无标样XRD定量相分析的计算

Zevin 首次提出了无标 X 射线定量相分析,解决了有标法试样制备的困难。但仍有局限性,故提出普适新方法。在含有几个相的样品中,如果有 m 个相未知 n-m 个相的重量分数可以用别的方法测得或已知,而且能够提供互相独立的 m 个样品,根据 Klug 的定量 X 线分析方程:     

自控远红外消化—氨电极法快速测定植物中全氮量

植物中全氮的测定,常用半微量蒸馏法和扩散吸收法,前者繁琐冗长,难以进行大批量样品分析;后者扩散时间长,并往往因密封不好及胶水沾污而造成分析误差,甚至分析失败。此外,所采用的常规消化技术大多手续繁杂,一次仅能至多处理十几个试样,难以适应大批量样品分析的需要。氨气敏电极应用于土壤,植物中全氮量测定,国内外已有不少报道。本文采用自控远红外消煮装置消化处理植物样品,单机一次可以同时处理40个试样,使用 WL—15     

纳米CuAl2O4粉体的合成工艺条件及其表征

通过化学共沉淀法制备了尖晶石型纳米CuAl2O4晶体,用正交试验设计方法研究了原料配比、溶剂用量、煅烧温度、煅烧时间等四种因素对CuAl2O4形成的影响,结果表明,煅烧温度是影响CuAl2O4形成的主要因素,溶剂用量次之.确定了共沉淀法制备CuAl2O4纳米粉体的最佳制备工艺条件为原料配比2∶1,溶剂用量120 mL,煅烧温度900℃,煅烧时间3h.用TG-DTA法确定前驱体热分解过程及煅烧温度.用XRD分析了L9(34)实验中9组样品的晶相,比较了各组样品中CuAl2O4晶相形成的相对数量.用TEM对最佳制备条件下制备的样品的表面形貌进行了表征.     

基于双全站仪的中子谱仪样品台位姿标定方法

中子谱仪样品台是实现样品上待测量点精确移动到衍射点并实现待测量矢量与Q散射矢量对齐的功能,从而进行残余应力测量。提出了一种基于双全站仪的位姿标定方案来实现样品台的以上功能,采用双全站仪测量系统和便携式激光扫描臂系统对各个坐标系进行标定。分别设计了样品坐标系、四轴样品台坐标系、中子谱仪衍射坐标系和全站仪坐标系的标定方案,并精确地设计了基于基准球的标定方案,由刚体变换法求得样品坐标系和全站仪坐标系之间的位姿转换矩阵,对样品上待测量点进行运动求解得到样品台的运动指令,并进行了实验验证。实验结果表明该方案能实现待测量点精确移动到衍射点,使待测量矢量与Q散射矢量对齐。     

可预置可逆式步进电机驱动器

<正> 在许多自动化设备中都要使用步进电机,因为步进电机给很多测量带来极大便利。例如,在一些物理实验中,由于某种条件的限制,被测试的样品远离实际操作者,特别是在核物理的一些实验中,待测样品被放在反应堆或加速器等有放射性的场所里,实验者不能直接靠近试样。试样的转动、平移、升降等,可借助步进电机加一个驱动装置来完成,试样安装在带步进电机的试验架上,用长电缆将电机与驱动器连接起来,实验者就可在远离(一般几十米至上百米)试样     

低频液体表面波衍射光斑分布研究

为了进一步研究水下低频声源特征,本研究基于液体表面波的声光衍射原理,对低频声源在不同入水深度位置处的液体表面波进行研究。通过建立精准的水下定位装置系统,改变声源在水下的位置,实验中可观察到不同光强度的衍射图样,图样清晰且稳定,呈明暗相间状。理论上分析了表面波的光衍射效应,得到了衍射光斑空间分布呈不对称性。实验结果表明,随着声源入水深度的逐渐增加,衍射光斑强度逐渐减少,最高衍射级次逐渐减少,衍射光斑尺寸逐渐减小,且衍射光斑位置呈不对称分布。实验结果与理论分析相吻合。     

