ESCA: Electron Spectroscopy for Chemical Analysis

A substance on which X-rays fall emits photoelectrons and Auger electrons. The energy spectra of the electrons emitted provide information about the electronic structure in the specimen, ranging from the innermost atomic levels and their dependence on the chemical environment to the molecular orbitals of the valence electrons and the band structure in solids. Electron spectra of this nature can now be recorded with high-resolution instruments; their analysis offers new aspects for investigation of chemical composition. The method of electron spectroscopy developed for this purpose, which has now been developed to a high degree of perfection, will be referred to in the following discussion as ESCA (Electron Spectroscopy for Chemical Analysis).     

A New Complex of Europium(II) with edta – Structure and Spectroscopy

A new complex of europium(II) with ethylenediaminetetraacetic acid was obtained by electrochemical reduction. The compound is composed of polymeric chains, guanidinium cations and water molecules. The Eu²⁺ cation is eight‐coordinate (two nitrogen atoms and six carboxylate oxygen atoms), and contrary to europium(III) complexes with edta, does not contain water molecules in the first coordination sphere. Relationships between the coordination mode and IR as well as UV–Vis spectra are discussed.     

Anomalies of the partition coefficient and properties of crystals in the region of low concentrations of an isomorphous admixture. 1. Unusual decomposition of solid solutions of the NaCl—CdCl2 system

Solid solutions NaCl—CdCl₂ were studied in an interval of CdCl₂ concentrations of 0.05—3 mol.% by Raman spectroscopy. The molecular form Na₂CdCl₄ decomposes: Na₂CdCl₄ 2Na⁺ + Cd²⁺ + 2Cl₂ ^– + 2e^–; 2Na + 2e^– 2Na⁰. Free sodium atoms form color centers of crystal (F centers) in the region of jumpwise changing the partition coefficient of CdCl₂ in NaCl (K jump).     

Curing of a maleimide model compound

A monofunctional maleimide-ended model compound was synthesized and purified. The thermal curing of this compound was followed by size exclusion chromatography and the molecular masses of the oligomers formed during the curing reaction were determined by mass spectroscopy. It was found that high molecular mass species were not thermally stable. At high temperature and after enough time, a strong decrease in the polydispersity of the oligomers and a significantly preferential formation of trimer were observed. From ¹³C-NMR characterization, a five membered ring structure was found for the trimer, which explains the thermal stability of this species. © 1995 John Wiley & Sons, Inc.     

Functionalization of the macropolyhedral borate anion cluster [B22H22]: isolation and characterization of the OH and OEt derivatives

Preparation and characterization of the first derivatives of the fused macropolyhedral anion [B₂₂H₂₂]²⁻ are reported. The species [B₂₂H₂₁OH]²⁻ (1) and [B₂₂H₂₁OEt]²⁻ (2) are obtained from workup of the products of the reaction between HgBr₂ and [NBzlEt₃]₂[B₂₂H₂₂]; a cluster involving the conjoining of a closo-B₁₂ icosahedron with a nido-B₁₀ cluster. Washing the products with ethanol followed by thin-layer chromatography allows the isolation of 1 and 2, reproducibly, in yields of 27 and 20%, respectively. The species were characterized by NMR spectroscopy, elemental analysis and X-ray diffraction studies. The crystal structure determinations of the two species identify novel features. Apparently the influence of the O atoms in the ions [B₂₂H₂₁OH]²⁻ and [B₂₂H₂₁OEt]²⁻ results in the lengthening of what was a gunwale B---B connection adjacent to the junction of the two cages such that the distances are 2.180 and 2.230 Å, respectively. These latter are longer than the corresponding distance in the parent species [B₂₂H₂₂]²⁻, which is 2.09 Å; quite long for a normal B---B distance. Thus it is assumed that these B atoms, in 1 and 2, one of which bears the substituent, are not bonded to each other.     

基于激光诱导击穿光谱(LIBS)的煤灰熔点快速检测

炉内结渣是影响火电机组和气化工艺可靠运行的关键因素之一,准确预测灰熔点可以提前调整炉膛出口温度以避免结渣。本论文采用激光诱导击穿光谱（LIBS）采集煤灰样中金属元素的光谱,分别建立煤灰中的金属元素的谱线强度与煤灰熔点的随机森林模型、支持向量机回归模型和线性回归模型,直接预测煤灰熔点温度。采用基于马氏距离(MD)的异常数据剔除算法和基于稀疏矩阵的基线估计与降噪算法（BEADS）,对粉煤灰样的全光谱数据进行了预处理。随机森林模型对粉煤灰熔点的预测平均相对误差（MRE）为54.74%,支持向量机回归模型的预测平均相对误差为60.08%,而线性回归模型的预测平均相对误差达到了9.78%。研究结果表明,线性回归模型对煤灰熔点的预测结果更准确。     

