Applied Nanoscience最新文献

This study investigates the enhancement of molybdenum disulfide (MoS₂) nanoparticles with polyethylene glycol (PEG) to improve peroxidase activity and antibiotic degradation capabilities. X-ray photoelectron spectroscopy confirmed successful modification, showing shifts in Mo and S binding energies. Scanning electron microscopy revealed an increase in nanoparticle size from 117.8–178.74 nm (MoS₂) to 99.73–200.20 µm (MoS₂-PEG), likely due to agglomeration. MoS₂-PEG demonstrated optimal peroxidase activity at 60 µg/mL concentration and 12 mM H₂O₂, with maximum efficiency at pH 5 and 30 °C, highlighting its pH sensitivity and moderate thermal stability. Under these conditions, MoS₂-PEG achieved nearly complete degradation of 10 mg/L Cefotaxime (CFX) within 312 min, identifying three metabolites (CFX 1, CFX 2, and CFX 3) in the degradation pathway. The study concludes that MoS₂-PEG nanoparticles are effective for peroxidase reactions and antibiotic degradation, positioning them as promising candidates for wastewater treatment. Their stability, reusability, and potential for sustainable applications underscore their value in developing cost-effective solutions for removing antibiotics from contaminated water sources.

The present work summarizes the mechanical, tribological, and corrosion properties of the aluminum 6061 alloy composite that has been strengthened with a novel combination of 2 wt% nano-silicon dioxide (nSiO₂) and varying percentages of tungsten carbide (WC) particles. Microstructural analysis, microhardness, tensile testing, impact testing, and porosity measures have all been assessed in addition to wear and corrosion studies. The results showed that adding 2 wt% nSiO₂ to the Al matrix caused the porosity of the composites to decrease, and adding WC caused it to rise. All composites exhibited an improvement in hardness but a decrease in impact strength. The composite containing 9 wt% WC (NAC4) has a hardness that is 2.3, 1.58, 1.35, and 1.25 times greater than that of the ACA, NAC1, NAC2, and NAC3 composites, in that order. The addition of nSiO₂ and an increasing amount of WC reduces elongation and increases tensile strength. The ultimate tensile strength of the NAC4 composites increased by 46.72, 27.86, 24.59, and 10.65%, respectively, compared to the ACA, NAC1, NAC2, and NAC3 composites. The cracked surface of the nSiO₂ with WC-reinforced composites displays a mixed fracture mechanism with dimples, voids, and cracks. In the wear test under 30 N load, the NAC4 composite shows 5.27, 4.72, 4.02, and 1.12 times lower wear rates than ACA, NAC1, NAC2, and NAC3 composites, respectively. As the concentration of WC particles increases, composites become more resistant to corrosion. According to the results, the polarization curve demonstrated a positive shift in E_corr from − 1.189 to − 0.656 V as the amount of WC increased, and the i_corr decreased to 4.974 × 10^–4 from 7.695 × 10^–4 A/cm².

This study examines the impact of copper oxide (CuO), iron oxide (Fe₃O₄), and their composite (Fe₃O₄@CuO) nanoparticles on harmful microorganisms in tomato plant roots and stems. The research evaluates agro-environmental factors, including soil composition, moisture levels, and temperature, that influence the efficacy of these nanoparticles. The nanoparticles prepared by the PLAL technique were subjected to structural, morphological, topographic, and optical analysis using a range of methods, including XRD, FE-SEM, EDS, AFM, and UV–Visible spectroscopy. The copper and iron composite particles were found to be polycrystalline, with the iron element present in magnetite and hematite phases. The particles exhibited a spherical form, however, there was agglomeration between them. The optical characteristics exhibited plasmon resonance peaks, indicating the transition of the materials into an optimal nanoscale phase. Both laboratory and field studies were conducted to assess their antifungal activity. The findings reveal that the Fe₃O₄@CuO composite exhibited superior pathogen suppression compared to the individual nanoparticles. This research offers valuable insights into the application of nanoparticles for controlling plant fungal and bacterial diseases, contributing to more effective and sustainable agricultural practices.

