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Here we report that photocatalytic and antioxidant properties of nanocomposite consist of silver- and copper-doped zinc oxide nanoparticles loaded onto carbon nanotubes (ZnO/Cu/Ag/CNT). The prepared nanocomposite material was analyzed using X-ray diffraction, scanning electron microscopy, tunneling electron microscopy, photoluminescence spectroscopy, and ultraviolet–visible spectroscopy for their structural, morphology, and optical studies. A photodegradation study was carried out against methylene blue, rose bengal, and eosin yellow dyes. The consequences of photocatalyst mass loading, pH, and dye concentration were explored. The optimum has result shown 99% degradation efficiency against methylene blue within 10 min of visible light irradiation at pH 10. A reusability test displayed the photocatalytic efficacy of the nanocomposite material was up to 83% after 4 rounds of use against methylene blue. The antioxidant performance of the nanocomposite material was studied against 2,2-diphenylpicrylhydrazyl. The results shown potential of the nanocomposite in photocatalytic and antioxidant activity giving quick, easy, and affordable alternative. [ABSTRACT FROM AUTHOR]

One of the critical issues faced by the desalination plants is an accurate analysis of their real-time performance. Soft computing techniques are efficient in overcoming these issues and predicting accurate outcomes. In this paper, models based on the third version of the modified particle swarm optimization algorithm called autonomous groups particles swarm optimization—based artificial neural network (AGPSO3-ANN) have been proposed for accurate prediction of permeate flux of reverse osmosis (RO) desalination plant. It employs remarkable optimization strategy that demonstrates superiority than the conventional PSO-ANN techniques, to update acceleration factors (c1 and c2) and to screen the global best solution. Here, four input parameters: evaporator inlet temperature, feedwater salt concentration, condenser inlet temperature, and feed flow rate have been considered for the modeling, and models' performance evaluated in terms of the regression coefficient (R2) and mean square errors (MSE). The results show an impressive agreement between simulated and experimental datasets indicating that the proposed approach is strongly capable of finding optimal solutions to predict accurate results with minimum errors (R2 = 99.2%, MSE = 0.005) compared to the existing ANN approaches. This demonstrates that the proposed models based on such soft computing tools like AGPSO3-ANN are perfect for analyzing and predicting real-time desalination plant performance that would present an effective way for improved process control and efficiency for plant engineers. [ABSTRACT FROM AUTHOR]

This work describes the preparation of new eco-friendly adsorbents with a simple method. At first, Montmorillonite (MMT) was modified with surfactant HTAB (MMT@HTAB) and then with polymer PEG (MMT@HTAB@PEG). The as-synthesized materials were characterized by several characterization techniques, including XRD, FTIR, SEM, TEM, TGA, N2 adsorption/desorption isotherm analysis by the BET method and zeta potential measurement then evaluated as adsorbents for removal of both methylene blue (MB) as a cationic dye and trypan blue (TB) as the anionic dye from aqueous solution under different contact time, dye concentration, temperature, and pH. The obtained results confirm the intercalation of surfactant within the clay layers, while the obtained nanocomposite showed different morphologies and structures in which the exfoliated and intercalated forms were obtained. The maximum adsorption capacity of TB and MB was found to be 190.81 and 237.22 mg/g, respectively, with MMT@HTAB@PEG adsorbent in an initial concentration of 100 mg/L at alkaline pH in 35 min and a temperature of 25 °C. The adsorption kinetics of TB and MB on MMT@HTAB@PEG was best fitted by the pseudo-second order model, and the isotherms results reveals better consistency of the Langmuir model, indicating that the adsorption is favorable and in the form of multilayers. The thermodynamic study showed that the adsorption processes of TB and MB by the both MMT@HTAB and MMT@HTAB@PEG adsorbents occur in an autonomous way and the temperature has not a significant effect on the adsorption capacity of TB and MB dyes. In addition, MMT@HTAB showed good antibacterial activity against both Escherichia coli (ATCC 8739) and Micrococcus luteus (ATCC 9341) bacteria compared to MMT@HTAB@PEG. The broadcast area was found to be 6 and 5 mm in Escherichia coli (ATCC 8739) and Micrococcus luteus (ATCC 9341), respectively. [ABSTRACT FROM AUTHOR]

