Water pollution has created a critical threat to the environment. A lot of research has been done recently to use surface-enhanced Raman spectroscopy (SERS) to detect multiple pollutants in water. This study aims to use Ag colloid nanoflowers as liquid SERS enhancer. Tri sodium phosphate (Na3PO4) was investigated as a pollutant using liquid SERS based on colloidal Ag nanoflowers. The chemical method was used to synthesize nanoflowers from silver ions. Atomic Force Microscope (AFM), Scanning Electron Microscope (SEM), and X-ray diffractometer (XRD) were employed to characterize the silver nanoflowers. This nanoflowers SERS action in detecting Na3PO4 was reported and analyzed concerning both shape and size using a 532 nm laser. We observed that the nanoflower's structure produced strong SERS signals. The increase in the SERS signal is related to the deposition of Na3PO4 molecules in the aggregated silver nanostructure in the solution. The concentration of Na3PO4 plays a main role in detection since the Raman signal becomes stronger as the concentration increases. The highest phosphate analytical enhancement factor obtained for SERS in colloidal nanoflowers was 1.7×103 at 0.7×10-6 M which was the lowest concentration.
The adsorption of Pb(II) ions onto bentonite and activated carbon was investigated. The effects of pH, initial adsorbent dosage, contact time and temperature were studied in batch experiments. The maximum adsorption capacities for bentonite and activated carbon were 0.0364 and 0.015 mg/mg, respectively. Thermodynamic parameters such as Gibbs free energy change, Enthalpy change and Entropy change have been calculated. These thermodynamic parameters indicated that the adsorption process was thermodynamically spontaneous under natural conditions and the adsorption was endothermic in nature. Experimental data were also tested in terms of adsorption kinetics, the results showed that the adsorption processes followed well pseudo second- order
... Show MoreThe development of a reversed phase high performance liquid chromatography fluorescence method for the determination of the mycotoxins fumonisin B1 and fumonisin B2 by using silica-based monolithic column is described. The samples were first extracted using acetonitrile:water (50:50, v/v) and purified by using a C18 solid phase extraction-based clean-up column. Then, pre-column derivatization for the analyte using ortho-phthaldialdehyde in the presence of 2-mercaptoethanol was carried out. The developed method involved optimization of mobile phase composition using methanol and phosphate buffer, injection volume, temperature and flow rate. The liquid chromatographic separation was performed using a reversed phase Chromolith® RP-18e column
... Show MoreAbstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped
... Show MoreWireless Sensor Networks (WSNs) are promoting the spread of the Internet for devices in all areas of
life, which makes it is a promising technology in the future. In the coming days, as attack technologies become
more improved, security will have an important role in WSN. Currently, quantum computers pose a significant
risk to current encryption technologies that work in tandem with intrusion detection systems because it is
difficult to implement quantum properties on sensors due to the resource limitations. In this paper, quantum
computing is used to develop a future-proof, robust, lightweight and resource-conscious approach to sensor
networks. Great emphasis is placed on the concepts of using the BB8
In this work, silver (Ag) self-metallization on a polyimide (PI) film was prepared through autocatalytic plating. PI films were prepared through the solution casting method, followed by etching with potassium hydroxide (KOH) solution, sensitization with tin chloride (SnCl2), and the use of palladium chloride (PdCl2) to activate the surface of PI. Energy-dispersive X-ray analysis (EDX) showed the highest peak in the (Ag) region and confirmed the presence of AgNPs. The diffraction peaks at 2θ = 38.2°, 44.5°, 64.6°, and 78.2° represented the 111, 200, 220, and 311 planes of Ag, respectively. The FT–IR an
... Show MoreSimulation of the Linguistic Fuzzy Trust Model (LFTM) over oscillating Wireless Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network
... Show MoreThe recent studies suggested the possible toxicities or genetic alterations associated with biological and medical applications of silver nanoparticles (AgNPs). The current research is directed to see if AgNPs administration can lead to some changes in expression of BRAF gene in selected body organs tissues. Fifty-six male of musmusculs (Balb/C) mice from the animal house of Al-Nahrain Centre of Biotechnology were used. These animals were divided randomly to seven groups (eight mouse in each group), one of these groups represented the control group, three groups were subjected to different doses of AgNPs (0.25, 0.5and 1 mg/kg of body weight) for one week, and the remaining three groups were subjected to three different doses of AgNP
... Show MoreA high sensitivity, low power and low cost sensor has been developed for photoplethysmography (PPG) measurement. The PPG principle was applied to follow the dilatation and contraction of skin blood vessels during the cardiac cycle. A standard light emitting diodes (LEDs) has been used as a light emitter and detector, and in order to reduce the space, cost and power, the classical analogue-to-digital converters (ADCs) replaced by the pulse-based signal conversion techniques. A general purpose microcontroller has been used for the implementation of measurement protocol. The proposed approach leads to better spectral sensitivity, increased resolution, reduction in cost, dimensions and power consumption. The basic sensing configuration prese
... Show MoreIn this work, CdS/TiO2 nanotubes composite nanofilms were successfully synthesized via electrodeposition technique. TiO2 titania nanotube arrays (NTAs) are commonly used in photoelectrochemical cells as the photoelectrode due to their high surface area, excellent charge transfer between interfaces and fewer interfacial grain boundaries. The anodization technique of titanium foil was used to prepare TiO2 NTAs photoelectrode. The concentration of CdCl2 played an important role in the formation of CdS nanoparticles. Field emission scanning electron microscopy (FESEM) shows that the CdS nanoparticles were well deposited onto the outer and inner of nanotube at 40 mM of CdCl2. X-ray diffraction (XRD) and energy dispersive X-ray (EDX) analyses wer
... Show MoreThis paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
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