A two-point calibration method for quantifying organic binary mixtures using secondary ion mass spectrometry in the presence of matrix effects

Quantification of the composition of binary mixtures in secondary ion mass spectrometry (SIMS) is required in the analyses of technological materials from organic electronics to drug delivery systems. In some instances, it is found that there is a linear dependence between the composition, expressed as a ratio of component volumes, and the secondary ion intensities, expressed as a ratio of intensities of ions from each component. However, this ideal relationship fails in the presence of matrix effects and linearity is observed only over small compositional ranges, particularly in the dilute limits. In this paper, we assess an empirical method, which introduces a power law dependence between the intensity ratio and the volume fraction ratio. A previously published physical model of the organic matrix effect is employed to test the limits of the method and a mixed system of 3,3′-bis(9-carbazolyl) biphenyl and tris(2-phenylpyridinato)iridium (III) is used to demonstrate the method. This paper introduces a two-point calibration, which determines both the exponent in the power law and the sensitivity factor for the conversion of ion intensity ratio into volume fraction ratio. We demonstrate that this provides significantly improved accuracy, compared with a one-point calibration, over a wide compositional range in SIMS quantification and with a weak dependence on matrix effects. Because the method enables the use of clearly identifiable secondary ions for quantitative purposes and mitigates commonly observed matrix effects in organic materials, the two-point calibration method could be of significant benefit to SIMS analysts.     

Interpretation of TOF-SIMS data based on information entropy of spectra

Time-of-flight secondary ion mass spectrometry (TOF-SIMS), when used for the analysis of complex material samples, typically provides data that are complicated and challenging to understand. Therefore, additional data analysis techniques, such as multivariate analysis, are often required to facilitate the interpretation of TOF-SIMS data. In this study, a new method based on the information entropy (Shannon entropy) is proposed as an indicator of the outline characteristics of an unknown sample, such as changes in the material within the sample and mixing conditions. The Shannon entropy values are calculated using the relative intensity of every secondary ion normalized to the total ion count and reflect the diversity of secondary ions in the spectrum. Mixed samples containing two organic electroluminescence materials of different ratios, multilayers of Irganox 1010, and other organic materials were employed to evaluate the utility of Shannon entropy in the analysis of TOF-SIMS data. The findings demonstrate that the Shannon entropy of a spectrum indicates differences in materials and changes in the conditions of a material in a sample without the need for peak identification or the knowledge of specific peaks corresponding to the materials in the sample.     

A pseudotargeted method based on sequential window acquisition of all theoretical spectra mass spectrometry acquisition and its application in quality assessment of traditional Chinese medicine preparation-Yuanhu Zhitong tablet

Quality control plays a key role in the application of Chinese materia medica, especially in the preparation of traditional Chinese medicine. A pseudotargeted analysis method using an ultra-high-performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry that was operated in the sequential window acquisition of all theoretical spectra mode was proposed to explore the chemical markers of traditional Chinese medicine preparation. Full-scan-based untargeted analysis was applied to extract the target ions. After data preprocessing, 302 target ions were extracted and used for the subsequent sequential window acquisition of all theoretical spectra analyses. The established sequential window acquisition of all theoretical spectra-based pseudotargeted approaches exhibited good repeatability and a wide linear range. The established method was successfully applied to discover analytical markers for the Yuanhu Zhitong tablet. After multivariate statistical analysis, 94 potential markers were identified. Ten markers were annotated by matching accurate m/z and product ion information obtained from previous reports. It is clearly indicated that the pseudotargeted analysis could make a great contribution to the quality assessment of traditional Chinese medicine preparation as a newly emerging technique.     

基于麻雀搜索算法结合深度前馈神经网络的近红外模型转移方法研究

该文提出了一种基于麻雀搜索算法结合深度前馈神经网络（SSA－DFN）的近红外光谱模型转移方法。使用深度前馈神经网络拟合不同仪器采集到的光谱之间的非线性函数映射,并将麻雀搜索算法用于网络各层连接权值和阈值的初始化,通过种群中个体位置的迭代更新,求得连接权值和阈值的最优初始值;通过多次调整深度前馈神经网络模型的超参数,使网络拟合效果趋于最优,最终确定转移函数。为验证方法的有效性,分别从烟叶近红外光谱谱图、主成分投影和预测结果的角度,将SSA－DFN方法与分段直接校正算法（PDS）、典型相关性分析算法（CCA）转移前后的效果进行了对比。结果表明SSA－DFN方法转移后的从机光谱与原主机光谱重合度最高,转移后主、从机总糖、烟碱含量的预测结果差异不显著,预测平均误差从8.32%、9.15%分别降至4.65%、4.82%,预测均方根误差（RMSEP）和决定系数（R2）等指标均优于PDS和CCA,取得了最佳的转移效果,可满足企业需求。结果表明该方法是一种有效的模型转移方法。     

1H-NMR Profiling Shows as Specific Constituents Strongly Affect the International EVOO Blends Characteristics: The Case of the Italian Oil

