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A novel modified electrode has been successfully constructed with the use of a nano-composite mixture consisting of molybdenum disulfide (MoS 2 ) and gold nanoparticles (AuNPs). Its application as a cholesterol biosensor was investigated. The morphology of the prepared MoS 2 -AuNPs nanoparticles were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), atomic force microscope (AFM), X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDS). The physicochemical properties of the modified electrode at each stage of the construction were characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Quantitative analysis of cholesterol was carried out with the use of the amperometric i – t method, and the calibration plot for cholesterol was linear in the range of 0.5–48 μM with a limit of detection (LOD) of 0.26 ± 0.015 μM. The apparent Michaelis-Menten constant ( K M a p p ) and sensitivity were estimated to be 0.325 mM and 4460 μA mM −1 cm −2 , respectively. This novel sensor produced satisfactory reproducibility and stability, and was used successfully for the quantitative analysis of cholesterol in egg yolk and pork liver samples. [ABSTRACT FROM AUTHOR]

A novel 3D nano-flower-like Cu/multi-layer molybdenum disulfide composite (CuNFs/MoS 2 ) modified glassy carbon electrode (GCE) has been successfully constructed. It was a highly sensitive and selective non-enzymatic hydrogen peroxide (H 2 O 2 ) and glucose biosensor. The morphology of the obtained CuNFs-MoS 2 nano-particles was investigated with the use of a scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDS). The physicochemical properties of the modified electrode were characterized at each of the construction stages with the use of an electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) techniques. The new sensor combined the advantages of MoS 2 and CuNFs, and exhibited high electro-catalytic activity toward H 2 O 2 and glucose. Quantitative analysis of H 2 O 2 and glucose was carried out with the use of the amperometric i – t method. Linear ranges were obtained between 0.04–1.88 μM and 1.88–35.6 μM for H 2 O 2 and 1–20 μM and 20–70 μM for glucose, and their corresponding limits of detection (LOD) were 0.021 μM and 0.32 μM. This novel sensor was successfully applied for the quantitative analysis of H 2 O 2 in tap water and glucose in human serum samples. [ABSTRACT FROM AUTHOR]

The work demonstrated that solid citric acid, one of the most common food additives, can be converted to graphene quantum dots (GQDs) under microwave heating. The as-prepared GQDs were further characterized by various analytical techniques like transmission electron microscopy, atomic force microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, fluorescence and UV-visible spectroscopy. Cytotoxicity of the GQDs was evaluated using HeLa cells. The result showed that the GQDs almost did not exhibit cytotoxicity at concentrations as high as 1000 µg mL-1. In addition, it was found that the GQDs showed good solubility, excellent photostability, and excitation-dependent multicolor photoluminescence. Subsequently, the multicolor GQDs were successfully used as a fluorescence light-up probe for live-cell imaging. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Bulk graphitic carbon nitride (g-CN) was obtained by pyrolysis of urea at 600 °C. The material was then subjected to protonation and exfoliation to obtain strongly fluorescent g-CN nanosheets. These nanosheets are representing a two-dimensional layered material that emits strong blue fluorescence peaking at 434 nm, and their quantum yield of up to 10.3 % is much higher than that of bulk g-CN (6.0 %). It was found that Cu(II) ions quench the fluorescence of the nanosheets due to photo-induced electron transfer (PET), probably the result of the stronger binding affinity between Cu(II) and the nitrogen and oxygen functional groups of the nanosheets. The probe responds to Cu(II) in the 0.01 to 0.4 nM concentration range, with a 8 pM detection limit. The method was applied to the determination of Cu(II) in spiked water samples. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of spectra of the jujube ( Zizyphus jujuba Mill .) fruit samples from four geographical regions. Prediction models were developed for the quantitative prediction of the contents of jujube fruit, i.e., total sugar, total acid, total phenolic content, and total antioxidant activity. Four pattern recognition methods, principal component analysis (PCA), linear discriminant analysis (LDA), least squares-support vector machines (LS-SVM), and back propagation-artificial neural networks (BP-ANN), were used for the geographical origin classification. Furthermore, three multivariate calibration models based on the standard normal variate (SNV) pretreated NIR spectroscopy, partial least squares (PLS), BP-ANN, and LS-SVM were constructed for quantitative analysis of the four analytes described above. PCA provided a useful qualitative plot of the four types of NIR spectra from the fruit. The LS-SVM model produced best quantitative prediction results. Thus, NIR spectroscopy in conjunction with chemometrics, is a very useful and rapid technique for the discrimination of jujube fruit. [ABSTRACT FROM AUTHOR]