Research on Quantitative Analytical Model for Determination of Phosmet by Using Surface Enhanced Raman SpectroscopySCIEI北大核心CSCD

Raman spectroscopy combined with surface enhanced technology was adopted for analysis of phosmet pesticide. Continuous wavelet transforms (CWT) and successive projections algorithm (SPA) were used for Raman spectral preprocess and characteristic Raman shifts selection, respectively. Multi-linear regression (MLR) was used for spectral modeling. It is shown that enhanced chips can achieve enhanced Raman spectral signal for low concentration of pesticides. CWT can improve spectral resolution and smoothness, and remove translation error. Characteristic Raman shifts selection method of SPA can improve analytical precision, and simplify modeling variables of MLR CWT-SPA-MLR model can improve correlation coefficient (r) of prediction from 0. 823 to 0. 903, and reduce root mean square error of prediction (RMSEP) from 1. 640 to 1. 122. CWT-SPA-MLR method can be used for constructing analytical models for Raman spectra and has good interpretability and repeatability.     

Year Discrimination of Mild Aroma Chinese Liquors Using Three-Dimensional Fluorescence Spectroscopy Combined with Parallel Factor and Neural NetworkSCIEI北大核心CSCD

Three-dimensional fluorescence spectroscopy coupled with parallel factor analysis and neural network was applied to the year discrimination of mild aroma Chinese liquors. The excitation-emission fluorescence matrices (EEMs) of 120 samples with various years were measured by FLS920 fluorescence spectrometer. The trilinear decomposition of the data array was performed and the loading scores of and the excitation-emission profiles of four components were also obtained. The scores were employed as the inputs of the BP neural networks and the PARAFAC-BP identification model was constructed. 10 samples were collected from 10, 20 and 30 years of liquors respectively, and 30 samples were selected as the test sets. The remaining 90 samples were used as the training sets to build the training model. The year prediction of unknown samples was also carried out, and the prediction accuracy was 90%, 100% and 100%, respectively. Meanwhile, the discrimination analysis method and the multi way partial least squares discriminant analysis were compared, namely PARAFAC-BP and NPLS-DA. The results indicated that parallel factor combined with the neural network (PARAFAC-BP) has higher prediction accuracy. The proposed method can effectively extract the spectral characteristics, and also reduce the dimension of the input variables of neural network. A good year discrimination result was finally achieved.     

Main Components of Xinjiang Lavender Essential Oil Determined by Partial Least Squares and Near Infrared SpectroscopySCIEI北大核心CSCD

This work was undertaken to establish a quantitative analysis model which can rapid determinate the content of linalool, linalyl acetate of Xinjiang lavender essential oil. Totally 165 lavender essential oil samples were measured by using near infrared absorption spectrum(NIR), after analyzing the near infrared spectral absorption peaks of all samples, lavender essential oil have abundant chemical information and the interference of random noise may be relatively low on the spectral intervals of 7100-4 500 cm(-1). Thus, the PLS models was constructed by using this interval for further analysis. 8 abnormal samples were eliminated. Through the clustering method, 157 lavender essential oil samples were divided into 105 calibration set samples and 52 validation set samples. Gas chromatography mass spectrometry (GC-MS) was used as a tool to determine the content of linalool and linalyl acetate in lavender essential oil. Then the matrix was established with the GC-MS raw data of two compounds in combination with the original NIR data. In order to optimize the model, different pretreatment methods were used to preprocess the raw NIR spectral to contrast the spectral filtering effect, after analysizing the quantitative model results of linalool and linalyl acetate, the root mean square error prediction(RMSEP) of orthogonal signal transformation (OSC) was 0.226, 0.558, spectrally, it was the optimum pretreatment method. In addition, forward interval partial least squares (FiPLS) method was used to exclude the wavelength points which has nothing to do with determination composition or present nonlinear correlation, finally 8 spectral intervals totally 160 wavelength points were obtained as the dataset. Combining the data sets which have optimized by OSC-FiPLS with partial least squares(PLS) to establish a rapid quantitative analysis model for determining the content of linalool and linalyl acetate in Xinjiang lavender essential oil, numbers of hidden variables of two components were 8 in the model. The performance of the model was evaluated according to root mean square error of cross-validation (RMSECV) 9 root mean square error of prediction (RMSEP). In the model, RESECV of linalool and linalyl acetate were 0.170 and 0.416, respectively; RMSEP were 0.188 and 0.364. The results indicated that raw data was pretreated by OSC and FiPLS, the NIR-PLS quantitative analysis model with good robustness, high measurement precision; it could quickly determine the content of linalool and linalyl acetate in lavender essential oil. In addition, the model has a favorable prediction ability. The study also provide a new effective method which could rapid quantitative analysis the major components of Xinjiang lavender essential oil.     

