NICKEL-COBALT SOLID SOLUTION AND ITS APPLICATIONS AS CATALYSTS FOR CARBON DIOXIDE REFORMING OF METHANE

Global warming issue becomes more significant to human beings and other organisms on the earth. Among many greenhouse gases, carbon dioxide (CO2) has the largest contribution to global warming. To find an effective way to utilize the greenhouse gas is urgent. It is the best way to convert CO2 to useful compounds. CO2 reforming of methane is an attractive process to convert CO2 and methane into synthesis gas (CO/H2), which can be used as a feedstock for gasoline, methanol, and other hydrocarbons. Nickel and cobalt were found to have good activity for CO2 reforming. However, they have a poor stability due to carbon deposition. This research developed efficient Ni-Co solid solution catalysts with excellent activities and high stability for CO2 reforming of methane. First, the structure of binary oxide solid solution of nickel and cobalt was investigated. It was found that while the calcination of Ni(NO3)2 and Co(NO3)2 mixture with 1:1 molar ratio at a high temperature above 800 oC generated NiO-CoO solid solution, only Ni3O4-Co3O4 solid solution was observed after the calcination at a low temperature of 500 oC. Furthermore, if the calcination was carried out at a medium temperature arranged from 600 to 700 oC, both NiO-CoO and Ni3O4-Co3O4 solid solutions can be formed. This occurred because Co3O4 can induce the formation of Ni3O4, whereas NiO can stabilize CoO. In addition, the lattice parameter of Ni3O4, which was predicted by using Vegard’s Law, is 8.2054 Å. As a very important part of this dissertation, Ni-Co solid solution was evaluated as catalysts for CO2 reforming of methane. It was revealed that nickel-cobalt solid solution showed excellent catalytic performance and high stability for CO2 reforming of methane. However, the stability of Ni-Co solid solution catalysts is strongly dependent on their composition and preparation condition. The optimum composition is 50%Ni-50%Co. Furthermore, the structure of Ni-Co catalysts was characterized by XRD, Vvis, TPR, TPD, BET, AES, TEM, XANES and EXAFS. The relationship between the structure and the catalytic performance was established: (1) The reduced NiO-CoO solid solution possesses better catalytic performance and stability than the reduced Ni3O4-Co3O4 solid solution. (2) Ni is richer on surface in Ni-Co catalysts. And (3) the reduction of Ni-Co-O solid solution generated two types of particles, small and large particles. The small ones are dispersed on large ones as catalytic component.

SYNTHESIS OF GRAPHENE AND ITS APPLICATIONS FOR DYE-SENSITIZED SOLAR CELLS

Graphene, which is a two-dimensional carbon material, exhibits unique properties that promise its potential applications in photovoltaic devices. Dye-sensitized solar cell (DSSC) is a representative of the third generation photovoltaic devices. Therefore, it is important to synthesize graphene with special structures, which possess excellent properties for dye-sensitized solar cells. This dissertation research was focused on (1) the effect of oxygen content on the structure of graphite oxide, (2) the stability of graphene oxide solution, (3) the application of graphene precipitate from graphene oxide solution as counter electrode for DSSCs, (4) the development of a novel synthesis method for the three-dimensional graphene with honeycomb-like structure, and (5) the exploration of honeycomb structured graphene (HSG) as counter electrodes for DSSCs. Graphite oxide is a crucial precursor to synthesize graphene sheets via chemical exfoliation method. The relationship between the oxygen content and the structures of graphite oxides was still not explored. In this research, the oxygen content of graphite oxide is tuned by changing the oxidation time and the effect of oxygen content on the structure of graphite oxide was evaluated. It has been found that the saturated ratio of oxygen to carbon is 0.47. The types of functional groups in graphite oxides, which are epoxy, hydroxyl, and carboxylgroups, are independent of oxygen content. However, the interplanar space and BET surface area of graphite oxide linearly increases with increasing O/C ratio. Graphene oxide (GO) can easily dissolve in water to form a stable homogeneous solution, which can be used to fabricate graphene films and graphene based composites. This work is the first research to evaluate the stability of graphene oxide solution. It has been found that the introduction of strong electrolytes (HCl, LiOH, LiCl) into GO solution can cause GO precipitation. This indicates that the electrostatic repulsion plays a critical role in stabilizing aqueous GO solution. Furthermore, the HCl-induced GO precipitation is a feasible approach to deposit GO sheets on a substrate as a Pt-free counter electrode for a dye-sensitized solar cell (DSSC), which exhibited 1.65% of power conversion efficiency. To explore broad and practical applications, large-scale synthesis with controllable integration of individual graphene sheets is essential. A novel strategy for the synthesis of graphene sheets with three-dimensional (3D) Honeycomb-like structure has been invented in this project based on a simple and novel chemical reaction (Li2O and CO to graphene and Li2CO3). The simultaneous formation of Li2CO3 with graphene not only can isolate graphene sheets from each other to prevent graphite formation during the process, but also determine the locally curved shape of graphene sheets. After removing Li2CO3, 3D graphene sheets with a honeycomb-like structure were obtained. This would be the first approach to synthesize 3D graphene sheets with a controllable shape. Furthermore, it has been demonstrated that the 3D Honeycomb-Structured Graphene (HSG) possesses excellent electrical conductivity and high catalytic activity. As a result, DSSCs with HSG counter electrodes exhibit energy conversion efficiency as high as 7.8%, which is comparable to that of an expensive noble Pt electrode.

