Electron beam lithography is gaining widespread utilization as the semiconductor industry progresses towards both advanced optical and non-optical lithographic technologies for high resolution patterning. The current resist technologies are based on organic systems that are imaged most commonly through chain scission, networking, or a chemically amplified polarity change in the material. Alternative resists based on inorganic systems were developed and characterized in this research for high resolution electron beam lithography and their interactions with incident electrons were investigated using Monte Carlo simulations. A novel inorganic resist imaging scheme was developed using metal-organic precursors which decompose to form metal oxides upon electron beam irradiation that can serve as inorganic hard masks for hybrid bilayer inorganic-organic imaging systems and also as directly patternable high resolution metal oxide structures. The electron beam imaging properties of these metal-organic materials were correlated to the precursor structure by studying effects such as interactions between high atomic number species and the incident electrons. Optimal single and multicomponent precursors were designed for utilization as viable inorganic resist materials for sub-50nm patterning in electron beam lithography. The electron beam imaging characteristics of the most widely used inorganic resist material, hydrogen silsesquioxane (HSQ), was also enhanced using a dual processing imaging approach with thermal curing as well as a sensitizer catalyzed imaging approach. The interaction between incident electrons and the high atomic number species contained in these inorganic resists was also studied using Monte Carlo simulations. The resolution attainable using inorganic systems as compared to organic systems can be greater for accelerating voltages greater than 50 keV due to minimized lateral scattering in the high density inorganic systems. The effects of loading nanoparticles in an electron beam resist was also investigated using a newly developed hybrid Monte Carlo approach that accounts for multiple components in a solid film. The resolution of the nanocomposite resist process was found to degrade with increasing nanoparticle loading. Finally, the electron beam patterning of self-assembled monolayers, which were found to primarily utilize backscattered electrons from the high atomic number substrate materials to form images, was also investigated and characterized. It was found that backscattered electrons limit the resolution attainable at low incident electron energies.

A novel computational approach, Two Level Simulation (TLS), was developed based on the explicit reconstruction of the small-scale velocity by solving the small-scale governing equations on the domain with reduced dimension representing a collection of one-dimensional lines embedded in the three-dimensional flow domain. A coupled system of equations, that is not based on an eddy-viscosity hypothesis, was derived based on the decomposition of flow variables into the large-scale and the small-scale components without introducing the concept of filtering. Simplified treatment of the small-scale equations was proposed based on modeling of the small-scale advective derivatives and the small-scale dissipative terms in the directions orthogonal to the lines. TLS approach was tested to simulate benchmark cases of turbulent flows, including forced isotropic turbulence, mixing layers and well-developed channel flow, and demonstrated good capabilities to capture turbulent flow features using relatively coarse grids.

This dissertation aims to establish a mathematical model to predict the steady-state (stationary) motion of a nano-particle that is suppressed between two parallel moving objects. The main purpose of this study intends to find an appropriate means to reduce surface damage caused by moving nano-paricle. This study will show that, via the molecular dynamics (MD) analysis, the surface will result in different sizes of damaged layer and surface roughness when a nano-particle moves in a distinct way on it. Therefore, it has a significant value in the applications of high precision polishing and surface cleaning to identify the dominant factors in affecting the motion of nano-particle. The proposed model is to find the steady-state motion by meeting the conditions of force and torque balances on a moving nano-particle. Several hypotheses are suggested to derive the interaction force occurred at the interface between particle and each object. The hypothesis starts from the energy point of view. It is claimed that the potential and kinetic energies of object atoms will increase when nano-particle moves relative to the object. Because of the relative motion, some of the object atoms will be pushed or driven away, depending on the manner of motion. The increment of potential or kinetic energies is assumed to be proportional to the number of pushed or driven atoms. The increase of energy is supplied from the works done by the normal stress and shear stress at the interface of particle. The interaction at the front end of particle is very different from that at the rear end when particle rolls on object surface. There is a pushing action at the front end while a pulling action occurs at the rear end. The magnitudes of both actions are dominated and proportional to the adhesive strength between particle and object. The computer simulations show that the particle motion is mainly affected by the relative adhesive strength among particle and two objects. If the adhesive strength between particle and one object increase, the particle will increase the sliding speed relative to another object. On the other hand, if the adhesive strength between particle and one object is close to that of another object, the particle tends to have significant rolling motion relative to two objects. The suppressed loading between particle and objects has little effect on the qualitative trend of particle motion. The validity of proposed model is evaluated by the molecular dynamics simulation. It indicates that the predicted behaviors of proposed model are consistent with that from the analysis of molecular dynamics simulations.