基于改进DPSO算法的并行测试任务优化调度研究

并行测试以减少测试时间和降低测试成本的强大优势,已成为当前自动测试系统发展的方向。针对并行自动测试过程中,测试任务调度复杂,难以优化的问题,以PSO算法为基础,通过对问题空间编码的重新定义,并运用交叉、变异算子给出了新的粒子位置的更新公式,提出了一种改进后的DPSO算法。依据并行测试完成时间极限定理,给出了并行测试任务调度的目标函数与约束条件。以某雷达电子装备并行测试系统中三块电路板并行测试为例,对改进的DPSO算法进行了仿真验证,得到了最优调度测试序列。结果表明：与遗传算法相比,改进后的DPSO算法迭代次数更少,寻优性能更好,适用于工程应用。     

Emergence of the sub‐THz central peak at phase transitions in artificial BaTiO3/(Ba,Sr)TiO3 superlattices

A prominent central peak in the sub‐THz frequency range was observed in the Raman spectra of BaTiO₃/(Ba,Sr)TiO₃ (BT/BST) superlattice grown on (001)MgO substrate. Both soft and central mode show an anomaly around 200 K and 280 K, which can be correlated with orthorhombic to monoclinic phase transition of BST and BT, respectively. The observed temperature dependence of the central mode enabled us to explain rather broad temperature dependence of the dielectric permittivity previously observed in BT/BST superlattices. (© 2015 WILEY‐VCH Verlag GmbH &Co. KGaA, Weinheim)     

Composition of oxygen precipitates in Czochralski silicon wafers investigated by STEM with EDX/EELS and FTIR spectroscopy

In this work, we investigated the stoichiometry of oxygen precipitates in Czochralski silicon wafers. The thickness dependence of the Cliff–Lorimer sensitivity factor for the silicon/oxygen system was determined and applied for the investigation of the stoichiometry of oxygen precipitates by EDX. The results show that both plate‐like oxygen precipitates and a transitional form between plate‐like and octahedral precipi‐ tates consist of SiO₂. This was confirmed by EELS low loss spectra where the typical spectrum for amorphous SiO₂ was observed. Moreover, the absorption band of plate‐like precipitates at 1227 cm^–1 was found in the low temperature FTIR spectrum. It was demonstrated that this band can only be simulated by the dielectric constants of amorphous SiO₂. (© 2015 WILEY‐VCH Verlag GmbH &Co. KGaA, Weinheim)     

A combined transient and steady state approach for robust lifetime spectroscopy with micrometer resolution

We present the combination of two complementary micro‐photoluminescence spectroscopic techniques operating in transient and steady state condition, respectively. Introducing the time domain into the well‐established micro‐photoluminescence mapping approach operating under steady state conditions demonstrates a distinct improvement of the robustness and reliability in the determination of charge carrier lifetime measured with micrometer spatial resolution. Lifetimes from 50 ns to above ms are accessible. We elaborate a calibration procedure and apply the combined all‐photoluminescence setup to high‐performance multicrystalline silicon. A lifetime image obtained from the established photoluminescence imaging technique is reconstructed from the microscopic map by considering lateral diffusion and optical blurring, revealing a more detrimental influence of small angle grain boundaries as well as a higher lifetime within grains as may be deduced from the standard imaging technique. (© 2015 WILEY‐VCH Verlag GmbH &Co. KGaA, Weinheim)     

Research on improving the accuracy of near infrared non-invasive hemoglobin detection

To optimize the accuracy of near-infrared non-invasive hemoglobin (Hb) clinical detection, high-performance instrument and prepossessing algorithm have been investigated. A near-infrared spectrophotometric system was constructed adopting InGaAs detector array with 16 pixels and plane grating spectrometer to obtain high signal noise ratio (SNR) spectral data. In our experiment, we applied the device independently to collect spectra data from 91 volunteers’ fingertips non-invasively. Two prediction tests were conducted to verify the effects of preprocessing algorithms improving the accuracy of near-infrared Hb detection and exclude the occasionality of satisfactory results in a single trial. Our non-invasive Hb detection methods were based on partial least squares (PLS). In each test, PLS, MSC coupled with PLS, DOSC coupled with PLS, three methods for non-invasive Hb detection, were analyzed respectively. The results of two trials showed that only DOSC & PLS performed excellently in both predictive ability and stability, obviously better than other two methods. Relative RMSEP was 6.16% in predicting test 1, 6.08% in predicting test 2, almost reaching the requirements of clinical application. It indicates that our independent-developed high-performance instrument and the method DOSC coupled with PLS are promising in non-invasive Hb detection clinical application.     

Structural,electrical and magnetic properties of (Fe,Co) co-doped SnO2 diluted magnetic semiconductor nanostructures

Nanostructures (NSs) of basic composition Sn_1−xFe_x/2Co_x/2O₂ with x=0.00, 0.04, 0.06, 0.08 and 0.1 were synthesized by citrate-gel route and characterized to understand their structural, electrical and magnetic properties. X-ray diffraction and Raman spectroscopy were used to confirm the formation of single phase rutile type tetragonal structure. The crystallite sizes calculated by using Williamson Hall were found to decrease with increasing doping level. In addition to the fundamental Raman peaks of rutile SnO₂, the other three weak Raman peaks at about 505, 537 and 688 cm⁻¹ were also observed. Field emission scanning electron microscopy studies showed the emergence of structural transformation. Electric properties such as dc electrical resistivity as a function of temperature and ac conductivity as a function of frequency were also studied. The variation of dielectric properties with frequency reveals that the dispersion is due to Maxwell–Wagner type of interfacial polarization in general. Hysteresis loops were clearly observed in M–H curves of Fe and Co co-doped SnO₂ NSs. However, pure SnO₂ nanoparticles (NPs) showed paramagnetic behaviour which vanished at higher values of magnetic field. The grain and grain boundary contribution in the conduction process is estimated through complex impedance plot fitted with non-linear least square (NLLS) approach which shows that the role of grain boundaries increases rapidly as compared to the grain volume with the increase of Fe and Co ions in to system.