevailing approaches that primarily focus on thermal conductivity, our characterization methodology encompasses several thermal parameters. In this paper, the physical characteristics of seven types of bio-based concrete were analyzed, focusing on the thermal properties of palm- and esparto-fiber-reinforced concrete. The proposed method uses artificial intelligence techniques, specifically the k-means clustering approach, to segregate data into homogeneous groups with shared thermal characteristics. This enables the elucidation of insights and recommendations regarding the utilization of bio-based insulation in building applications. The results show that the k-means algorithm is able to efficiently classify the reference concrete (RC) with a performance of up to 71%. Additionally, the technique is more accurate when retaining only six centroids, which, among other things, allows all the characteristics associated with each type of concrete to be grouped and identified. Indeed, whether for k clusters k = 7 or k = 5, the technique was not able to predict the typical characteristics of 2% or 3% esparto concrete (EC).

Due to its efficiency, eco-friendliness, non-toxicity, and cost-effectiveness, the utilisation of plant extracts in the manufacture of silver nanoparticles has garnered attention. The purpose of this study is to determine the feasibility of generating silver nanoparticles from an aqueous extract of Citrus limon leaves and their size and composition was characterized utilizing UV visible, FTIR, SEM, EDX, and Zeta seizer. Additionally, the antioxidant efficacy of Ag NPs was tested using the DPPH radical scavenging method, and their antibacterial activity was verified in vitro using the Agar well diffusion technique. Silver nanoparticles were successfully synthesized and exhibit surface plasmon resonance with an absorption maximum of 475.2 nm and the stabilization of the ions Ag to nanometric spherical negative charge particles, as verified by FTIR, MEB, EDX, and Zeta potential values. Furthermore, the silver nanoparticles created displayed a substantial bactericidal effect against the three types of bacteria (Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus) and an antifungal activity against (Candida albicans) as well as reasonable antioxidant properties.

The use of natural, eco-friendly coagulant-flocculants in wastewater treatment can help to reduce suspended particles in a way that includes less exhaustible materials with minimal adverse effects on the environment. Hence, this study is to investigate raw diatomaceous earth (diatomite) as a sustainable ecological coagulant to reduce colloids and suspended matter in wastewater and optimize the coagulation process parameters to improve efficiency, save energy consumption, and reduce costs in the urban sewage treatment plants. The Box-Behnken response surface design was applied to model the individual and combined interactions between four variable factors (initial pH, coagulant dose, coagulation speed, and coagulation time) and their effect on turbidity removal efficiency and final pH of water. Results showed that diatomite has excellent efficiency in reducing the turbidity of wastewater; Elimination reached a maximum of 85.74%. The optimal operating conditions for reducing energy consumption and cost of the operation while improving turbidity removal effectiveness and achieving a neutral final pH to avoid a post-adjustment are an initial pH of 7, a dose of diatomite of 0.5 g/L of effluent, and a coagulation speed of 100 rpm for 3 min. It results in 72.6% turbidity removal and a pH of 7.27. diatomaceous earth shows very usefully for reducing the turbidity of the sewage in the urban wastewater treatment plant.