SnSxSe2-x单晶纳米片的可控制备与表征

锡二硫族化合物可以通过改变硫和硒的含量来连续调控三元合金材料的带隙、载流子浓度等物理化学性质,在电子和光电子器件应用上具有巨大的潜力。本文采用化学气相沉积(CVD)技术可控地制备了不同元素组分的SnS_xSe_2-x(x=0,0.2,0.5,0.8,1.0,1.2,1.5,1.8,2.0)单晶纳米片。采用扫描电子显微镜(SEM)、原子力显微镜(AFM)、能量色散X射线光谱(EDS)、透射电子显微镜(TEM)以及拉曼光谱等手段对SnS_xSe_2-x纳米片进行了综合表征。结果表明本方法成功实现了元素百分比可调的SnS_xSe_2-x单晶纳米片的可控制备。重点研究了依赖于元素百分比的SnS_xSe_2-x的拉曼特征谱,实验结果与基于密度泛函理论(DFT)的第一性原理计算得到的SnS_xSe_2-x的拉曼仿真谱高度吻合,理论计算结果较好地诠释了实验拉曼光谱发生变化的原因。本研究提供了一种元素百分比可调的三元SnS_xSe_2-x单晶纳米片的可控制备方法,同时对锡二硫族化合物的明确、无损识别提供了方案。     

石英晶体板非线性高频振动的拓展伽辽金法分析

针对考虑几何和材料非线性的石英晶体板厚度剪切振动和弯曲振动的方程组,利用扩展伽辽金法对该方程组进行转化和求解,分别获得了强烈耦合的厚度剪切振动模态和弯曲振动模态的频率响应关系,绘制了不同振幅比和不同驱动电压影响下的频率响应曲线图。数值计算结果表明可以选取石英晶片的最佳长厚比尺寸来避免两种模态的强烈耦合。驱动电压的变化将引起石英晶体谐振器厚度剪切振动频率的明显改变,必须将振动频率的漂移值控制在常用压电声波器件的允许值之内。扩展伽辽金法对石英晶体板非线性振动方程组的求解为非线性有限元分析和偏场效应分析奠定了基础。     

Solvent Influence on Absorption Spectra and Tautomeric Equilibria of Symmetric Azomethine-Functionalized Derivatives: Structural Elucidation and Computational Studies

A new series of azomethine-functionalized compounds was synthesized from the condensation of 2-hydroxy-1,3-propanediamine and 2-thienylcarboxaldehydes in the presence of a drying agent. The derivatives were spectroscopically characterized by NMR, LC-MS, UV/Vis, IR and elemental analysis. Variable temperature ¹H-NMR (−60 to +60 °C) was performed to investigate the effect of solvent polarity; the capability of solvent to form H-bond was found to dramatically influencing the tautomerization process of the desired structures. The calculated thermochemical parameters (ΔH₂₉₈, ΔG₂₉₈ and ΔS₂₉₈) at DFT and MP2 levels of theory explained that 3 b exists in equilibrium with two tautomers. The basis of the electronic absorptions was pursued through Time-Dependent Density-Functional Theory (TD-DFT). Analysis of the structural surfaces was inspected and the molecular electrostatic potential (MEP) demonstrated that the three functionalized compounds were relatively analogous in the electronic distributions. Furthermore, the electrophilic and nucleophilic centers lying on the molecular surfaces were probably playing a key-role in stabilizing the compounds through the nonclassical C−H⋅⋅⋅π interactions and hydrogen bonding. The impact of solvent polarity on absorption spectra were investigated via solvatochromic shifts. For instance, compound 3 c displayed a gradual shift of the maximum absorption to the red area when the solvent polarity was increased, recording a 21 nm of bathochromic shift. In contrast, no significant solvent-effect on 3 a and 3 b was observed. The solvation relation was pursued between Gutmann's donicity numbers the experimental λ_max; exhibited almost positive linear performance with a minor oscillation, that ascribe to the possible weak interface between the molecules of solute and designated solvents. The bandgap energy of all products were assessed experimentally using optical absorption spectra following Tauc approach, giving −4.050 ( 3 a ), −3.900 ( 3 b ) and −3.210 ( 3 c ) eV. However, the ΔE were computationally figured out from TD-DFT simulation to be −4.258 ( 3 a ), −4.022 ( 3 b ) and −3.390 ( 3 c ) eV.     

Circularly polarized luminescence based on small organic fluorophores

Circularly polarized luminescence (CPL) has attracted attention as a next-generation light signal because of its carrying more information compared with normal and linearly polarized lights as well as its potential wide application in information fields. Recently, much attention has been paid to small organic molecules-based CPL emitters because of easy synthesis, fine structural modification at molecular level, and tunable wide range emission wavelength. This review highlights the development of small organic molecules-based CPL emitters in the past 5 years (2017–2021). The progress suggests that small organic molecules-based CPL emitters provide a simple and efficient way to generate CPL.     

Application of Machine Learning for Tool Condition Monitoring in Turning

The machining process is primarily used to remove material using cutting tools. Any variation in tool state affects the quality of a finished job and causes disturbances. So, a tool monitoring scheme (TMS) for categorization and supervision of failures has become the utmost priority. To respond, traditional TMS followed by the machine learning (ML) analysis is advocated in this paper. Classification in ML is supervised based learning method wherein the ML algorithm learn from the training data input fed to it and then employ this model to categorize the new datasets for precise prediction of a class and observation. In the current study, investigation on the single point cutting tool is carried out while turning a stainless steel (SS) workpeice on the manual lathe trainer. The vibrations developed during this activity are examined for failure-free and various failure states of a tool. The statistical modeling is then incorporated to trace vital signs from vibration signals. The multiple-binary-rule-based model for categorization is designed using the decision tree. Lastly, various tree-based algorithms are used for the categorization of tool conditions. The Random Forest offered the highest classification accuracy, i.e., 92.6%.