This work concerns the preparation of multifunctional composite beads based on Cu-Alginate and AgNPs. First, the Cu-Alginate hydrogel was obtained by adding alginate at different concentrations of the crosslinking agent Cu2+ (2%, 4%, and 8%). The obtained hydrogels were modified by Ag+ species then by a chemical treatment (using NaBH4) followed by freeze-drying. The obtained aerogel beads were characterized by different methods and then were used as catalysts for the reduction of organic pollutants in a simple and binary system, and also as antibacterial and antifungal agents on different strains. The results showed the formation of a porous structure containing well-dispersed silver nanoparticles in the alginate matrix. The concentration of the Cu2+ crosslinking agent significantly influences the content of encapsulated AgNPs, the catalytic activity, and thus the antibacterial and antifungal properties of the resulting material. In the catalysis part, the Cu(2%)-ALG(AgNPs) material was selected as the most efficient catalyst due to the presence of high content of AgNPs and their good dispersion in the alginate biopolymer. High conversions of MO, 4-NP, MB, and CR were obtained in a reaction time of 2.5, 26, 23, and 29 min, respectively. Thus for binary systems, the Cu(2%)-ALG(AgNPs) catalyst was more selective with the MB dye. For antibacterial and antifungal activities all materials were effective through six strains, but it was shown that materials with unreduced Ag+ species were more effective. [ABSTRACT FROM AUTHOR]

Simple and easy synthesis of ZnO nanoparticles is done using Zinc metal dust and double distilled water. ZnO nano-powder is synthesized by using two methods: reflux (ZnO) and hydrothermal methods (ZnO-24 h. and ZnO-48 h.) using Zinc metal dust as a precursor. Photoanode plays an important role in dye-sensitized solar cells, a compact layer is included via the SILAR method to reduce the recombination. The hydrothermal synthesis is carried out at two different temperatures. Results show that ZnO powder has a wurtzite crystalline structure with a band gap of 3.2 eV. Here these powders are further used to fabricate Dye-Sensitized Solar cells. From J-V characteristics the short circuit current for ZnO was 1.88 mA cm−2, Voltage was observed to be 0.54 V, fill factor was observed to be 0.48, and Efficiency was observed to be 0.5%. The various other parameters such as chronoamperometry, chronopotentiometry, and Electrochemical Impedance spectroscopy supporting the J-V characteristics were also studied. The external quantum efficiency very well supports the optical absorption spectra of the N3 dye. [ABSTRACT FROM AUTHOR]

In recent decades, nature-inspired optimization methods have played a critical role in helping industrial plant designers to find superior solutions for process parameters. According to the literature, such methods are simple, quick, and indispensable for saving time, money, and energy. In this regard, the Modified Whale Optimization Algorithm (MWOA) hybridized with Artificial Neural Networks (ANN) has been employed in the Reverse Osmosis (RO) desalination plant performance to estimate the permeate flux (0.118‒2.656 L/h m2). The plant's datasets have been collected from the literature and include four input parameters: feed flow rate (400‒600 L/h), evaporator inlet temperature (60‒80 °C), feed salt concentration (35‒140 g/L) and condenser inlet temperature (20‒30 °C). For this purpose, ten predictive models (MWOA-ANN Model-1 to Model-10) have been proposed, which are capable of predicting more accurate permeate flux (L/h m2) than the existing models (Response Surface Methodology (RSM), ANN and hybrid WOA-ANN models) with minimum errors. Simulation results suggest that the MWOA algorithm demonstrates a stronger optimization capability of finding the correct weights and biases so as to enable superior ANN based modeling without limitation of overfitting. Ten MWOA-ANN models (Model-1 to Model-10) have been proposed to investigate the plant's performance. Model-6 with a single hidden layer (H = 1), eleven hidden layer nodes (n = 11) and the thirteen search agents (SA = 13) produced most outstanding regression results (R2 = 99.1%) with minimal errors (MSE = 0.005). The residual errors for Model-6 are also found to be within limits (span of − 0.1 to 0.2). Finally, the findings show that the screened MWOA-ANN models are promising for identifying the best process parameters in order to assist industrial plant designers. [ABSTRACT FROM AUTHOR]