锗元素测定方法综述

锗在国防工业、航空航天和通信等领域中的战略性,锗含量的测定对于保证材料质量和满足国际标准至关重要。本文综述了锗含量测定方法的多种技术,包括分光光度法、原子荧光光谱法、原子吸收光谱法、电感耦合等离子体原子发射光谱法、电感耦合等离子体质谱法以及滴定法。在每个检测方法的介绍中,详细探讨了方法的原理、前处理步骤以及应用范围,并分别总结了各个方法的优势和不足。最后,强调了锗含量测定方法的意义,特别是在满足出口监管和促进科学研究方面的作用。同时对锗元素的测定方法进行了展望,为未来的发展提供了参考方向。     

Spider Silk-Improved Quartz-Enhanced Conductance Spectroscopy for Medical Mask Humidity Sensing

Spider silk is one of the hottest biomaterials researched currently, due to its excellent mechanical properties. This work reports a novel humidity sensing platform based on a spider silk-modified quartz tuning fork (SSM-QTF). Since spider silk is a kind of natural moisture-sensitive material, it does not demand additional sensitization. Quartz-enhanced conductance spectroscopy (QECS) was combined with the SSM-QTF to access humidity sensing sensitively. The results indicate that the resonance frequency of the SSM-QTF decreased monotonously with the ambient humidity. The detection sensitivity of the proposed SSM-QTF sensor was 12.7 ppm at 1 min. The SSM-QTF sensor showed good linearity of ~0.99. Using this sensor, we successfully measured the humidity of disposable medical masks for different periods of wearing time. The results showed that even a 20 min wearing time can lead to a >70% humidity in the mask enclosed space. It is suggested that a disposable medical mask should be changed <2 h.     

Acid–Base Equilibrium and Self-Association in Relation to High Antitumor Activity of Selected Unsymmetrical Bisacridines Established by Extensive Chemometric Analysis

Unsymmetrical bisacridines (UAs) represent a novel class of anticancer agents previously synthesized by our group. Our recent studies have demonstrated their high antitumor potential against multiple cancer cell lines and human tumor xenografts in nude mice. At the cellular level, these compounds affected 3D cancer spheroid growth and their cellular uptake was selectively modulated by quantum dots. UAs were shown to undergo metabolic transformations in vitro and in tumor cells. However, the physicochemical properties of UAs, which could possibly affect their interactions with molecular targets, remain unknown. Therefore, we selected four highly active UAs for the assessment of physicochemical parameters under various pH conditions. We determined the compounds’ pK_a dissociation constants as well as their potential to self-associate. Both parameters were determined by detailed and complex chemometric analysis of UV-Vis spectra supported by nuclear magnetic resonance (NMR) spectroscopy. The obtained results indicate that general molecular properties of UAs in aqueous media, including their protonation state, self-association ratio, and solubility, are strongly pH-dependent, particularly in the physiological pH range of 6 to 8. In conclusion, we describe the detailed physicochemical characteristics of UAs, which might contribute to their selectivity towards tumour cells as opposed to their effect on normal cells.     

The Classification of Rice Blast Resistant Seed Based on Ranman Spectroscopy and SVM

Rice blast is a serious threat to rice yield. Breeding disease-resistant varieties is one of the most economical and effective ways to prevent damage from rice blast. The traditional identification of resistant rice seeds has some shortcoming, such as long possession time, high cost and complex operation. The purpose of this study was to develop an optimal prediction model for determining resistant rice seeds using Ranman spectroscopy. First, the support vector machine (SVM), BP neural network (BP) and probabilistic neural network (PNN) models were initially established on the original spectral data. Second, due to the recognition accuracy of the Raw-SVM model, the running time was fast. The support vector machine model was selected for optimization, and four improved support vector machine models (ABC-SVM (artificial bee colony algorithm, ABC), IABC-SVM (improving the artificial bee colony algorithm, IABC), GSA-SVM (gravity search algorithm, GSA) and GWO-SVM (gray wolf algorithm, GWO)) were used to identify resistant rice seeds. The difference in modeling accuracy and running time between the improved support vector machine model established in feature wavelengths and full wavelengths (200–3202 cm⁻¹) was compared. Finally, five spectral preproccessing algorithms, Savitzky–Golay 1-Der (SGD), Savitzky–Golay Smoothing (SGS), baseline (Base), multivariate scatter correction (MSC) and standard normal variable (SNV), were used to preprocess the original spectra. The random forest algorithm (RF) was used to extract the characteristic wavelengths. After different spectral preproccessing algorithms and the RF feature extraction, the improved support vector machine models were established. The results show that the recognition accuracy of the optimal IABC-SVM model based on the original data was 71%. Among the five spectral preproccessing algorithms, the SNV algorithm’s accuracy was the best. The accuracy of the test set in the IABC-SVM model was 100%, and the running time was 13 s. After SNV algorithms and the RF feature extraction, the classification accuracy of the IABC-SVM model did not decrease, and the running time was shortened to 9 s. This demonstrates the feasibility and effectiveness of IABC in SVM parameter optimization, with higher prediction accuracy and better stability. Therefore, the improved support vector machine model based on Ranman spectroscopy can be applied to the fast and non-destructive identification of resistant rice seeds.