径向冲击中心直裂纹巴西圆盘的复合型动态断裂分析

中心直裂纹巴西圆盘试样可以用于脆性材料在纯Ⅰ型、纯Ⅱ型以及Ⅰ-Ⅱ复合型载荷下的动态断裂韧度的测试.通过改变径向冲击的加载角θ(加载方向相对于裂纹的倾斜角),可以方便地实现不同的Ⅰ、Ⅱ型动态断裂实验.本文用有限元软件ANSYS对试样进行动态复合型断裂模拟分析,研究了不同载荷、不同材料以及不同试样尺寸对动态无量纲应力强度因子的影响,得到了纯Ⅱ型加载所对应的加载角θⅡ的近似计算公式.对于在斜坡载荷作用下的复合型断裂,Ⅰ、Ⅱ型应力强度因子具有相似的时间历程曲线,其比值逐渐趋近于一个常数.本文给出了不同无量纲裂纹长度的试样在不同加载角下对应的Ⅰ、Ⅱ型无量纲应力强度因子的比值KⅠ(t)/KⅡ(t)(该比值称为复合比),利用该复合比,可以通过应变能密度因子准则求出试样的起裂角β0,得到的结果与文献给出的试验结果吻合得很好.     

X射线定量物相分析程序

选用１１种常用的方法，编成了通用的Ｘ射线定量物相分析程序，此程序可以大大提高分析的精度与速率。在无标样法中，样品数可以大于物相数，采用多元线性回归法求解，以减少误差。整个软件人机对话清楚。而且全部进行了汉化，操作使用极为方便。     

用硝酸根电极作硝酸盐及亚硝酸盐的联合测定

在卫生分析中,硝酸盐及亚硝酸盐常共存于同一试样,如采用离子选择电极法测硝酸盐,则亚硝酸盐将干扰测定,作者提出将样品蒸馏处理可免除干扰,其蒸出液经氧化后,用同一支电极可测出试样中的亚硝酸盐,由此实现了两盐的联合测定。测试时,采用不同     

基于电导法的原油含水率测量改进方法

基于电导法开展原油含水率测量具有硬件结构简单,系统稳定可靠及测量准确等特点。根据Maxwell模型原理,电导法测量原油含水率需要获知纯水相电导率。然而,开展井下实时含水率测量时,纯水相电导率无法直接测得,直接使用预设的纯水相电导率无法真实得出井下原油的实时含水率。鉴于此,本文根据原油的馏分性质,通过测量不同温度下两组油水,混合相的电导率值并进一步推导得出原油含水率表达式,规避纯水相电导率测试问题及预设纯水相电导率不精确问题,实现对现有原油含水率测量方法的改进。基于ARM Cortex M4处理器及多种传感器测量技术开展了实验研究.实验结果表明,当测量含水率大于90％的油水两相流时,误差可在２％以内。当测量纯水相矿化度在7g/L以内的油水两相流时,含水率误差基本不受矿化度影响。实验结果验证了优化方法理论的有效性,具有实际应用的可行性。     

Contribution of the Rietveld method to non-stoichiometric phase modeling. Part II: α-Tl5Te3 and μ Nb-Ni as experimental examples

Two detailed examples are considered to show the ability of powder diffraction data analyzed with the Rietveld method to get insight into the detailed structure of non-stoichiometric phases. Both the γ-phase in Tl-Te system and μ-phase in Nb-Ni system were investigated as a function of composition across their whole homogeneity domain. In the case of the γ Tl-Te phase, the excess Tl relative to the stoichiometric composition is accommodated by Tl substitution on one of the two Te sites. In the μ Nb-Ni, three of the five sites of the structure are partially disordered for all the compositions studied. The results are analyzed in view of Calphad modeling of both phases.     

