Irradiation-mediated tailoring of carbon nanotubes

The ever-increasing demand for faster computers in various areas, ranging from entertaining electronics to computational science, is pushing the semiconductor industry towards its limits on decreasing the sizes of electronic devices based on conventional materials. According to the famous law by Gordon E. Moore, a co-founder of the world s largest semiconductor company Intel, the transistor sizes should decrease to the atomic level during the next few decades to maintain the present rate of increase in the computational power. As leakage currents become a problem for traditional silicon-based devices already at sizes in the nanometer scale, an approach other than further miniaturization is needed to accomplish the needs of the future electronics. A relatively recently proposed possibility for further progress in electronics is to replace silicon with carbon, another element from the same group in the periodic table. Carbon is an especially interesting material for nanometer-sized devices because it forms naturally different nanostructures. Furthermore, some of these structures have unique properties. The most widely suggested allotrope of carbon to be used for electronics is a tubular molecule having an atomic structure resembling that of graphite. These carbon nanotubes are popular both among scientists and in industry because of a wide list of exciting properties. For example, carbon nanotubes are electronically unique and have uncommonly high strength versus mass ratio, which have resulted in a multitude of proposed applications in several fields. In fact, due to some remaining difficulties regarding large-scale production of nanotube-based electronic devices, fields other than electronics have been faster to develop profitable nanotube applications. In this thesis, the possibility of using low-energy ion irradiation to ease the route towards nanotube applications is studied through atomistic simulations on different levels of theory. Specifically, molecular dynamic simulations with analytical interaction models are used to follow the irradiation process of nanotubes to introduce different impurity atoms into these structures, in order to gain control on their electronic character. Ion irradiation is shown to be a very efficient method to replace carbon atoms with boron or nitrogen impurities in single-walled nanotubes. Furthermore, potassium irradiation of multi-walled and fullerene-filled nanotubes is demonstrated to result in small potassium clusters in the hollow parts of these structures. Molecular dynamic simulations are further used to give an example on using irradiation to improve contacts between a nanotube and a silicon substrate. Methods based on the density-functional theory are used to gain insight on the defect structures inevitably created during the irradiation. Finally, a new simulation code utilizing the kinetic Monte Carlo method is introduced to follow the time evolution of irradiation-induced defects on carbon nanotubes on macroscopic time scales. Overall, the molecular dynamic simulations presented in this thesis show that ion irradiation is a promisingmethod for tailoring the nanotube properties in a controlled manner. The calculations made with density-functional-theory based methods indicate that it is energetically favorable for even relatively large defects to transform to keep the atomic configuration as close to the pristine nanotube as possible. The kinetic Monte Carlo studies reveal that elevated temperatures during the processing enhance the self-healing of nanotubes significantly, ensuring low defect concentrations after the treatment with energetic ions. Thereby, nanotubes can retain their desired properties also after the irradiation. Throughout the thesis, atomistic simulations combining different levels of theory are demonstrated to be an important tool for determining the optimal conditions for irradiation experiments, because the atomic-scale processes at short time scales are extremely difficult to study by any other means.

Numerical approaches to new particle formation and growth in the atmosphere

Aerosols impact the planet and our daily lives through various effects, perhaps most notably those related to their climatic and health-related consequences. While there are several primary particle sources, secondary new particle formation from precursor vapors is also known to be a frequent, global phenomenon. Nevertheless, the formation mechanism of new particles, as well as the vapors participating in the process, remain a mystery. This thesis consists of studies on new particle formation specifically from the point of view of numerical modeling. A dependence of formation rate of 3 nm particles on the sulphuric acid concentration to the power of 1-2 has been observed. This suggests nucleation mechanism to be of first or second order with respect to the sulphuric acid concentration, in other words the mechanisms based on activation or kinetic collision of clusters. However, model studies have had difficulties in replicating the small exponents observed in nature. The work done in this thesis indicates that the exponents may be lowered by the participation of a co-condensing (and potentially nucleating) low-volatility organic vapor, or by increasing the assumed size of the critical clusters. On the other hand, the presented new and more accurate method for determining the exponent indicates high diurnal variability. Additionally, these studies included several semi-empirical nucleation rate parameterizations as well as a detailed investigation of the analysis used to determine the apparent particle formation rate. Due to their high proportion of the earth's surface area, oceans could potentially prove to be climatically significant sources of secondary particles. In the lack of marine observation data, new particle formation events in a coastal region were parameterized and studied. Since the formation mechanism is believed to be similar, the new parameterization was applied in a marine scenario. The work showed that marine CCN production is feasible in the presence of additional vapors contributing to particle growth. Finally, a new method to estimate concentrations of condensing organics was developed. The algorithm utilizes a Markov chain Monte Carlo method to determine the required combination of vapor concentrations by comparing a measured particle size distribution with one from an aerosol dynamics process model. The evaluation indicated excellent agreement against model data, and initial results with field data appear sound as well.