Metal ions are important for medical, environmental and catalytic applications. They are used as precursor molecules for the manufacture of metal nanocatalysts, which are promising materials for an array of biomedical, industrial, and technological applications. Understanding the effect of the environment upon a metal ion-dendrimer system constitutes a step closer to the understanding of the liquid phase templated synthesis of metal nanoparticles. In this dissertation we have used computational techniques such as abinitio calculations and molecular dynamics (MD) simulations to investigate the complexation of Cu(II) and Pt(II) metal ions to a polyamidoamine (PAMAM) dendritic polymer from structural, thermodynamic, and kinetic viewpoints. First, we analyze the local configuration of a low generation polyamidoamine dendrimer to understand the role of intramolecular interactions. Then, we examine the local configuration of dendrimer outer pockets in order to determine their capacity to encapsulate water within. Next, the complexation of Cu(II) with a small –OH terminated dendrimer in presence of solvent and counterions is investigated. This relatively simple system gives insight on how cationic species bind within a dendrimer. The complexation of potassium tetrachloroplatinate, commonly used precursor salt in dendrimer templated synthesis of platinum and bimetallic platinum-containing nanoparticles, with PAMAM dendrimer has been the subject of several experimental reports. So we investigate the complexation of potassium tetrachloroplatinate within a dendrimer outer pocket in order to understand the effect of dendrimer branches, Pt(II) speciation, pH, solvent and counterions upon it. Our study shows that dendrimer branches can improve the thermodynamics but can also preclude the kinetics by raising the energy barriers. Our study provides an explanation of why, where Pt(II) and how Pt(II) binds. We believe that these molecular level details, unaccessible to experimental techniques, can be a helpful contribution toward furthering our understanding of the complexation of Pt(II) and the starting point to study the next step of dendrimer templated synthesis, the reduction of Pt(II) into platinum nanoparticles inside pockets.

High Mach-number compressible flows with heat release are inherently more complicated than incompressible flows due to, among other reasons, the activation of the thermal energy mode. Such flow fields can experience significant fluctuations in density, temperature, viscosity, conductivity and specific heat, which affect velocity and pressure fluctuations. Furthermore, the flow field cannot be assumed to be dilatation-free in high Mach numbers and even in low Mach-number flows involving combustion, or in boundary layers on heated walls. The main issue in these high-speed and highly-compressible flows is the effect of thermal gradients and fluctuations on turbulence. The thermal field has various routes through which it affects flow structures of compressible turbulence. First, it has direct influence through pressure, which affects turbulence via pressure-strain correlation. The indirect effects of thermal fields on compressible turbulence are through the changes in flow properties. The high temperature gradients alter the transport coefficient and compressibility of the flow. The objective of this work is to answer the following questions: How do temperature fluctuations change the compressible flow structure and energetics? How does compressibility in the flow affect the non-linear pressure redistribution process? What is the main effect of spatial transport-coefficient variation? We perform direct numerical simulations (DNS) to answer the above questions. The investigations are categorized into four parts: 1) Turbulent energy cascade and kinetic-internal energy interactions under the influence of temperature fluctuations; 2) Return-to-isotropy of anisotropic turbulence under the influence of large temperature fluctuations; 3) The effect of turbulent Mach number and dilatation level on small-scale (velocity-gradient) dynamics; 4) The effect of variable transport-coefficients (viscosity and diffusivity) on cascade and dissipation processes of turbulence. The findings lead to a better understanding of temperature fluctuation effects on non-linear processes in compressible turbulence. This improved understanding is expected to provide direction for improving second-order closure models of compressible turbulence.

Abstract Reformer, the most important link of fuel cell, is the main set to create the hydrogen. After the fuel passes through the catalytic reaction by reformer, will produce hydrogen and chemical substances, the hydrogen will become the energy to support fuel cell. At the present day, the technology of PEM fuel cell and traditional fuel reformer has already existed, only need to reduce the volume, cost and to promote the efficiency. Catalytic layer, with the construction of microchannel, makes the adequate impact to gas and catalyst to promote the efficiency. This research uses the Lattice Boltzmann method (LBM) to simulate the fluid field and heat-mass transfer of microchannel, to discuss the function influence to the different parameter such as velocity, temperature, channel length, and channel height. The result displays, with the same inlet speed and temperature, by the increasing of the channel length, the amount of hydrogen will raise and residual methanol will reduce. When the channel length is more than 500£gm, the produce rate of hydrogen will not be a big change. If fix the channel length at 500£gm, under the different inlet temperature, while the maximum concentration at inlet, the speed of hydrogen at inlet is not the same. The best inlet speed will increase with the higher temperature. When fix the channel length at 500£gm, raising the altitude to 500£gm, the hydrogen product will not increase, on the contrary, it¡¦ll go down. Keywords¡GFuel cell reformer¡BMicorchannel of hat and mass transfer¡BNumerical simulations

