Complex optical constants and interband transitions of a hybrid perovskite CsPbBr3 thin film measured by spectroscopic ellipsometry.

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Construction of van der Waals (vdW) nanocomposites can advance two-dimensional (2D) materials with desired properties and significantly widen their applications. Based on first-principles calculations, we verify that a gallium nitride/boron phosphide (GaN/BP) vdW nanocomposite is a direct-gap semiconductor with type-I band alignment. The nanocomposite shows significant optical properties in the visible and near-ultraviolet regions. Additionally, the bandgap, band edge positions, and optical absorption of the GaN/BP nanocomposite can be tuned by in-plane biaxial strains. A biaxial tensile strain with a strength of 3% can induce the type-II band alignment in the GaN/BP nanocomposite, which results in effective separation of the photogenerated charge carriers. Meanwhile, the application of biaxial strain can also significantly enhance the optical absorption of the GaN/BP nanocomposite in the near-infrared and visible regions. Furthermore, we show that the adjustment of interlayer coupling is also an effective way to modulate the electronic and optical properties of the GaN/BP nanocomposite. Our studies reveal the potential application of the GaN/BP nanocomposite in optoelectronic devices.

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Beef offal (i.e., kidney, liver, heart, lung) adulteration of beefburgers was studied using dispersive Raman spectroscopy and multivariate data analysis to explore the potential of these analytical tools for detection of adulterations in comminuted meat products with complex formulations. Adulterated (n = 46) and authentic (n = 36) beefburger samples were produced based on formulations derived using market knowledge and an experimental design. Raman spectral data in the fingerprint range (900-1800 cm(-1)) were examined using both a classification (partial least-squares discriminant analysis, PLS-DA) and class-modeling (soft independent modeling of class analogy, SIMCA) approach to identify offal-adulterated and authentic beefburgers. PLS-DA models correctly classified 89-100% of authentic and 90-100% of adulterated samples. SIMCA models were developed using either PCA or PLS scores as input data. For authentic beefburgers, they exhibited sensitivity, specificity, and efficiency values of 0.94-1, 0.64-1, and 0.80-0.97, respectively. PLS regression quantitative models were also developed in an attempt to quantify total offal and added fat in these samples. The performance of PLS regression quantitative models for prediction of added fat may be acceptable for screening purposes, with the most accurate model producing a coefficient of determination in prediction of 0.85 and a root-mean-square error of prediction equal to 3.8% w/w.

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