     

Rapid qualitative profiling and quantitative analysis of Juglandis Mandshuricae Cortex and seven flavonoids by ultra-high performance liquid chromatography–quadrupole/orbitrap high-resolution mass spectrometry

Juglandis Mandshuricae Cortex is the bark of Juglans mandshurica Maxim., which has been used as a folk medicine plant in China and India. In this study, an ultra-high performance liquid chromatography–quadrupole/orbitrap high-resolution mass spectrometry method was developed to clarify and quantify the chemical profiling of Juglandis Mandshuricae Cortex rapidly. A total of 113 compounds were characterized. Among them, seven flavonoids were simultaneously quantified in 15 min, including myricetin, myricetrin, taxifolin, kaempferol, quercetin, quercitrin, and naringenin. The method was validated for accuracy, precision, and the limits of detection and quantification. All calibration curves showed a good linear relationship (r > 0.9990) within test ranges. The intra- and inter-day relative standard deviations were less than 2.16%. Accuracy validation showed that the recovery was between 95.6 and 101.3% with relative standard deviation values below 2.85%. The validated method was successfully applied to determine the contents of seven flavones in Juglandis Mandshuricae Cortex from seven sources and the contents of these places were calculated respectively. This method provides a theoretical basis for further developing the medicinal value of Juglandis Mandshuricae Cortex.     

以磷化铁为添加剂沿(111)面生长磷掺杂金刚石大单晶

掺杂是调控金刚石性能的一种重要手段。本文采用温度梯度法,在5.6 GPa、1 312 ℃的条件下,选用Fe₃P作为磷源进行磷掺杂金刚石大单晶的合成。金刚石样品的显微光学照片表明,随着Fe₃P添加比例的增加,金刚石晶体的颜色逐渐变深,包裹体数量逐渐增加,晶形由板状转变为塔状直至骸晶。金刚石晶形的变化表明Fe₃P的添加使生长金刚石的V形区向右偏移,这是Fe₃P改变触媒特性的缘故。红外光谱分析表明,Fe₃P的添加使金刚石晶体中氮含量上升,这说明磷的进入诱使氮原子更容易进入金刚石晶格中。激光拉曼光谱测试表明,随着Fe₃P添加比例的增加,所合成的掺磷金刚石的拉曼峰位变化不大,其半峰全宽(FWHM)值变大,这说明磷的进入使得金刚石晶格畸变增加。XPS测试结果显示,随着Fe₃P添加比例的增加,金刚石晶体中磷相对碳的原子百分含量也会增加,这意味着添加Fe₃P所合成的金刚石晶体中有磷存在。     

微区X射线荧光成像技术在岩心分析中的应用

微区X射线荧光（Micro-XRF）分析技术是通过微小的X射线光束照射样品，对样品进行原位成分观测的无损分析手段之一，具有灵敏度高、速度快和准确性高的特点。采用微区X射线荧光光谱仪（M6 JETSTREAM）对安徽铜陵冬瓜山铜矿床四段岩心样品进行面扫描，分析不同矿层共17种元素区域分布特征、空间分布规律及组合关系等，结果表明：（1）Cu和Fe两种成矿元素高值空间分布区域基本不重叠，S与Fe分布范围高度重叠，关系密切，微量元素Ni，Bi，Pb，Zn，Si，Na与Cu密切相关，而Ti，Al，K与Fe具有弱相关性；（2）垂向上，Fe元素含量随深度增加逐步增大，而Cu元素含量呈降低趋势，其他元素也随深度呈下降趋势；（3）元素分布受石炭纪中期海底喷流沉积成矿作用和岩浆热液成矿作用叠加改造作用明显；（4）该钻孔矿石矿物以磁黄铁矿、黄铜矿和黄铁矿为主，垂向上组合规律明显，脉石矿物以石英、石榴子石和透辉石为主。该技术通过分析元素空间分布规律、相关性以及矿物组合和分配关系等可对元素富集和运移以及对矿床的成矿机制、成因模式等地质环境和地质过程提供新认识和新证据。结合矿床地球化学特征的分布模式，微量元素可作为寻找主矿种的指示元素，为深部找矿提供依据。此外，该技术能作为预分析技术快速筛选出感兴趣的信息和位置，为后期各种更高精度的微区分析提供不同尺度、不同层次的元素分布信息。     

雾化辅助化学气相沉积法氧化镓薄膜生长研究

采用自主设计搭建的雾化辅助化学气相沉积系统设备,开展了Ga₂O₃薄膜制备及其特性研究工作。通过X射线衍射研究了沉积温度、系统沉积压差对Ga₂O₃薄膜结晶质量的影响。结果表明,Ga₂O₃在425~650 ℃温度区间存在物相转换关系。随着沉积温度从425 ℃升高至650 ℃,薄膜结晶分别由非晶态、纯α-Ga₂O₃结晶状态向α-Ga₂O₃、β-Ga₂O₃两相混合结晶状态改变。通过原子力显微镜表征探究了生长温度对Ga₂O₃薄膜表面形貌的影响,从475 ℃升高至650 ℃时,薄膜表面粗糙度由26.8 nm下降至24.8 nm。同时,高分辨X射线衍射仪测试表明475 ℃、5 Pa压差条件下的α-Ga₂O₃薄膜样品半峰全宽仅为190.8″,为高度结晶态的单晶α-Ga₂O₃薄膜材料。