Preparation of Y2Si2O7/ ZrO2 composites and their composition - Mechanical properties - Tribology relationships

In this work, novel Y2Si2O7/ZrO 2 composites were developed for structural and coating applications by taking advantage of their unique properties, such as good damage tolerance, tunable mechanical properties, and superior wear resistance. The γ-Y 2Si2O7/ZrO2 composites showed improved mechanical properties compared to the γ-Y2Si 2O7 matrix material, that is, the Young's modulus was enhanced from 155 to 188 GPa (121%) and the flexural strength from 135 to 254 MPa (181%); when the amount of ZrO2 was increased from 0 to 50 vol%, the γ-Y2Si2O7/ZrO2 composites also presented relatively high facture toughness (>1.7 MPa·m 1/2), but this exhibited an inverse relationship with the ZrO 2 content. The composition-mechanical property-tribology relationships of the Y2Si2O7/ZrO2 composites were elucidated. The wear resistance of the composites is not only influenced by the applied load, hardness, strength, toughness, and rigidity but also effectively depends on micromechanical stability properties of the microstructures. The easy growth of subcritical microcracks in Y 2Si2O7 grains and at grain boundaries significantly contributes to the macroscopic fracture toughness, but promotes the pull-out of individual grains, thus resulting in a lack of correlation between the wear rate and the macroscopic fracture toughness of the composites.

Characterization of Failure Modes in CFRP Composites - An ANN Approach

Carbon fiber reinforced polymer (CFRP) composite specimens with different thickness, geometry, and stacking sequences were subjected to fatigue spectrum loading in stages. Another set of specimens was subjected to static compression load. On-line acoustic Emission (AE) monitoring was carried out during these tests. Two artificial neural networks, Kohonen-self organizing feature map (KSOM), and multi-layer perceptron (MLP) have been developed for AE signal analysis. AE signals from specimens were clustered using the unsupervised learning KSOM. These clusters were correlated to the failure modes using available a priori information such as AE signal amplitude distributions, time of occurrence of signals, ultrasonic imaging, design of the laminates (stacking sequences, orientation of fibers), and AE parametric plots. Thereafter, AE signals generated from the rest of the specimens were classified by supervised learning MLP. The network developed is made suitable for on-line monitoring of AE signals in the presence of noise, which can be used for detection and identification of failure modes and their growth. The results indicate that the characteristics of AE signals from different failure modes in CFRP remain largely unaffected by the type of load, fiber orientation, and stacking sequences, they being representatives of the type of failure phenomena. The type of loading can have effect only on the extent of damage allowed before the specimens fail and hence on the number of AE signals during the test. The artificial neural networks (ANN) developed and the methods and procedures adopted show significant success in AE signal characterization under noisy environment (detection and identification of failure modes and their growth).

Effect of Crystallographic Structure of MnO2 on Its Electrochemical Capacitance Properties

MnO2 is currently under extensive investigations for its capacitance properties. MnO2 crystallizes into several crystallographic structures, namely, α, β, γ, δ, and λ structures. Because these structures differ in the way MnO6 octahedra are interlinked, they possess tunnels or interlayers with gaps of different magnitudes. Because capacitance properties are due to tercalation/deintercalation of protons or cations in MnO2, only some crystallographic structures, which possess sufficient gaps to accommodate these ions, are expected to be useful for capacitance studies. In order to examine the dependence of capacitance on crystal structure, the present study involves preparation of these various crystal phases of MnO2 in nanodimensions and to evaluate their capacitance properties. Results of α-MnO2 prepared by a microemulsion route (α-MnO2(m)) are also used for comparison. Spherical particles of about 50 nm, nanorods of 30−50 nm in diameter, or interlocked fibers of 10−20 nm in diameters are formed, which depend on the crystal structure and the method of preparation. The specific capacitance (SC) measured for MnO2 is found to depend strongly on the crystallographic structure, and it decreases in the following order: α(m) > α δ > γ > λ > β. A SC value of 297 F g-1 is obtained for α-MnO2(m), whereas it is 9 F g-1 for β-MnO2. A wide (4.6 Å) tunnel size and large surface area of α-MnO2(m) are ascribed as favorable factors for its high SC. A large interlayer separation (7 Å) also facilitates insertion of cations in δ-MnO2 resulting in a SC close to 236 F g-1. A narrow tunnel size (1.89 Å) does not allow intercalation of cations into β-MnO2. As a result, it provides a very small SC.