Considering the growing number of extra virgin olive oil (EVOO) producers in the world, knowing the influence of olive oils with different geographical origins on the characteristics of the final blend becomes an interesting goal. The present work is focused on commercial organic EVOO blends obtained by mixing multiple oils from different geographical origins. These blends have been studied by ¹H-NMR spectroscopy supported by multivariate statistical analysis. Specific characteristics of commercial organic EVOO blends originated by mixing oils from Italy, Tunisia, Portugal, Spain, and Greece were found to be associated with the increasing content of the Italian component. A linear progression of the metabolic profile defined characteristics for the analysed samples—up to a plateau level—was found in relation to the content of the main constituent of the Italian oil, the monocultivar Coratina. The Italian constituent percentage appears to be correlated with the fatty acids (oleic) and the polyphenols (tyrosol, hydroxytyrosol, and derivatives) content as major and minor components respectively. These results, which highlight important economic aspects, also show the utility of ¹H-NMR associated with chemometric analysis as a powerful tool in this field. Mixing oils of different national origins, to obtain blends with specific characteristics, could be profitably controlled by this methodology.     

Drying Effects on Chemical Composition and Antioxidant Activity of Lippia thymoides Essential Oil,a Natural Source of Thymol

Leaves of Lippia thymoides (Verbenaceae) were dried in an oven at 40, 50 and 60 °C and the kinetic of drying and the influence of the drying process on the chemical composition, yield, and DPPH radical scavenging activity of the obtained essential oils were evaluated. The composition of the essential oils was determined with gas chromatography-mass spectrometry and gas chromatography-flame ionization detection analyses. The influence of drying on the chemical composition of the essential oils of L. thymoides was evaluated by multivariate analysis, and their antioxidant activity was investigated via the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. The Midilli model was the most appropriate to describe the behavior of drying kinetic data of L. thymoides leaves. Thymol was the major compound for all analyzed conditions; the maximum content was obtained from fresh leaves (62.78 ± 0.63%). The essential oils showed DPPH radical scavenging activity with an average of 73.10 ± 12.08%, and the fresh leaves showed higher inhibition (89.97 ± 0.31%). This is the first study to evaluate the influence of drying on the chemical composition and antioxidant activity of L. thymoides essential oils rich in thymol.     

Combined Experimental and Multivariate Model Approaches for Glycoalkaloid Quantification in Tomatoes

The intake of tomato glycoalkaloids can exert beneficial effects on human health. For this reason, methods for a rapid quantification of these compounds are required. Most of the methods for α-tomatine and dehydrotomatine quantification are based on chromatographic techniques. However, these techniques require complex and time-consuming sample pre-treatments. In this work, HPLC-ESI-QqQ-MS/MS was used as reference method. Subsequently, multiple linear regression (MLR) and partial least squares regression (PLSR) were employed to create two calibration models for the prediction of the tomatine content from thermogravimetric (TGA) and attenuated total reflectance (ATR) infrared spectroscopy (IR) analyses. These two fast techniques were proven to be suitable and effective in alkaloid quantification (R² = 0.998 and 0.840, respectively), achieving low errors (0.11 and 0.27%, respectively) with the reference technique.     

基于非同步替代光谱定标的地表下垫面影响分析

对760nm附近的氧气吸收带,选用植被、枯萎植被、人工地物、沙地和雪地五种典型地表类型,基于模拟数据进行非同步替代光谱定标方法的误差分析,比较不同地表类型得到的光谱定标准确度,为高光谱成像仪的非同步替代光谱定标提供定标图像选择策略.结果表明:运用两种光谱匹配方法——光谱角度匹配和欧氏距离法得到的定标误差基本一致;730~800nm的地表反射率曲线标准差在0.05nm以内时,定标误差集中在±0.5nm范围内;人工地物类型中个别地物如橄榄绿光泽涂料和植被大面积覆盖的图像数据不适合用于非同步替代光谱定标.     

光栅投影相位法系统模型及标定方法

本文针对传统投影光栅相位法的光学三角法模型进行了改进,采用直入射光路并配合使用一种简便易行的标定方法,只需使用相移公式求取相位差,而不会引入与系统几何位置关系有关的量,简化了求取高度矩阵的要求。实验结果表明,新系统模型精度良好,测量误差为0.107 mm。采用该模型和标定方法可以克服传统方法系统模型的局限性,最大限度减少误差源并提高抗干扰性。     

天文/卫星组合点校捷联惯性导航系统算法研究

捷联式惯性导航系统通常采用卫星导航系统的位置、速度信息对惯导解算误差进行校正,但对于水下载体惯性导航系统而言,由于只能获得点位置信息,对惯导的校正精度以及校正参量有限。针对上述问题,提出了基于天文/卫星组合校正捷联式惯导技术,通过卫星精确定位信息和天文快速观测信息,全面修正惯导系统误差、提高导航精度。仿真结果表明,基于天文/卫星组合校正算法对惯导进行校正,相对于传统校正算法精度可提高约50%。