It is given wrongly as "Advanced Physics Laboratory, Department of Physics, Savitribai Pule Pune University, Pune 411007, India" but should have been "Advanced Physics Laboratory, Department of Physics, Savitribai Phule Pune University, Pune 411007, India". B Correction to: J Mater Sci: Mater Electron (2023) 34:1864 b https://doi.org/10.1007/s10854-023-11242-8 In this article there are typo in the affiliation details In Affiliation 1, "Pule" should be "Phule" (h is missing). The complete affiliation should be "Department of Physics, College of Science, Princess Nourah bint Abdulrahman University, 11671 Riyadh, Saudi Arabia" Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. [Extracted from the article]

Field emission from nanostructured films is known to be dominated by only small number of localized spots which varies with the voltage, electric field and heat treatment. It is important to develop processing methods which will produce stable and uniform emitting sites. In this paper we report a novel approach which involves analysis of Proximity Field Emission Microscopic (PFEM) images using Scanning Probe Image Processing technique. Vertically aligned carbon nanotube emitters have been deposited on tungsten foil by water assisted chemical vapor deposition. Prior to the field electron emission studies, these films were characterized by scanning electron microscopy, transmission electron microscopy, and Atomic Force Microscopy (AFM). AFM images of the samples show bristle like structure, the size of bristle varying from 80 to 300 nm. The topography images were found to exhibit strong correlation with current images. Current--Voltage (I-V) measurements both from Scanning Tunneling Microscopy and Conducting-AFM mode suggest that electron transport mechanism in imaging vertically grown CNTs is ballistic rather than usual tunneling or field emission with a junction resistance of ~10 kΩ. It was found that I-V curves for field emission mode in PFEM geometry vary initially with number of I-V cycles until reproducible I-V curves are obtained. Even for reasonably stable I-V behavior the number of spots was found to increase with the voltage leading to a modified Fowler--Nordheim (F-N) behavior. A plot of ln(I/V³) versus 1/V was found to be linear. Current versus time data exhibit large fluctuation with the power spectral density obeying 1/f² law. It is suggested that an analogue of F-N equation of the form ln(I/Vα) versus 1/V may be used for the analysis of field emission data, where α may depend on nanostructure configuration and can be determined from the dependence of emitting spots on the voltage. [ABSTRACT FROM AUTHOR]

This article addresses the growth of hollow nanocrystalline particles of γ-alumina by the post-oxidation of nano-aluminium particles in air. The nanoparticles of aluminium were synthesized in a DC-transferred arc thermal plasma reactor. The as-synthesized nano-aluminium particles were oxidized, in air, at different temperatures. The as-synthesized parent nano aluminium and their daughter nanoparticles of aluminium oxide were thoroughly characterized with the help of X-ray diffraction analysis, high resolution transmission electron microscopy and thermogravimetric analysis. Two-step oxidation behaviours, unique in nanoparticles, are found to be the main driving force behind the formation of hollow spherical structures. The entire phenomenon is compared with the oxidation behaviour of coarse grain aluminium. The content of γ-alumina, identified by X-ray diffraction, relative to that of unreacted aluminium, has increased almost exponentially with the oxidation temperature in the case of nano aluminium. Similar behaviour is not observed in the case of coarse grain aluminium. The crystalline features of alumina, forming the walls of the hollow sphere, were confirmed by high resolution transmission electron microscopy. [ABSTRACT FROM AUTHOR]

A combination of carbon nanotubes (CNT) and graphene in the form of macroscopic hybrid buckypaper (HBP), exhibits a unique set of properties that can be exploited for many emerging applications. Here, we present a simple, inexpensive and scalable approach for the synthesis of highly conductive auxetic graphene/CNT HBP via wet-filtration-zipping and demonstrate the electrical, electrochemical and mechanical performance (tensile, mode I and mode III fracture) of synthesized HBP. An overall increase in electrical conductivity of 247% is observed for HBP (50 wt.% graphene and 50 wt.% CNT) as compared to BP (100 wt.% CNT) due to effective electronic percolation through the graphene and CNT. As a negative electrode for lithium-ion batteries, HBP shows 50% higher gravimetric specific capacity and 89% lower charge transfer resistance relative to BP. The graphene content in the HBP influences the mechanical performance providing an auxetic structure to HBP with large negative Poisson’s ratio. The facile green-chemistry approach reported here can be readily applied to any other 1D and 2D materials and solves key challenges associated with existing buckypaper manufacturing methods. The potential of the synthesis method to integrate with current cellulose paper manufacturing technology and its scalability demonstrate the novelty of the work for industrial scale production. [ABSTRACT FROM AUTHOR]