3D printing and its applications

Eine zunehmende Anzahl von Artikeln in Publikumszeitschriften und Journalen rückt die direkte Herstellung von Bauteilen und Figuren immer mehr in das Bewusstsein einer breiten Öffentlichkeit. Leider ergibt sich nur selten ein einigermaßen vollständiges Bild davon, wie und in welchen Lebensbereichen diese Techniken unseren Alltag verändern werden. Das liegt auch daran, dass die meisten Artikel sehr technisch geprägt sind und sich nur punktuell auf Beispiele stützen. Dieser Beitrag geht von den Bedürfnissen der Menschen aus, wie sie z.B. in der Maslow’schen Bedürfnispyramide strukturiert dargestellt sind und unterstreicht dadurch, dass 3D Printing (oder Additive Manufacturing resp. Rapid Prototyping) bereits alle Lebensbereiche erfasst hat und im Begriff ist, viele davon zu revolutionieren.

New methods for the estimation of Takagi-Sugeno model based extended Kalman filter and its applications to optimal control for nonlinear systems

This paper describes new approaches to improve the local and global approximation (matching) and modeling capability of Takagi–Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy and fast convergence. The main problem encountered is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the application of the T-S method because this type of membership function has been widely used during the last 2 decades in the stability, controller design of fuzzy systems and is popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S identification method with optimized performance in approximating nonlinear functions. We propose a noniterative method through weighting of parameters approach and an iterative algorithm by applying the extended Kalman filter, based on the same idea of parameters’ weighting. We show that the Kalman filter is an effective tool in the identification of T-S fuzzy model. A fuzzy controller based linear quadratic regulator is proposed in order to show the effectiveness of the estimation method developed here in control applications. An illustrative example of an inverted pendulum is chosen to evaluate the robustness and remarkable performance of the proposed method locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity, and generality of the algorithm. An illustrative example is chosen to evaluate the robustness. In this paper, we prove that these algorithms converge very fast, thereby making them very practical to use.

Abstract specialization and its applications

The aim of program specialization is to optimize programs by exploiting certain knowledge about the context in which the program will execute. There exist many program manipulation techniques which allow specializing the program in different ways. Among them, one of the best known techniques is partial evaluation, often referred to simply as program specialization, which optimizes programs by specializing them for (partially) known input data. In this work we describe abstract specialization, a technique whose main features are: (1) specialization is performed with respect to "abstract" valúes rather than "concrete" ones, and (2) abstract interpretation rather than standard interpretation of the program is used in order to propágate information about execution states. The concept of abstract specialization is at the heart of the specialization system in CiaoPP, the Ciao system preprocessor. In this paper we present a unifying view of the different specialization techniques used in CiaoPP and discuss their potential applications by means of examples. The applications discussed include program parallelization, optimization of dynamic scheduling (concurreney), and integration of partial evaluation techniques.