The present research explores the dispersion of SiO₂ nanoparticles in compressor lubricant, polyolester (POE) oil for performance enhancement of vapour compression refrigeration system (VCRS). The contribution of SiO₂ nanoparticles based nanolubricant was examined for eco-friendly hydrocarbon (HC) refrigerant R600a, retrofitted to hydrofluorocarbon (HFC) compressor based VCRS and also in HC compressor, in governing the performance of VCRS. Wear characteristics improved by the nanolubricants were assessed through pin-on-disc wear testing, using the pins extracted from the actual compressor piston used in VCRS. As compared to POE oil, the average specific wear rate (SWR) and coefficient of friction (COF) of nanolubricant were reduced by about 20% and 29%, respectively. Enhanced average viscosity and average thermal conductivity were observed (35–95 °C), with maximum increases of about 13% at 65 °C and 45% at 95 °C, respectively, in comparison to those of POE oil. Field emission scanning electron microscopy (FE-SEM) was utilized to analyze the morphology of SiO₂ nanoparticles, while Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analyzed their crystal structure. The Zeta potential tests for the prepared nanolubricant were conducted to ensure its long-term stability. An HC compressor based VCRS shows better performance including average refrigeration effect, average power consumption by compressor, and the average coefficient of performance (COP) of 29%, 7%, and 39%, respectively compared to the base lubricant filled retrofitted system. Hence the findings of the present research provide novel perspectives on the potential benefits of incorporating SiO₂ nanoparticles and an HC compressor to improve the VCRS performance.

In recent years, there has been an exponential increase in the production of silver bionanoparticles due to their widespread commercialization and technological applications. However, there is limited understanding of the impact of silver bionanoparticles on biological agents commonly used in wastewater treatment, particularly in waste stabilization ponds (WSPs). This study aimed to synthesize new silver nanoparticles (sg-AgNPs) from Synadenium glaucescens root using an environmentally friendly method and optimized biosynthesis parameters, and evaluate their antimicrobial activity and ecotoxicological impact on WSPs using standardized approaches. The average primary sizes of the sg-AgNPs in the five samples were not significantly different (P > 0.05), indicating the effectiveness of the eco-friendly method and the importance of optimal biosynthesis conditions. Analysis from UV–Vis spectroscopy, energy-dispersive spectroscopy (EDX), transmission electron microscope (TEM), and X-ray diffraction (XRD) confirmed that sg-AgNPs exhibited typical characteristics of green silver nanoparticles. Furthermore, sg-AgNPs showed strong antimicrobial activity (MIC, 0.012–0.094 mg/ml) against gram-positive bacteria (Escherichia coli), gram-negative bacteria (Staphylococcus aureus), non-filamentous fungi (Candida albicans) and filamentous fungi (Aspergillus niger). While the Synadenium glaucescens root proved to be a valuable precursor for producing effective antimicrobial sg-AgNPs, the introduction of sg-AgNPs into WSPs significantly impacted algal chlorophyll-a production and survival of ostracod population. These results shed light on the ecotoxicological risks of sg-AgNPs for WSPs organisms and highlight the suitability of algae and ostracods as model organisms for ecotoxicological studies in WSPs.

Zinc oxide (ZnO) has been extensively used in areas such as optoelectronics, solar cells, and photocatalysis, among others. Modifying the optical properties of ZnO through different processes can potentially improve the performance of devices based on this material. This work presents the biosynthesis of ZnO by Beaucarnea gracilis leaf extract. The natural extract was mixed with zinc nitrate hexahydrate, Zn(NO₃)₂·6H₂O resulting in a precipitate. Then the precipitate was calcined for 2 h at 400 °C, resulting in a yellowish-ZnO powder. Diffraction laser measurements showed a particle size average of 419 nm. The material exhibited high absorption in the UVA region with photoluminescence at 530 nm. Moreover, from the Tauc plot, a 2.7 eV band gap was obtained. Fourier Transform Infrared (FTIR) spectroscopy results confirmed the ZnO synthesis through 550 cm⁻¹ and 667 cm⁻¹ absorption peaks. To the best of our knowledge, this is the first time that ZnO has been synthesized by the endemic plant Beaucarnea gracilis. A major difference with conventional ZnO is significant reduction in the band gap from 3.3 eV to 2.7 eV. Moreover, the material exhibited photoluminescence at 530 nm by exposure to UV light which is attributed to oxygen vacancies. The increase in the optical absorbance in the UV–Visible region and the reduction in the optical band gap could enhance the performance in solar cells based on ZnO and in photocatalysis processes, allowing the use of visible light sources in addition to UV light.