基于句类特征的作者写作风格分类研究

不同作家的作品有自己的特点,这些特点体现在词汇、句型、修辞手法等各个方面,尝试使用句类特征进行作者写作风格分类,进一步可以用于作者的识别。利用向量空间模型,以句类作为特征,并通过混合句类分解等技术对句类向量空间降维,使用itc算法对特征项进行权重计算,KNN算法进行分类并利用集成判决技术,形成作者写作风格分类器。本分类器的性能在近现代小说的按作者写作风格的分类和鉴别方面的性能是可以接受的,并有进一步提升的可能。     

Analysis of networks of queues via projection techniques

In this research, the author deviates from the conventional traffic models and approaches. The author uses a traffic model proposed by Cruz (1990). In Cruz's model, the rate functions of traffic sources are assumed to satisfy some linear “burstiness constraints”. Such traffic models can be used to describe a class of rate-based flow-controlled sources. A state vector is defined to describe the queueing system. The author divides the operation of the studied queueing system into multiple phases. For each phase, the author writes a system equation to describe completely the behavior of this studied queueing system. The author then proposes the iterative feasible set method to identify the feasible region of the state vector using some linear programming techniques and other existing theorems regarding the projection of convex sets into a space with a lower dimension. Using the above technique, the author studied the performance of three routing schemes in a simple dynamic routing problem, namely the route to shortest rule, the fixed routing rule and the bounded linear rule. The author first identified the feasible regions of a defined state vector for each routing scheme using the proposed method. From the identified feasible regions, the author then analyzed the extremal performance of these routing schemes and compared their performances     

A computational experiment on deducing phase diagrams from spatial thermodynamic data using machine learning techniques

Derivation and discovery of physical dynamics inherent in big data is one of the most major purposes of machine learning (ML) in the field of modern natural science. In the materials science, phase diagrams are often called as “road maps” to perfectly understand the conditions for phase formation and/or transformation in any material system caused by the associated thermodynamics. In this paper, we report a numerical experiment investigating whether the underlying thermodynamics can be derived from the big data constructed of local spatial composition and phase distribution data along with the help of ML. The artificial data analysed have been created assuming a steel composition based on the calculation phase diagram (CALPHAD) thermodynamics combined with the order-statistics-based sampling model. The hypothetical procedures of data acquisition assumed in this numerical experiment are as follows; (i) obtaining local analysis data on the composition and phase distribution in the same observation area using instruments such as electron probe micro analyser (EPMA) and electron backscattering diffraction (EBSD), and (ii) training the classification model based on a ML algorithm with compositional data as input and the phase data as output. The accuracies of the reconstructed phase diagrams have been estimated for three ML algorithms, i.e. support vector machine (SVM), random forest, and multilayer perceptron (MLP). The phase diagrams predicted using SVM and MLP are found to be adequately consistent with those of the CALPHAD method. We have also investigated the regression performance of the continuous data involved in the CALPHAD thermodynamics, such as the phase fractions of body-centred cubic, face-centred cubic, and cementite phases. Compared with the ML algorithms, the CALPHAD method is found to show superior predictive performance since it is based on the sophisticated physical model.     

Musical performance analysis in terms of emotions it evokes

Finding pieces with a similar emotional distribution throughout the same composition was the aim of this work. A comparative analysis of musical performances by using emotion tracking was proposed. A dimensional approach of dynamic music emotion recognition was used in the analysis. Music data annotation and regressor training were done. Values of arousal and valence, predicted by regressors, were used to compare performances. The obtained results confirm the validity of the assumption that tracking and analyzing the values of arousal and valence over time in different performances of the same composition can be used to indicate their similarities. Detailed results of analyzing different performances of Prelude No.1 by Frédéric Chopin were presented. They enabled to find the most similar performances to the performance by Arthur Rubinstein, for example. The author found which performances of the same composition were closer to each other and which were quite distant in terms of the shaping of arousal and valence over time. The presented method gives access to knowledge on the shaping of emotions by a performer, which had previously been available only to music professionals.     