Numerical Error Prediction and its applications in CFD using tau-estimation

Nowadays, Computational Fluid Dynamics (CFD) solvers are widely used within the industry to model fluid flow phenomenons. Several fluid flow model equations have been employed in the last decades to simulate and predict forces acting, for example, on different aircraft configurations. Computational time and accuracy are strongly dependent on the fluid flow model equation and the spatial dimension of the problem considered. While simple models based on perfect flows, like panel methods or potential flow models can be very fast to solve, they usually suffer from a poor accuracy in order to simulate real flows (transonic, viscous). On the other hand, more complex models such as the full Navier- Stokes equations provide high fidelity predictions but at a much higher computational cost. Thus, a good compromise between accuracy and computational time has to be fixed for engineering applications. A discretisation technique widely used within the industry is the so-called Finite Volume approach on unstructured meshes. This technique spatially discretises the flow motion equations onto a set of elements which form a mesh, a discrete representation of the continuous domain. Using this approach, for a given flow model equation, the accuracy and computational time mainly depend on the distribution of nodes forming the mesh. Therefore, a good compromise between accuracy and computational time might be obtained by carefully defining the mesh. However, defining an optimal mesh for complex flows and geometries requires a very high level expertize in fluid mechanics and numerical analysis, and in most cases a simple guess of regions of the computational domain which might affect the most the accuracy is impossible. Thus, it is desirable to have an automatized remeshing tool, which is more flexible with unstructured meshes than its structured counterpart. However, adaptive methods currently in use still have an opened question: how to efficiently drive the adaptation ? Pioneering sensors based on flow features generally suffer from a lack of reliability, so in the last decade more effort has been made in developing numerical error-based sensors, like for instance the adjoint-based adaptation sensors. While very efficient at adapting meshes for a given functional output, the latter method is very expensive as it requires to solve a dual set of equations and computes the sensor on an embedded mesh. Therefore, it would be desirable to develop a more affordable numerical error estimation method. The current work aims at estimating the truncation error, which arises when discretising a partial differential equation. These are the higher order terms neglected in the construction of the numerical scheme. The truncation error provides very useful information as it is strongly related to the flow model equation and its discretisation. On one hand, it is a very reliable measure of the quality of the mesh, therefore very useful in order to drive a mesh adaptation procedure. On the other hand, it is strongly linked to the flow model equation, so that a careful estimation actually gives information on how well a given equation is solved, which may be useful in the context of _ -extrapolation or zonal modelling. The following work is organized as follows: Chap. 1 contains a short review of mesh adaptation techniques as well as numerical error prediction. In the first section, Sec. 1.1, the basic refinement strategies are reviewed and the main contribution to structured and unstructured mesh adaptation are presented. Sec. 1.2 introduces the definitions of errors encountered when solving Computational Fluid Dynamics problems and reviews the most common approaches to predict them. Chap. 2 is devoted to the mathematical formulation of truncation error estimation in the context of finite volume methodology, as well as a complete verification procedure. Several features are studied, such as the influence of grid non-uniformities, non-linearity, boundary conditions and non-converged numerical solutions. This verification part has been submitted and accepted for publication in the Journal of Computational Physics. Chap. 3 presents a mesh adaptation algorithm based on truncation error estimates and compares the results to a feature-based and an adjoint-based sensor (in collaboration with Jorge Ponsín, INTA). Two- and three-dimensional cases relevant for validation in the aeronautical industry are considered. This part has been submitted and accepted in the AIAA Journal. An extension to Reynolds Averaged Navier- Stokes equations is also included, where _ -estimation-based mesh adaptation and _ -extrapolation are applied to viscous wing profiles. The latter has been submitted in the Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering. Keywords: mesh adaptation, numerical error prediction, finite volume Hoy en día, la Dinámica de Fluidos Computacional (CFD) es ampliamente utilizada dentro de la industria para obtener información sobre fenómenos fluidos. La Dinámica de Fluidos Computacional considera distintas modelizaciones de las ecuaciones fluidas (Potencial, Euler, Navier-Stokes, etc) para simular y predecir las fuerzas que actúan, por ejemplo, sobre una configuración de aeronave. El tiempo de cálculo y la precisión en la solución depende en gran