To grapple with multidrug resistant bacterial infections, implementations of antibacterial nanomedicines have gained prime attention of the researchers across the globe. Nowadays, zinc oxide (ZnO) at nano‐scale has emerged as a promising antibacterial therapeutic agent. Keeping this in view, ZnO nanostructures (ZnO‐NS) have been synthesised through reduction by P. aphylla aqueous extract without the utilisation of any acid or base. Structural examinations via scanning electron microscopy (SEM) and X‐ray diffraction have revealed pure phase morphology with highly homogenised average particle size of 18 nm. SEM findings were further supplemented by transmission electron microscopy examinations. The characteristic Zn–O peak has been observed around 363 nm using ultra‐violet–visible spectroscopy. Fourier‐transform infrared spectroscopy examination has also confirmed the formation of ZnO‐NS through detection of Zn–O bond vibration frequencies. To check the superior antibacterial activity of ZnO‐NS, the authors'' team has performed disc diffusion assay and colony forming unit testing against multidrug resistant E. coli, S. marcescens and E. cloacae. Furthermore, protein kinase inhibition assay and cytotoxicity examinations have revealed that green fabricated ZnO‐NS are non‐hazardous, economical, environmental friendly and possess tremendous potential to treat lethal infections caused by multidrug resistant pathogens.Inspec keywords: nanomedicine, zinc compounds, II‐VI semiconductors, wide band gap semiconductors, nanoparticles, scanning electron microscopy, X‐ray diffraction, antibacterial activity, transmission electron microscopy, particle size, Fourier transform infrared spectra, ultraviolet spectra, visible spectra, enzymes, biochemistry, molecular biophysics, microorganisms, drugs, toxicology, bonds (chemical), semiconductor growth, nanofabrication, vibrational modesOther keywords: green synthesised zinc oxide nanostructures, Periploca aphylla extract, antibacterial potential, multidrug resistant pathogens, multidrug resistant bacterial infections, antibacterial nanomedicines, P. aphylla aqueous extract, structural examinations, scanning electron microscopy, X‐ray diffraction, pure phase morphology, homogenised average particle size, SEM, transmission electron microscopy, Fourier‐transform infrared spectroscopy, bond vibration frequency, antibacterial activity, disc diffusion assay, colony forming unit testing, S. marcescens, E. cloacae, E. coli, ultraviolet‐visible spectroscopy, protein kinase inhibition assay, cytotoxicity, lethal infections, ZnO相似文献
The ternary strategy for incorporating multiple photon-sensitive components into a single junction has emerged as an effective method for optimizing the nanoscale morphology and improving the device performance of organic solar cells (OSCs).In this study,efficient and stable ternary OSCs were achieved by introducing the small-molecule dye (5E,5'E)-5,5'-(4',4″-(1,2-diphenylethene-1,2-diyl)bis(biphenyl-4',4-diyl))bis(methan-1-yl-1-ylidene)bis(3-ethyl-2-thioxothia zolidin-4-one) (BTPERn) into poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiopheneco-3-fluorothieno[3,4-b]thiophene-2-carboxylate] (PTB7-Th):[6,6]-phenyl C71 butyric acid methyl ester (PC71BM) blend films processed using a 1,8-diiodooctane (DIO)-free solvent.The incorporation of BTPE-Rn enhanced the short-circuit current density and fill factor of the ternary OSCs compared with those of binary OSCs.An investigation of the optical,electronic,and morphological properties of the ternary blends indicated that the third component of BTPE-Rn not only promoted the photon utilization of blends through the energy-transfer process but also improved the electron mobility of the blends owing to the fullerene-rich nanophase optimization.More importantly,this ternary strategy of utilizing a small-molecule dye to replace the photounstable DIO additive enhanced the operational stability of the OSCs. 相似文献
Carbon-coated SiC@C nanocapsules (NCs) with a hexagonal platelet-like morphology were fabricated by a simple direct current (DC) arc-discharge plasma method.The SiC@C NCs were monocrystalline,120-150 nm in size,and approximately 50 nm thick.The formation of the as-prepared SiC@C NCs included nucleation of truncated octahedral SiC seeds and subsequent anisotropic growth of the seeds into hexagonal nanoplatelets in a carbon-rich atmosphere.The disordered carbon layers on the SiC@C NCs were converted into SiO2 shells of SiC@SiO2 NCs by heat treatment at 650 ℃ in air,during which the shape and inherent characteristics of the crystalline SiC core were obtained.The interface evolution from carbon to SiO2 shells endowed the SiC@SiO2 NCs with enhanced photocatalytic activity due to the hydrophilic and transparent nature of the SiO2 shell,as well as to the photosensitive SiC nanocrystals.The band gap of the nanostructured SiC core was determined to be 2.70 eV.The SiC@SiO2 NCs degraded approximately 95% of methylene blue in 160 min under visible light irradiation. 相似文献
Nano-Micro Letters - A NiFe2O4/expanded graphite (NiFe2O4/EG) nanocomposite was prepared via a simple and inexpensive synthesis method. Its lithium storage properties were studied with the goal of... 相似文献