Time scales for transitions between free-energy minima of a dense hard-sphere system

Time scales associated with activated transitions between glassy metastable states of a free-energy functional appropriate for a dense hard-sphere system are calculated by using a new Monte Carlo method for the local density variables. In particular, we calculate the time the system, initially placed in a shallow glassy minimum of the free-energy, spends in the neighborhood of this minimum before making a transition to the basin of attraction of another free-energy minimum. This time scale is found to increase as the average density is increased. We find a crossover density near which this time scale increases very sharply and becomes longer than the longest times accessible in our simulation. This time scale does not show any evidence of increasing with sample size

FIELD EMISSION EFFICIENCY OF A CARBON NANOTUBE ARRAY UNDER PARASITIC NONLINEARITIES

Carbon Nanotubes (CNTs) grown on substrates are potential electron sources in field emission applications. Several studies have reported the use of CNTs in field emission devices, including field emission displays, X-ray tube, electron microscopes, cathode-ray lamps, etc. Also, in recent years, conventional cold field emission cathodes have been realized in micro-fabricated arrays for medical X-ray imaging. CNTbased field emission cathode devices have potential applications in a variety of industrial and medical applications, including cancer treatment. Field emission performance of a single isolated CNT is found to be remarkable, but the situation becomes complex when an array of CNTs is used. At the same time, use of arrays of CNTs is practical and economical. Indeed, such arrays on cathode substrates can be grown easily and their collective dynamics can be utilized in a statistical sense such that the average emission intensity is high enough and the collective dynamics lead to longer emission life. The authors in their previous publications had proposed a novel approach to obtain stabilized field emission current from a stacked CNT array of pointed height distribution. A mesoscopic modeling technique was employed, which took into account electro-mechanical forces in the CNTs, as well as transport of conduction electron coupled with electron phonon induced heat generation from the CNT tips. The reported analysis of pointed arrangements of the array showed that the current density distribution was greatly localized in the middle of the array, the scatter due to electrodynamic force field was minimized, and the temperature transients were much smaller compared to those in an array with random height distribution. In the present paper we develop a method to compute the emission efficiency of the CNT array in terms of the amount of electrons hitting the anode surface using trajectory calculations. Effects of secondary electron emission and parasitic capacitive nonlinearity on the current-voltage signals are accounted. Field emission efficiency of a stacked CNT array with various pointed height distributions are compared to that of arrays with random and uniform height distributions. Effect of this parasitic nonlinearity on the emission switch-on voltage is estimated by model based simulation and Monte Carlo method.

Aircraft Composite Structure Preventive Maintenance

In this paper, a methodology to reduce composite structure maintenance operational cost using SHM systems is adressed. Based on SHM real-time data, in-service structure lifetime prognostic and remaining useful lifetime (RUL) can be performed. Maintenance timetable can be therefore predicted by optimizing inspection times. A probabilistic ap-proach is combined with phenomenological fatigue damage models for composite mate-rials to perform maintenance cost-effectiveness of composite structure. A Monte Carlo method is used to estimate the probability of failure of composite structures and com-pute the average number of composite structure components to be replaced over the component lifetime. The replacement frequency of a given structure component over the aircraft lifetime is assessed. A first application of aeronautical composite structure maintenance is considered. Two composite models to predict the fatigue life and several laminates have been used. Our study shows that maintenance cost-effectiveness depends on material and fatigue loading applied.

Examination of the LBM in simulation of microchannel flow in transitional regime

The gas flows in micro-electro-mechanical systems possess relatively large Knudsen number and usually belong to the slip flow and transitional flow regimes. Recently the lattice Boltzmann method (LBM) was proposed by Nie et al. in Journal of Statistical Physics, vol. 107, pp. 279-289, in 2002 to simulate the microchannel and microcavity flows in the transitional flow regime. The present article intends to test the feasibility of doing so. The results of using the lattice Boltzmann method and the direct simulation Monte Carlo method show good agreement between them for small Kn (Kn = 0.0194), poor agreement for Kn = 0.194, and large deviation for Kn = 0.388 in simulating microchannel flows. This suggests that the present version of the lattice Boltzmann method is not feasible to simulate the transitional channel flow.