medida de los modelos utilizados, así como de la dimensión espacial del problema considerado. Mientras que modelos simples basados en flujos perfectos, como modelos de flujos potenciales, se pueden resolver rápidamente, por lo general aducen de una baja precisión a la hora de simular flujos reales (viscosos, transónicos, etc). Por otro lado, modelos más complejos tales como el conjunto de ecuaciones de Navier-Stokes proporcionan predicciones de alta fidelidad, a expensas de un coste computacional mucho más elevado. Por lo tanto, en términos de aplicaciones de ingeniería se debe fijar un buen compromiso entre precisión y tiempo de cálculo. Una técnica de discretización ampliamente utilizada en la industria es el método de los Volúmenes Finitos en mallas no estructuradas. Esta técnica discretiza espacialmente las ecuaciones del movimiento del flujo sobre un conjunto de elementos que forman una malla, una representación discreta del dominio continuo. Utilizando este enfoque, para una ecuación de flujo dado, la precisión y el tiempo computacional dependen principalmente de la distribución de los nodos que forman la malla. Por consiguiente, un buen compromiso entre precisión y tiempo de cálculo se podría obtener definiendo cuidadosamente la malla, concentrando sus elementos en aquellas zonas donde sea estrictamente necesario. Sin embargo, la definición de una malla óptima para corrientes y geometrías complejas requiere un nivel muy alto de experiencia en la mecánica de fluidos y el análisis numérico, así como un conocimiento previo de la solución. Aspecto que en la mayoría de los casos no está disponible. Por tanto, es deseable tener una herramienta que permita adaptar los elementos de malla de forma automática, acorde a la solución fluida (remallado). Esta herramienta es generalmente más flexible en mallas no estructuradas que con su homóloga estructurada. No obstante, los métodos de adaptación actualmente en uso todavía dejan una pregunta abierta: cómo conducir de manera eficiente la adaptación. Sensores pioneros basados en las características del flujo en general, adolecen de una falta de fiabilidad, por lo que en la última década se han realizado grandes esfuerzos en el desarrollo numérico de sensores basados en el error, como por ejemplo los sensores basados en el adjunto. A pesar de ser muy eficientes en la adaptación de mallas para un determinado funcional, este último método resulta muy costoso, pues requiere resolver un doble conjunto de ecuaciones: la solución y su adjunta. Por tanto, es deseable desarrollar un método numérico de estimación de error más asequible. El presente trabajo tiene como objetivo estimar el error local de truncación, que aparece cuando se discretiza una ecuación en derivadas parciales. Estos son los términos de orden superior olvidados en la construcción del esquema numérico. El error de truncación proporciona una información muy útil sobre la solución: es una medida muy fiable de la calidad de la malla, obteniendo información que permite llevar a cabo un procedimiento de adaptación de malla. Está fuertemente relacionado al modelo matemático fluido, de modo que una estimación precisa garantiza la idoneidad de dicho modelo en un campo fluido, lo que puede ser útil en el contexto de modelado zonal. Por último, permite mejorar la precisión de la solución resolviendo un nuevo sistema donde el error local actúa como término fuente (_ -extrapolación). El presenta trabajo se organiza de la siguiente manera: Cap. 1 contiene una breve reseña de las técnicas de adaptación de malla, así como de los métodos de predicción de los errores numéricos. En la primera sección, Sec. 1.1, se examinan las estrategias básicas de refinamiento y se presenta la principal contribución a la adaptación de malla estructurada y no estructurada. Sec 1.2 introduce las definiciones de los errores encontrados en la resolución de problemas de Dinámica Computacional de Fluidos y se examinan los enfoques más comunes para predecirlos. Cap. 2 está dedicado a la formulación matemática de la estimación del error de truncación en el contexto de la metodología de Volúmenes Finitos, así como a un procedimiento de verificación completo. Se estudian varias características que influyen en su estimación: la influencia de la falta de uniformidad de la malla, el efecto de las no linealidades del modelo matemático, diferentes condiciones de contorno y soluciones numéricas no convergidas. Esta parte de verificación ha sido presentada y aceptada para su publicación en el Journal of Computational Physics. Cap. 3 presenta un algoritmo de adaptación de malla basado en la estimación del error de truncación y compara los resultados con sensores de featured-based y adjointbased (en colaboración con Jorge Ponsín del INTA). Se consideran casos en dos y tres dimensiones, relevantes para la validación en la industria aeronáutica. Este trabajo ha sido presentado y aceptado en el AIAA Journal. También se incluye una extensión de estos métodos a las ecuaciones RANS (Reynolds Average Navier- Stokes), en donde adaptación de malla basada en _ y _ -extrapolación son aplicados a perfiles con viscosidad de alas. Este último trabajo se ha presentado en los Actas de la Institución de Ingenieros Mecánicos, Parte G: Journal of Aerospace Engineering. Palabras clave: adaptación de malla, predicción del error numérico, volúmenes finitos