Producing biomechanical energy from waste polymer has attracted lot of interest in this digital era as a number of benefits can be accounted for this including: (i) addressing challenges in the disposal of waste materials, and pollution (air, water, soil) caused by their presence in the atmosphere (ii) ensuring clean and affordable energy at low cost (iii) avoiding the hassle of constant battery replacement, charging, and long wires for charging, and so on. Here, the authors aim at the recycling of waste materials, especially polymers, keeping the 4R’s of effective waste management in mind. Energy harvesters based on triboelectric/piezoelectric effects convert energy from vibrational waves and material deformations into electricity. A hybrid energy harvester is constructed, with waste polymer to act as the tribo-active layer, nanomaterial coating is applied to induce piezoelectricity and Al as the electrode. The energy harvester demonstrated an output voltage enhancement of 266.166% for qualitative input conditions and 375.374%, 337.33%, and 287.308% for quantized input conditions (1 N, 1.5 N, 3 N respectively) when compared with the performance of raw waste polymer-based energy harvester. The developed device could drive low-power portable electronic devices, such as LEDs, calculator, digital watch, thermometer and pedometer.

Responding to the pressing need to mitigate climate change effects due to fossil fuel consumption, there is a collective push to transition towards renewable and clean energy sources. However, the effectiveness of this move depends on an efficient energy storage system that surpasses current lithium-ion battery technology. The lithium-oxygen battery, having significantly high theoretical specific capacity compared to other systems, has emerged as a promising solution. However, the issues of poor cathode electrode conductivity and slow kinetics during discharge product formation have limited its practical applications. In this work, the first principles-based density functional theory was used to investigate the electrocatalytic properties of β₁₂-borophene as a cathode electrode material for a high-performance lithium-oxygen battery. The adsorption energy, charge density distributions, Gibbs free energy changes, and diffusion energy barriers of lithium superoxide (LiO₂) on β₁₂-borophene were calculated. Our findings revealed several important insights: The adsorption energy was found to be − 3.70 eV, suggesting a strong tendency for the LiO₂ to remain anchored to the material during the discharging process. The dynamics in the charge density distributions between LiO₂ and the β₁₂-borophene substrate exhibited complex behavior. The analysis of the Gibbs free energy changes of the reactions yielded an overpotential of − 1.87 V, this moderate value suggests spontaneous reactions during the formation of the discharge products. Most interestingly, the density of states and band structure analysis suggested the preservation of metallic properties and improved electrical conductivity of the material after the adsorption of LiO₂. Additionally, β₁₂-borophene has a relatively low diffusion energy barrier of 1.08 eV, implying effortless diffusion of the LiO₂ and an increase in the rate of discharging process. Ultimately, the predicted electronic properties of β₁₂-borophene, make it a strong candidate as a cathode electrode material for an efficient lithium-oxygen battery.

Random lasers operate without a traditional resonator cavity compared with traditional lasers, instead relying on multiple scattering events within a disordered medium to amplify light. Their emission spectrum and spatial characteristics are determined by the disorder within the medium rather than by specific resonant modes. ZnO nanostructures are ideal for random lasers due to their strong light emission properties and high refractive index, facilitating efficient light scattering and amplification within the disordered medium. Additionally, their wide bandgap and ability to support both optical and electrical pumping make them versatile for various laser applications. ZnO-based random lasers unlock a future beyond high-resolution displays and foldable phones due to their speckle-free emission and a knack for scattering. In medicine, they promise label-free cellular insights, targeted cancer treatments, and miniaturized diagnostics. However, the future of ZnO-based random lasers demands careful crafting. Scalability, cost, and longevity remain hurdles. This review first addresses the synthesis parameters controlling ZnO nanostructures as gain media in random lasers. Then, recent advances in random laser design and performance are discussed, followed by an explanation of the pumping mechanisms. The review concludes by addressing the potential applications of ZnO-based random lasers, including sensors, imaging, medical and display technologies.

Recently, membrane bioreactors (MBRs) have emerged as a promising approach for sewage treatment because of their high efficiency in removing contaminants. However, they are prone to membrane-fouling and computational loading. To resolve these issues, this research article presents an innovative control strategy combining both artificial bee colony optimization (ABC) and recurrent neural network (RNN) to regulate the performance of MBR in sewage treatment. Initially, the influent wastewater data were collected and pre-processed using the regression imputation approach. RNN architecture was designed and trained using the pre-processed data to forecast the performance of the MBN system. Further, the ABC algorithm was applied to optimize the function of MBR by adjusting the control variables. The developed model was validated with the publically available wastewater treatment plan dataset and the effectiveness of the developed model was validated by performing intensive performance and comparative assessment. The performance evaluation demonstrates that the proposed methodology attained greater results of 98.59% effluent quality, 98.70% of nutrient removal efficiency, less computational time of 2.87 s, and a low membrane-fouling index of 1.23%. The comparative analysis illustrates that the presented approach achieved improved performances than the existing methodologies.