Bubble-to-Slug Transition for Low-Re Two-Phase Flows

A critical review on the mechanism and models on the bubble-to-slug transition of two-phase gas-liquid flows are presented in the present paper. It is shown that the most possible mechanism controlled the bubble-to-slug transition is the bubble coalescence. Focusing on the bubble-to-slug transition for the low-Re two-phase flow, a simple Monte Carlo method is used to simulate the influence of the initial bubble size on the bubble-to-slug transition. Some secondary factors, such as the liquid viscosity, the surface tension, and the relative slip between the two phases, are ignored in the present study. It is found that the locus of the dimensionless rate of collision is a universal curve. Based on this curve, it is determined that the bubble initial size can affect the phase distribution and flow pattern when its dimensionless value is in the range from 0.03 to 0.4. A simple relationship between the critical void fraction and the initial bubble size is proposed, which agrees very well with the experimental data.

Information Preservation Modeling of Rayleigh-Benard Transition from Thermal Conduction to Convection

Onset and evolution of the Rayleigh-Benard (R-B) convection are investigated using the Information Preservation (IP) method. The information velocity and temperature are updated using the Octant Flux Splitting (OFS) model developed by Masters & Ye based on the Maxwell transport equation suggested by Sun & Boyd. Statistical noise inherent in particle approaches such as the direct simulation Monte Carlo (DSMC) method is effectively reduced by the IP method, and therefore the evolutions from an initial quiescent fluid to a final steady state are shown clearly. An interesting phenomenon is observed: when the Rayleigh number (Ra) exceeds its critical value, there exists an obvious incubation stage. During the incubation stage, the vortex structure clearly appears and evolves, whereas the Nusselt number (Nu) of the lower plate is close to unity. After the incubation stage, the vortex velocity and Nu rapidly increase, and the flow field quickly reaches a steady, convective state. A relation of Nu to Ra given by IP agrees with those given by DSMC, the classical theory and experimental data.

Rarefied gas dynamics: fundamentals, simulations and micro flows

Kinetic studies of gas flows

Our recent studies on kinetic behaviors of gas flows are reviewed in this paper. These flows have a wide range of background, but share a common feature that the flow Knudsen number is larger than 0.01. Thus kinetic approaches such as the direct simulation Monte Carlo method are required for their description. In the past few years, we studied several micro/nano-scale flows by developing novel particle simulation approach, and investigated the flows in low-pressure chambers and at high altitude. In addition, the microscopic behaviors of a couple of classical flow problems were analyzed, which shows the potential for kinetic approaches to reveal the microscopic mechanism of gas flows.

Two-phase flow and pool boiling heat transfer in microgravity

Researches on two-phase flow and pool boiling heat transfer in microgravity, which included groundbased tests, flight experiments, and theoretical analyses, were conducted in the National Microgravity Laboratory/CAS. A semi-theoretical Weber number model was proposed to predict the slug-to-annular flow transition of two-phase gas–liquid flows in microgravity, while the influence of the initial bubble size on the bubble-to-slug flow transition was investigated numerically using the Monte Carlo method. Two-phase flow pattern maps in microgravity were obtained in the experiments both aboard the Russian space station Mir and aboard IL-76 reduced gravity airplane. Mini-scale modeling was also used to simulate the behavior of microgravity two-phase flow on the ground. Pressure drops of two-phase flow in microgravity were also measured experimentally and correlated successfully based on its characteristics. Two space experiments on pool boiling phenomena in microgravity were performed aboard the Chinese recoverable satellites. Steady pool boiling of R113 on a thin wire with a temperature-controlled heating method was studied aboard RS-22, while quasi-steady pool boiling of FC-72 on a plate was studied aboard SJ-8. Ground-based experiments were also performed both in normal gravity and in short-term microgravity in the drop tower Beijing. Only slight enhancement of heat transfer was observed in the wire case, while enhancement in low heat flux and deterioration in high heat flux were observed in the plate case. Lateral motions of vapor bubbles were observed before their departure in microgravity. The relationship between bubble behavior and heat transfer on plate was analyzed. A semi-theoretical model was also proposed for predicting the bubble departure diameter during pool boiling on wires. The results obtained here are intended to become a powerful aid for further investigation in the present discipline and development of two-phase systems for space applications.

Multiscale model reduction methods for deterministic and stochastic partial differential equations

Partial differential equations (PDEs) with multiscale coefficients are very difficult to solve due to the wide range of scales in the solutions. In the thesis, we propose some efficient numerical methods for both deterministic and stochastic PDEs based on the model reduction technique.