A new approach to fuzzy estimation of Takagi-Sugeno model and its applications to optimal control for nonlinear systems

An efficient approach is presented to improve the local and global approximation and modelling capability of Takagi-Sugeno (T-S) fuzzy model. The main aim is obtaining high function approximation accuracy. The main problem is that T-S identification method cannot be applied when the membership functions are overlapped by pairs. This restricts the use of the T-S method because this type of membership function has been widely used during the last two decades in the stability, controller design and are popular in industrial control applications. The approach developed here can be considered as a generalized version of T-S method with optimized performance in approximating nonlinear functions. A simple approach with few computational effort, based on the well known parameters' weighting method is suggested for tuning T-S parameters to improve the choice of the performance index and minimize it. A global fuzzy controller (FC) based Linear Quadratic Regulator (LQR) is proposed in order to show the effectiveness of the estimation method developed here in control applications. Illustrative examples of an inverted pendulum and Van der Pol system are chosen to evaluate the robustness and remarkable performance of the proposed method and the high accuracy obtained in approximating nonlinear and unstable systems locally and globally in comparison with the original T-S model. Simulation results indicate the potential, simplicity and generality of the algorithm.

On a comparison method to reaction-diffusion systems and its applications to chemotaxis

In this paper we consider a general system of reaction-diffusion equations and introduce a comparison method to obtain qualitative properties of its solutions. The comparison method is applied to study the stability of homogeneous steady states and the asymptotic behavior of the solutions of different systems with a chemotactic term. The theoretical results obtained are slightly modified to be applied to the problems where the systems are coupled in the differentiated terms and / or contain nonlocal terms. We obtain results concerning the global stability of the steady states by comparison with solutions of Ordinary Differential Equations.

Kabat Database and its applications: future directions

The Kabat Database was initially started in 1970 to determine the combining site of antibodies based on the available amino acid sequences. The precise delineation of complementarity determining regions (CDR) of both light and heavy chains provides the first example of how properly aligned sequences can be used to derive structural and functional information of biological macromolecules. This knowledge has subsequently been applied to the construction of artificial antibodies with prescribed specificities, and to many other studies. The Kabat database now includes nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules, and other proteins of immunological interest. While new sequences are continually added into this database, we have undertaken the task of developing more analytical methods to study the information content of this collection of aligned sequences. New examples of analysis will be illustrated on a yearly basis. The Kabat Database and its applications are freely available at http://immuno.bme.nwu.edu.

Data assimilation and its applications

In data assimilation, one prepares the grid data as the best possible estimate of the true initial state of a considered system by merging various measurements irregularly distributed in space and time, with a prior knowledge of the state given by a numerical model. Because it may improve forecasting or modeling and increase physical understanding of considered systems, data assimilation now plays a very important role in studies of atmospheric and oceanic problems. Here, three examples are presented to illustrate the use of new types of observations and the ability of improving forecasting or modeling.

The theory of electrons and its applications to the phenomena of light and radiant heat /

Includes bibliographical footnotes and index.

Aniline black and its applications in dyeing and printing /

Includes index.

Darwinism; an exposition of the theory of natural selection, with some of its applications,

Mode of access: Internet.