Nowadays, metal oxide semiconductors (MOS)-reduced graphene oxide (rGO) nanocomposites have attracted significant research attention for gas sensing applications. Herein, a novel composite material is synthesized by combining two p-type semiconductors, i.e., Cu2O and rGO, and a p-p-type gas sensor is assembled for NO2 detection. Briefly, polypyrrole-coated cuprous oxide nanowires (PPy/Cu2O) are prepared via hydrothermal method and combined with graphene oxide (GO). Then, the nanocomposite (rGO/PPy/Cu2O) is obtained by using high-temperature thermal reduction under Ar atmosphere. The results reveal that the as-prepared rGO/PPy/Cu2O nanocomposite exhibits a maximum NO2 response of 42.5% and is capable of detecting NO2 at a low concentration of 200 ppb. Overall, the as-prepared rGO/PPy/Cu2O nanocomposite demonstrates excellent sensitivity, reversibility, repeatability, and selectivity for NO2 sensing applications.
Kefir is a traditional fermented milk beverage used throughout the world for centuries. A cell-penetrating peptide, F3, was isolated from kefir by Sephadex G-50 gel filtration, DEAE-52 ion exchange, and reverse-phase high-performance liquid chromatography. F3 was determined to be a low molecular weight peptide containing one leucine and one tyrosine with two phosphate radicals. This peptide displayed antimicrobial activity across a broad spectrum of organisms including several Gram-positive and Gram-negative bacteria as well as fungi, with minimal inhibitory concentration (MIC) values ranging from 125 to 500 μg/mL. Cellular penetration and accumulation of F3 were determined by confocal laser scanning microscopy. The peptide was able to penetrate the cellular membrane of Escherichia coli and Staphylococcus aureus. Changes in cell morphology were observed by scanning electron microscopy (SEM). The results indicate that peptide F3 may be a good candidate for use as an effective biological preservative in agriculture and the food industry.
Many studies have been carried out to investigate the scale effect on the shear behavior of rock joints. However, existing methods are difficult to determinate the joint roughness coefficient (JRC) and the shear strength of rock joints with incomplete and indeterminate information; the nature of scale dependency of rock joints is still unknown and remains an ongoing debate. Thus, this paper establishes two neutrosophic functions of the JRC values and the shear strength based on neutrosophic theory to express and handle the incomplete and indeterminate problems in the analyses of the JRC and the shear strength. An example, including four rock joint samples derived from the pyroclastic rock mass in Shaoxing city, China, is provided to show the effectiveness and rationality of the developed method. The experimental results demonstrate that the proposed neutrosophic functions can express and deal with the incomplete and indeterminate problems of the test data caused by geometry complexity of the rock joint surface and sampling bias. They provide a new approach for estimating the JRC values of the different-sized test profiles and the peak shear strength of rock joints.
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