For the deterministic PDEs, the main purpose of our method is to derive an effective equation for the multiscale problem. An essential ingredient is to decompose the harmonic coordinate into a smooth part and a highly oscillatory part of which the magnitude is small. Such a decomposition plays a key role in our construction of the effective equation. We show that the solution to the effective equation is smooth, and could be resolved on a regular coarse mesh grid. Furthermore, we provide error analysis and show that the solution to the effective equation plus a correction term is close to the original multiscale solution.

For the stochastic PDEs, we propose the model reduction based data-driven stochastic method and multilevel Monte Carlo method. In the multiquery, setting and on the assumption that the ratio of the smallest scale and largest scale is not too small, we propose the multiscale data-driven stochastic method. We construct a data-driven stochastic basis and solve the coupled deterministic PDEs to obtain the solutions. For the tougher problems, we propose the multiscale multilevel Monte Carlo method. We apply the multilevel scheme to the effective equations and assemble the stiffness matrices efficiently on each coarse mesh grid. In both methods, the $\KL$ expansion plays an important role in extracting the main parts of some stochastic quantities.

For both the deterministic and stochastic PDEs, numerical results are presented to demonstrate the accuracy and robustness of the methods. We also show the computational time cost reduction in the numerical examples.

蒙特卡罗模拟四极阱中原子的参变激发

在中性原子的磁囚禁实验中,磁阱线圈的电流噪声会激发磁阱中的原子运动,势必对原子团的温度和寿命产生不可忽视的影响。对于非简谐阱,这种激发具有能量选择特性,它又取决于电流噪声的频谱分布。选择了实验中常用的四极阱为研究对象,用直接模拟蒙特卡罗方法来模拟四极阱中原子运动的参变激发现象,得到了原子温度与原子数损失随激发频率的变化关系,并进一步计算了两个共振峰处原子温度随调制时间和调制深度的变化曲线。此外,还研究了弹性碰撞速率对参变激发过程中原子温度上升的影响。这些结果对四极阱参变激发的实验有较好的参考价值。

光通过纳米颗粒随机散射体透射光强的计算及分析

光通过随机散射体后透射光强的估算,对于提取散射体内部无法直接测量或者无法直接观察的信息至关重要。在分析平行光束通过纳米圆形颗粒随机散射体出射面上光强组成的基础上推导了透射光强的计算公式,并指出多重散射理论、一阶多重散射理论和朗伯比尔定律在一定近似程度上可以相对精确地估算透射光强。这三种方法的估算结果之间会出现四种相对关系。根据这些相对关系,分析了光在散射体内部传输时散射过程的特征以及各种散射过程对出射面光强的贡献大小。

Desenvolvimento de um simulador para espectrometria por fluorescência de raios X usando computação distribuída

A Física das Radiações é um ramo da Física que está presente em diversas áreas de estudo e se relaciona ao conceito de espectrometria. Dentre as inúmeras técnicas espectrométricas existentes, destaca-se a espectrometria por fluorescência de raios X. Esta também possui uma gama de variações da qual pode-se dar ênfase a um determinado subconjunto de técnicas. A produção de fluorescência de raios X permite (em certos casos) a análise das propriedades físico-químicas de uma amostra específica, possibilitando a determinação de sua constituiçõa química e abrindo um leque de aplicações. Porém, o estudo experimental pode exigir uma grande carga de trabalho, tanto em termos do aparato físico quanto em relação conhecimento técnico. Assim, a técnica de simulação entra em cena como um caminho viável, entre a teoria e a experimentação. Através do método de Monte Carlo, que se utiliza da manipulação de números aleatórios, a simulação se mostra como uma espécie de alternativa ao trabalho experimental.Ela desenvolve este papel por meio de um processo de modelagem, dentro de um ambiente seguro e livre de riscos. E ainda pode contar com a computação de alto desempenho, de forma a otimizar todo o trabalho por meio da arquitetura distribuída. O objetivo central deste trabalho é a elaboração de um simulador computacional para análise e estudo de sistemas de fluorescência de raios X desenvolvido numa plataforma de computação distribuída de forma nativa com o intuito de gerar dados otimizados. Como resultados deste trabalho, mostra-se a viabilidade da construção do simulador através da linguagem CHARM++, uma linguagem baseada em C++ que incorpora rotinas para processamento distribuído, o valor da metodologia para a modelagem de sistemas e a aplicação desta na construção de um simulador para espectrometria por fluorescência de raios X. O simulador foi construído com a capacidade de reproduzir uma fonte de radiação eletromagnética, amostras complexas e um conjunto de detectores. A modelagem dos detectores incorpora a capacidade de geração de imagens baseadas nas contagens registradas. Para validação do simulador, comparou-se os resultados espectrométricos com os resultados gerados por outro simulador já validado: o MCNP.