A hierarchically porous structured zeolite composite was synthesized from NaX zeolite supported on carbonaceous porous material produced by thermal treatment for plum stones which is an agro-waste. This kind of inorganic-organic composite has an improved performance because bulky molecules can easily access the micropores due to the short diffusion path to the active sites which means a higher diffusion rate. The composite was prepared using a green synthesis method, including an eco-friendly polymer to attach NaX zeolite on the carbon surface by phase inversion. The synthesized composite was characterized using X-ray diffraction spectrometry, Fourier transforms infrared spectroscopy, field emission scanning electron microscopy, energy d

The cost-effective removal of heavy metal ions represents a significant challenge in environmental science. In this study, we developed a straightforward and efficient reusable adsorbent by amalgamating chitosan and vermiculite (forming the CSVT composite), and comprehensively investigated its selective adsorption mechanism. Different techniques, such as Fourier-transform infrared spectroscopy (FTIR), zeta potential analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD), and Brunauer, Emmett, Teller (BET) analysis were employed for this purpose. The prepared CSVT composite exhibited a larger surface area and higher mesoporosity increasing from 1.9 to 17.24 m2/g compared to pristine chitosan. The adsorption capabilities of the

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

The current study was applied in Al-Zafaraniya area southeast of the capital Baghdad from October 2021 to April 2022. This is to evaluate some heavy elements (Cd, Co, Cu, Fe, Pb, and Mn) in the street, storm, and suspended dust. Four sampling sites were selected, and codes A, B, C, and D were given to represent the industrial activity sites, service workshops, business activity, and residential areas.

        The results showed that the concentration rates of elements (Cd, Co, Cu, Fe, Pb, Mn) in street dust samples were (1.15, 6.6, 60.15, 26770, 44.4, 6, 489.8). In storm dust (2, 10, 49.3, 54760, 24.3, 827.2) ppm, respectively, the results of suspended dust revealed that the general rates of element concentrations were (0.7

This study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V₂O₅NPs nanoparticles from vanadium sulfate VSO₄.H₂O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V₂O₅NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V₂O₅

This study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V2O5NPs nanoparticles from vanadium sulfate VSO4.H2O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V2O5NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V2O5NPs were determined using the (EDX) pattern, Atomic force microscopy AFM. The a

In this study we using zirconium sulfate, Punica granatum plant extract, and an alkaline medium, to created ZrO₂ nanoparticles. They were then characterized using a variety of techniques, including FT-IR, UV-visible, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The Debye-Scherrer equation was used to calculate the crystal size in X-ray diffraction and found to be 27.82 nm. The particle size of ZrO₂ nanoparticles was determined using atomic force microscopy, scanning electron microscopes, and transmission electron microscopy. Utilizing ZrO₂ NPs, the metal ions M (II) = Co, Ni, and Cu were successfully a

Manganese sulfate and Punica granatum plant extract were used to create MnO₂ nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO₂ NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencie