缺陷单层和双层石墨烯的拉曼光谱及其激发光能量色散关系

拉曼光谱作为一种无破坏性、快速且敏锐的测试技术已经成 为表征石墨烯样品和研究其缺陷的最重要的实验手段之一. 本论文用离子注入在单层和双层石墨烯中产生缺陷, 并利用拉曼光谱研究了存在缺陷时单层和双层石墨烯的一阶和二阶拉曼模, 单层石墨烯的D模为双峰结构, 而双层石墨烯的D模具有四峰结构. 同时, 利用四条激光线系统地研究了本征和缺陷单层和双层石墨烯的拉曼峰频率的激发光能量依赖关系, 并基于石墨材料的双共振拉曼散射机理指认了离子注入后样品各拉曼峰的物理根源. 关键词： 石墨烯 缺陷 拉曼光谱 能量色散关系     

基于电化学与热能的耦合关系演算聚合物锂离子动力电池的温度状态及分布

基于电化学-热耦合模型研究聚合物锂离子动力电池放电过程热行为, 分析了放电倍率、冷却条件对电池放电过程的温度变化及分布的影响规律. 结果表明: 3C放电时, 模型计算结果与实测结果的平均偏差为0.57 K, 方差为0.15, 说明模型准确度较高. 电芯的平均生热率在整个放电过程中呈现出增加的趋势, 初期和末期增长较快. 大倍率放电时, 与电流密度的平方呈正比的不可逆热所占的比重较大, 小倍率放电时, 电化学反应可逆热占主导. 改善冷却条件能降低电池放电过程的平均温度, 对流传热过程的表面传热系数为5 W/(m²·K), 1 C, 3 C, 5 C放电结束时, 电芯的平均温升为分别为6.46 K, 17.67 K, 27.53 K, 当对流传热过程的表面传热系数增加至25 W/(m²·K)时, 温升比自然对流条件下相同倍率放电时的温度分别降低了2.91 K, 4.68 K, 5.62 K, 但电芯温度分布的不一致性也会加剧. 关键词： 电化学 耦合 锂离子动力电池 温度分布     

国产六面顶压机多晶种法合成宝石级金刚石单晶

对国产六面顶压机平台下使用多晶种法合成宝石级金刚石单晶进行了系统的研究. 通过合理调整温度梯度法的合成腔体组装, 采用多晶种法, 探索多晶种法金刚石合成的压力和温度区间, 在单个合成腔体内放置3–5颗金刚石晶种, 成功合成出多颗(3–5)优质Ib型宝石级金刚石单晶. 多颗晶种的引入, 单次实验合成的多个金刚石晶体晶形及品质一致; 同时, 晶体的整体生长速度也有明显的增大. 多晶种法金刚石单晶合成的研究, 可以有效地利用腔体空间、提高单次金刚石单晶合成的效率, 解决压机大型化下高温高压资源利用率低的问题; 同时, 为宝石级金刚石单晶商业化生产提供重要的依据. 关键词： 金刚石 国产六面顶 多晶种 温度梯度法     

电场诱导氧化石墨烯的极化动力学特性研究

本文通过外加电场改变氧化石墨烯团簇分子的共振能量,利用激光激发氧化石墨烯产生的共振荧光特性测量氧化石墨烯在电场作用下的极化动力学特性. 发现存在外加电场使得荧光共振峰的半高全宽趋于饱和的时间特性,而不同的氧化石墨烯团簇分子的荧光共振峰的暂态特性同时反映了电场对氧化石墨烯产生定向极化和变形极化的动力学特性. 关键词： 氧化石墨烯 团簇分子 电场 极化动力学     

Investigation of odd-order nonlinear susceptibilities in atomic vapors

We theoretically deduce the macroscopic symmetry constraints for arbitrary odd-order nonlinear susceptibilities in homogeneous media including atomic vapors for the first time. After theoretically calculating the expressions using a semiclassical method, we demonstrate that the expressions for third- and fifth-order nonlinear susceptibilities for undressed and dressed four- and six-wave mixing (FWM and SWM) in atomic vapors satisfy the macroscopic symmetry constraints. We experimentally demonstrate consistence between the macroscopic symmetry constraints and the semiclassical expressions for atomic vapors by observing polarization control of FWM and SWM processes. The experimental results are in reasonable agreement with our theoretical calculations.     

Relationship between Dispersive Surface Tension and Density and Molecular Weight of Solvents and Polymers

The surface and interfacial properties of polymers are important for their applications. Generally, the surface property is quantitatively characterized by the surface tension or surface tension component parameters, which are obtained with the contact angle technique. However, the contact angle technique has an inherent problem, contact angle hysteresis phenomenon, which will result in many incredible surface tension data. In order to find a simple and easy method to estimate the rationality of a surface tension result, the relationship between dispersive surface tension component and density and molecular weight is researched in this work. It is found that for 30 organic solvents, there is a good relationship between the dispersive surface tension r^d and the parameter . In addition, for 12 polymers, when the molecular weight is replaced with the molecular weight of the repeat unit, there is still the same relationship as for small liquids. However, because it is difficult to judge the accuracy of the published dispersive data of the polymers, the found experiential relationship needs further confirmation, requiring more reliable published data.     

A New Equation between Surface Tensions and Solubility Parameters without Molar Volume Parameters Simultaneously Fitting Polymers and Solvents

Both surface tension and solubility parameter are decided by molecular interactions. There are several empirical equations describing their connection. However, at least two limitations exist for them: polymers cannot be treated and only apolar or weakly polar solvents can be fitted. We found when only the dispersive properties were considered, for 37 solvents and 22 polymers, a linear relationship exists between γ ^d and γ/δ^2/3 _d , fitted by a new equation. Compared with the previous equations, the value of the new equation is that most solvents and common polymers could be treated simultaneously. This equation will be of value for estimating the accuracy of reported surface tension data or solubility parameters of polymers.     

Binding Study of Phenformin with Bovine Serum Album Using a Combined Technique of Equilibrium Dialysis with Flow-Injection Chemiluminescence Detection

ABSTRACT

The interaction between phenformin hydrochloride and bovine serum albumin (BSA) was investigated by the methods of chemiluminescence combined with equilibrium dialysis technique. A novel N-bromosuccinimide (NBS)–eosin Y (EY) chemiluminescence (CL) method was established for the determination of phenformin. The mechanism of this chemiluminescence system was proposed. Optimization studies were performed to determine the phenformin. Under the optimal conditions, the CL intensity was linear for a phenformin concentration over the range of 4.6 × 10^?8 to 5.0 × 10^?5 g/mL. The detection limit was 1.5 × 10^?8 g/mL. The data obtained by the present equilibrium dialysis–CL system were analyzed using the Klotz plot and the Scatchard analysis. The results showed that the Klotz plot and the Scatchard plot are linear with good correlation coefficient, indicating that the phenformin has only one type of binding site on BSA. The binding parameters were the number of the binding sites n (1.02) and the estimated association constant K (2.66 × 10⁴ L/mol). The chemiluminescence system combined with equilibrium dialysis developed in this work demonstrated its use for determination of interaction between drug and protein by using relatively simple instrument.     

Research on exponential regularization approach for nonnegative Tucker3 decomposition

Methods of nonnegative tensor factorization (NTF), such as NTF1, NTF2, etc., are extension of nonnegative matrix factorization (NMF) for multi-way data analysis. As an existing NTF method, nonnegative Tucker3 decomposition (NTD) is researched for three-way decomposition in this paper. Firstly, an approach utilizing matrix exponentials built on Tikhonov-type regularization to enforce sparseness is proposed to extract image features instead of exclusively using Tucker tensor decomposition. Meanwhile, updating algorithms, derived from updating rules of NMF, are allowed to efficiently implement updating of mode matrices and core tensors alternatively for accuracy. Then, experimental cases of alternating least squares (ALS) and conjugate nonnegative constraints, called nonnegative alternating least squares (NALS), are studied to remedy data overfitting in computing procedures. Lastly, the proposed method exhibits more advantageous results than other algorithms of Tucker3 for feature extraction, thanks to computer simulations performed in the context of data analysis.     

An Overview of Infrared Spectroscopy Based on Continuous Wavelet Transform Combined with Machine Learning Algorithms: Application to Chinese Medicines,Plant Classification,and Cancer Diagnosis

Abstract

Infrared spectroscopy has been a workhorse technique for materials analysis and can result in positively identifying many different types of material. In recent years there have been reports using wavelet analysis and machine learning algorithms to extract features of Fourier transform infrared spectrometry (FTIR). The machine learning algorithms contain back-propagation neural network (BPNN), radial basis function neural network (RBFNN), and support vector machine (SVM). This article reviews the important advances in FTIR analysis employing a continuous wavelet transform (CWT) and machine learning algorithms, especially in the applications of the method for Chinese medicine identification, plant classification, and cancer diagnosis.