Synthesis of nanostructural ZnO using hydrothermal method for dye-sensitized solar cells

ZnO nanocrystals with different morphologies were successful synthesized by a simple hydrothermal method combined with and without hexadecyl trimethyl ammonium bromide(CTAB).The phases and morphologies of the products were measured using X-ray diffraction(XRD),scanning electron microscopy(SEM),and transmission electron microscopy(TEM),respectively.The results indicated that the ZnO nanocrystals with different morphologies were of hexagonal wurtzite structure.ZnO nanorods were obtained without using CTAB,and...     

Contribution of the Rietveld method to non-stoichiometric phase modeling. Part I: generalities

While being the most efficient way of analyzing a powder diffraction diagram for evidencing an additional phase, refining lattice parameters and performing quantitative phase analysis, the Rietveld method is also able to perform structure refinement including accurate determination of atomic positions and atom occupancies at the different sites. Owing to technological improvements of both powder diffractometers, and Rietveld analysis software, the method is now able to compete with single crystal analysis. It is actually the only alternative when single crystals do not exist or when no single crystal diffractometer is available. The Rietveld method makes possible the determination of vacancy ratio or relative occupancies when atoms of different kinds can occupy the same sites. It allows the measurement of the order parameter in partially ordered structures and the determination of the mechanism for accommodating the excess or deficient atoms in non-stoichiometric phases. This makes the Rietveld method the ideal tool to use in conjunction with the sublattice model especially if experimental site fractions can be taken into account in phase diagram assessment software. Powder diffraction associated with Rietveld analysis should therefore be widely used as an efficient experimental tool for thermodynamic optimization.     

A monolithic approach to automated composition of semantic web services with the Event Calculus

In this paper, a web service composition and execution framework is presented for semantically -annotated web services. A monolithic approach to automated web service composition and execution problem is chosen, which provides some benefits by separating composition and execution phases. An AI planning method using a logical formalism, namely Abductive Event Calculus, is chosen for the composition phase. This formalism allows one to generate a narrative of actions and temporal orderings using abductive planning techniques given a goal. The functional properties of services, namely input/output/precondition/effects (IOPE) are taken into consideration in the composition phase and non-functional properties, namely Quality of Service (QoS) parameters are used in selecting the most appropriate solution to be executed. The repository of OWL-S semantic web services are translated to the Event Calculus axioms and the resulting plans found by the Abductive Event Calculus Planner are converted to graphs. These graphs can be sorted according to a score calculated using the defined quality of service parameters of the atomic services in the composition to determine the optimal solution. The selected graph is converted to an OWL-S file which is executed consequently.     

Function-to-structure transformation in conceptual design: An associative memory-based paradigm

The three most important phases of design are (1) conceptual phase; (2) configuration phase; and (3) parameterization phase. The second and the third phases are well researched. However, little work has been done in the conceptual design phase. In this paper the author deals with a different way of modeling the conceptual design phase. In this research the paradigm of function-to-structure transformation is used. One of the most difficult ideas of design is that of modeling the function-to-structure transformation process. The current research shows that the function-to-structure transformation is accomplished through a process of association. Whenever a designer is faced with finding a solution to a new functional requirement, the designer tries to associate this new function with known functions from his/her memory through a process of association. After having identified the closest function, an associated structure can be retrieved and mutated to form the design solution for the new problem. In essence, the designer associates the new functions with known functions and will try to retrieve the closest and most general design solution from his/her memory through a process of association. The author models the human associative memory through artificial neural networks (ANN) with back-propagation. A simple yet illustrative example of cups and containers is selected to model the function-to-structure transformation process at the conceptual design phase. In this paper the implementation aspects of the ANN are clearly explained. The robustness of the ANN through different schemes is also explored. A performance analysisvia simulation by varying the nodes of the hidden layer is also carried out.