The purpose of this thesis is to develop a testing environment for mobile robot experiments, to examine methods for multi-robot platooning through hostile environments, and test these algorithms on mobile robots. Such a system will allow us to rapidly address and test problems that arise concerning robot swarms and consequent interactions. In order to create this hardware simulation environment a test bed will be created using ROS or Robot Operating System. This platform is highly modular and extensible for future development. Trajectory generation for the robots will use smoothing splines, B-splines, and A* search. Each method has distinct properties which will be analyzed and rated with respect to its effectiveness with regards to robotic platooning. A few issues to be considered include: Is the optimal path taken with respect to distance and threats? Is the formation of the robots maintained or compromised during traversal of the path? And finally, what sorts of compromises or additions are needed to make each method effective? This work will be helpful for choosing route planning methods in future work and will provide a large code base for rapid prototyping.

<p>This thesis investigates the possibilities of explaining higher cognition as internal simulations of perception and action at an abstract level. Relatively recent findings in both neuroscience and psychology indicates that both perception and action can be internally simulated by activating sensory and motor areas in the brain in absence of sensory input and without any resulting overt behavior. An investigation was conducted in order to test the hypothesis that perception can be simulated in a mobile robot using abstractions. The result from this investigation showed that this was indeed the case but that the accuracy was limited. The simulations allowed the robot to anticipate long chains of future situations but were not good enough to support any overt behavior. To further improve the results there is a need for better training techniques and/or a more complex architecture.</p>

<p><i>Successful integration of simulations within the Network-Based Defence (NBD), specifically use of simulations within Command and Control (C2) environments, enforces a number of requirements. Simulations must be reliable and be able to respond in a timely manner. Otherwise the commander will have no confidence in using simulation as a tool. An important aspect of these requirements is the provision of fault-tolerant simulations in which failures are detected and resolved in a consistent manner. Given the distributed nature of many military simulations systems, services for fault-tolerance in distributed simulations are desirable. The main architecture for distributed simulations within the military domain, the High Level Architecture (HLA), does not provide support for development of fault-tolerant simulations.</i></p><p><i>A common approach for fault-tolerance in distributed systems is check-pointing. In this approach, states of the system are persistently stored through-out its operation. In case a failure occurs, the system is restored using a previously saved state. Given the abovementioned shortcomings of the HLA standard this thesis explores development of fault-tolerant mechanisms in the context of the HLA. More specifically, the design, implementation and evaluation of fault-tolerance mechanisms, based on check-pointing, are described and discussed.</i></p>

Numerical modeling of shallow microtidal semi-enclosed estuaries requires the effective simulation of physical processes with a wide range of temporal and spatial scales. In theory, application of sufficient grid resolution in both the horizontal and vertical should result in a reasonable simulation. However, in practice, this is not the case. Fully resolving the finest scales can be computationally prohibitive, and various algorithmic assumptions can break down at fine resolutions, leading to spurious oscillations in the solution. One method of simulating inherently cross-scale phenomena is to use multimodel approaches in which domain decomposition is used to divide the region into multiple subregions, each modeled by different submodels. These submodels are coupled to simulate the entire system efficiently. In general, the different models may involve different physics, they may be dimensionally heterogeneous or they may be both physically and dimensionally heterogeneous. A reduction in computational expense is obtained by using simpler physics and/or a reduced dimension model in the submodels. In this research, we look at the particular case of modeling shallow bays containing narrow, deep ship channels. In order to accurately model bay circulation, a model should capture the effect of these spatially localized navigational channels. Our research shows that modeling techniques currently used to simulate such systems using 2 dimensional or coarse resolution 3 dimensional estuary models misrepresent wind driven surface circulation in the shallow bay and tide driven volume fluxes through the channel. Fully resolving the geometry of the ship channel is impractical on all but large parallel computing clusters. We propose a more efficient method using the multimodel approach. This approach splits the estuary into a shallow bay region and a subsurface ship channel region. By separating the physical domain into two parts in this way, simpler models can be used that are targeted at the different physical processes and geometries dominant in each region. By using a low resolution 3D model (SELFE) in the shallow bay region, coupled through appropriate interface conditions with a 2D laterally averaged model, the effects of the ship channel on bay circulation are accurately represented at a fraction of the computational expense. In this research, this coupled model was developed and applied to an ideal shallow bay- ship channel system. The coupled model approach is found to be an effective strategy for modeling this type of system. / text