In this article, we have examined the performance of some useful capability indices using normal and non-normal distributions. The confidence intervals are calculated and mean coverage rates are observed for different capability indices. The effects of symmetry and kurtosis of parent distributions are examined on the mean coverage rates of different capability indices. Moreover, we have investigated the robustness (of confidence interval) using the median and percentile-based indices. We have considered the well-known distributions including normal, gamma, t, Weibull, and chi-squared. For these process scenarios, we have observed that some indices resist disturbance only in symmetry of the parent distribution, some resist the disturbance in symmetry and kurtosis of the distribution, and some indices don’t resist against either type of disturbance. 相似文献
In this work, the authors report a facile low‐temperature wet‐chemical route to prepare morphology‐tailored hierarchical structures (HS) of copper oxide. The preparation of copper oxide collides was carried out using varying concentrations of copper acetate and a reducing agent at a constant temperature of 50°C. The prepared HS of CuO were characterised by powdered X‐rays diffraction that indicates phase pure having monoclinic structures. The morphology was further confirmed by field‐emission scanning electron microscope. It reveals a difference in shape and size of copper oxide HS by changing the concentration of reactants. In order to evaluate the effect of H2 O2 on CuO NPs, the prepared CuO are modified by treatment with H2 O2. In general trend, CuOH2 O2 collide showed enhanced protein kinase inhibition, antibacterial (maximum zone 16.34 mm against Staphylococcus aureus) and antifungal activities in comparison to unmodified CuO collides. These results reveal that CuO HS exhibit antimicrobial properties and can be used as a potential candidate in pharmaceutical industries.Inspec keywords: molecular biophysics, antibacterial activity, X‐ray diffraction, microorganisms, copper compounds, nanofabrication, nanoparticles, narrow band gap semiconductors, field emission scanning electron microscopy, enzymes, nanomedicine, particle size, semiconductor growthOther keywords: unmodified CuO collides, low‐temperature synthesis, morphology‐tailored hierarchical structures, copper acetate, reducing agent, monoclinic structures, copper oxide HS, CuO NPs, Staphylococcus aureus, biological activity, copper oxide, powdered X‐ray diffraction, field‐emission scanning electron microscopy, facile low‐temperature wet‐chemical method, protein kinase inhibition, antibacterial activity, antifungal activity, antimicrobial properties, pharmaceutical industries, temperature 50.0 degC, CuO相似文献
Construction of macro-materials with highly oriented microstructures and well-connected interfaces between building blocks is significant for a variety of applications. However, it is still challenging to confine the desired structures. Thus, well-defined building blocks would be crucial to address this issue. Herein, we present a facile process based on 1.8 nm Pd nanoclusters (NCs) to achieve centimeter-size assemblages with aligned honeycomb structures, where the diameter of a single tubular moiety is ~4 μm. Layered and disordered porous assemblages were also obtained by modulating the temperature in this system. The reconciled interactions between the NCs were crucial to the assemblages. As a comparison, 14 nm Pd nanoparticles formed only aggregates. This work highlights the approach of confining the size of the building blocks in order to better control the assembly process and improve the stability of the structures.
With the recent developments in the Internet of Things (IoT), the amount of data collected has expanded tremendously, resulting in a higher demand for data storage, computational capacity, and real-time processing capabilities. Cloud computing has traditionally played an important role in establishing IoT. However, fog computing has recently emerged as a new field complementing cloud computing due to its enhanced mobility, location awareness, heterogeneity, scalability, low latency, and geographic distribution. However, IoT networks are vulnerable to unwanted assaults because of their open and shared nature. As a result, various fog computing-based security models that protect IoT networks have been developed. A distributed architecture based on an intrusion detection system (IDS) ensures that a dynamic, scalable IoT environment with the ability to disperse centralized tasks to local fog nodes and which successfully detects advanced malicious threats is available. In this study, we examined the time-related aspects of network traffic data. We presented an intrusion detection model based on a two-layered bidirectional long short-term memory (Bi-LSTM) with an attention mechanism for traffic data classification verified on the UNSW-NB15 benchmark dataset. We showed that the suggested model outperformed numerous leading-edge Network IDS that used machine learning models in terms of accuracy, precision, recall and F1 score. 相似文献