Large coherent acoustic phonon oscillations were demonstrated using InGaN/GaN multiple quantum wells with piezoelectric fields. With UV femtosecond pulse excitation, photogenerated carriers screened the piezoelectric field and initiated the displacive coherent phonon oscillations. The specific phonon frequency was selected by the coupling between the periodic carrier distribution and the corresponding acoustic phonon mode. The induced acoustic phonon oscillation resulted in piezoelectric field modulation and then caused absorption variation through the quantum confined Franz-Keldysh effect. The wave vector uncertainty due to the finite sample width was found to determine the observed dephasing time.

Abstract:A high affinity polyclonal antibody-based enzyme linked immunosorbent assay (ELISA) was developed for the quantification of zeranol in bovine urine. On the basis of urine matrix studies, the optimized dilution factors producing insignificant matrix interference were selected as 1:5 in pretreatment. In the improved ELISA, the linear response range was between 0.02 and 1 µg/ml , and the detection limit was 0.02 µg/ml for the assay. The overall recoveries and the coefficients of variation (CVs) were in the range of 82%~127% and 3.5%~8.8%, respectively. Thirty-six bovine urine samples spiked with zeranol (ranging from 0.2 to 10 µg/ml) were detected by the ELISA and liquid chromatography (LC) method, and good correlations were obtained between the two methods (R 2 =0.9643). We conclude that this improved ELISA is suitable tool for a mass zeranol screening and can be an alternative for the conventional LC method for zeranol in bovine urine.

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The classification of plastic waste before recycling is of great significance to achieve effective recycling. In order to achieve rapid, nondestructive, and on-site detection, a portable near-infrared spectrometer was used in this study to obtain the diffuse reflectance spectrum for both standard and commercial plastics made by ABS, PC, PE, PET, PP, PS, and PVC. After applying a series of pretreatments, the principal component analysis (PCA) was used to analyze the cluster trend. K-nearest neighbor (KNN), support vector machine (SVM), and back propagation neural network (BPNN) classification models were developed and evaluated, respectively. The result showed that different plastics could be well separated in top three principal components space after pretreatment, and the classification models performed excellent classification results and high generalization capability. This study indicated that the portable NIR spectrometer, integrated with chemometrics, could achieve excellent performance and has great potential in the field of commercial plastic identification.

Scale formation is a significant problem in a wide range of industries, including water treatment, food processing, power plants, and oilfield production. While surface modification provides a promising methodology to address this challenge, it has generally been believed that surface coatings with the lowest surface energy, such as fluorocarbon coatings, are most suitable for antiscaling applications. In contrast to this general knowledge, here we show that a liquid-like coating featuring highly mobile linear poly­(dimethylsiloxane) (LPDMS) brush chains can bring an even better antiscaling performance than conventional perfluoroalkylsilane coatings, despite the fact that the former has much higher surface energy than the latter. We demonstrate that the LPDMS brush coating can more effectively inhibit heterogeneous nucleation of scale on a substrate compared with common perfluoroalkylsilane or alkylsilane coatings, and the dynamic liquid-like characteristic of the LPDMS brush coating is speculated to be responsible for its excellent nucleation inhibiting ability by reducing the affinity and effective interface interaction between the substrate and the scale nucleus. Our findings reveal the great prospect of using liquid-like coating to replace environmentally hazardous fluorine-containing organic ones as a green and cost-effective solution to address the scale problem with enhanced antiscaling performance.

Ultrafast phase dynamics of free-induction decay for carriers in bulk GaAs is studied with differential-phase spectroscopy. The instantaneous phase shifts of the free-induction decay with respect to the excitation pulses are extracted from simultaneously recorded laser pulse autocorrelation and free-induction decay in GaAs. Ultrafast phase dynamics during and immediately after the femtosecond pulse excitation are numerically evaluated with optical Bloch equations using pump pulse and semiconductor exciton parameters as input. Good agreement of the theory with experiment is obtained.

No abstract

Dried tangerine peel is a Chinese medicine with high medicinal value. The storage age is an important indicator of its medicinal value, so it is very significant to accurately identify the storage age of dried tangerine peel. Traditional physical and chemical analysis methods can be used to achieve this goal, but these methods are limited by their operability and convenience. Near infrared (NIR) spectroscopy and machine learning have excellent performance in the rapid detection of food and pharmaceutical samples. This study investigated the novel application of integrating a hand-held NIR spectrometer combined with machine learning to rapidly and accurately identify the storage age of Xinhui dried tangerine peel. Savitzky–Golay convolution smoothing, standard normal variate (SNV), first derivative, and second derivative pretreatments were employed to preprocess spectral data. Principal component analysis (PCA) was used to reduce the spectral data dimensions and obtain the characteristic spectral variables of each sample. Support vector machine (SVM) and k-nearest neighbor were applied to establish the qualitative discriminant models. The SNV-PCA-SVM model discriminant accuracy was 99.60% in the validation set and was 96.50% in the test set, showing excellent generalization performance. The results indicated that the method of using a hand-held NIR spectrometer combined with machine learning could be applied to rapidly identify the storage age of Xinhui dried tangerine peel. This is a promising and economical hand-held NIR spectroscopic method for assuring the dried tangerine peel age on-site.