Carotid Stenosis, Endarterectomy, and the Brain : Brain microcirculation, diffusion, and cognitive function before and after carotid endarterectomy in patients with a high-grade carotid stenosis

Carotid atherosclerotic disease is a major cause of stroke, but it may remain clinically asymptomatic. The factors that turn the asymptomatic plaque into a symptomatic one are not fully understood, neither are the subtle effects that a high-grade carotid stenosis may have on the brain. The purpose of this study was to evaluate brain microcirculation, diffusion, and cognitive performance in patients with a high-grade stenosis in carotid artery, clinically either symptomatic or asymptomatic, undergoing carotid endarterectomy (CEA). We wanted to find out whether the stenoses are associated with diffusion or perfusion abnormalities of the brain or variation in the cognitive functioning of the patients, and to what extent the potential findings are affected by CEA, and compare the clinically symptomatic and asymptomatic subjects as well as strictly healthy controls. Coagulation and fibrinolytic parameters were compared with the rate microembolic signals (MES) in transcranial Doppler (TCD) and the macroscopic appearance of stenosing plaques in surgery. Patients (n=92) underwent CEA within the study. Blood samples pertaining to coagulation and fibrinolysis were collected before CEA, and the subjects underwent repeated TCD monitoring for MES. A subpopulation (n= 46) underwent MR imaging and repeated neuropsychological examination (preoperative, as well 4 and 100 days after CEA). In MRI, the average apparent diffusion coefficients were higher in the ipsilateral white matter (WM), and altough the interhemispheric difference was abolished by CEA, the levels remained higher than in controls. Symptomatic stenoses were associated with more sluggish perfusion especially in WM, and lower pulsatility of flow in TCD. All patients had poorer cognitive performance than healthy controls. Cognitive functions improved as expected by learning effect despite transient postoperative worsening in a few subjects. Improvement was greater in patients with deepest hypoperfusion, primarily in executive functions. Symptomatic stenoses were associated with higher hematocrit and tissue plasminogen activator antigen levels, as well as higher rate of MES and ulcerated plaques, and better postoperative improvement of vasoreactivity and pulsatility. In light of the findings, carotid stenosis is associated with differences in brain diffusion, perfusion, and cognition. The effect on diffusion in the ipsilateral WM, partially reversible by CEA, may be associated with WM degeneration. Asymptomatic and symptomatic subpopulations differ from each other in terms of hemodynamic adaptation and in their vascular physiological response to removal of stenosis. Although CEA may be associated with a transient cognitive decline, a true improvement of cognitive performance by CEA is possible in patients with the most pronounced perfusion deficits. Mediators of fibrinolysis and unfavourable hemorheology may contribute to the development of a symptomatic disease in patients with a high-grade stenosis.

Fractional damping: Stochastic origin and finite approximations

Fractional-order derivatives appear in various engineering applications including models for viscoelastic damping. Damping behavior of materials, if modeled using linear, constant coefficient differential equations, cannot include the long memory that fractional-order derivatives require. However, sufficiently great rnicrostructural disorder can lead, statistically, to macroscopic behavior well approximated by fractional order derivatives. The idea has appeared in the physics literature, but may interest an engineering audience. This idea in turn leads to an infinite-dimensional system without memory; a routine Galerkin projection on that infinite-dimensional system leads to a finite dimensional system of ordinary differential equations (ODEs) (integer order) that matches the fractional-order behavior over user-specifiable, but finite, frequency ranges. For extreme frequencies (small or large), the approximation is poor. This is unavoidable, and users interested in such extremes or in the fundamental aspects of true fractional derivatives must take note of it. However, mismatch in extreme frequencies outside the range of interest for a particular model of a real material may have little engineering impact.

Long-lived giant number fluctuations in a swarming granular nematic

Coherently moving flocks of birds, beasts, or bacteria are examples of living matter with spontaneous orientational order. How do these systems differ from thermal equilibrium systems with such liquid crystalline order? Working with a fluidized monolayer of macroscopic rods in the nematic liquid crystalline phase, we find giant number fluctuations consistent with a standard deviation growing linearly with the mean, in contrast to any situation where the central limit theorem applies. These fluctuations are long-lived, decaying only as a logarithmic function of time. This shows that flocking, coherent motion, and large-scale inhomogeneity can appear in a system in which particles do not communicate except by contact.

Microwave-Assisted Synthesis of NiO Nanoparticles

NiO has been synthesized by microwave-induced chemical synthesis route using metalorganic complex of nickel in a domestic-type microwave oven (2.45 GHz). A novel metalorganic complex of nickel, viz., a beta-ketoester of nickel, synthesized and characterized as apart of this work, was employed as the precursor material. We varied the experimental parameters, such as the choice of solvent and microwave power, to obtain nanoparticles of NiO. The NiO nanoparticles were characterized by XRD, SEM, and TEM. The particle size of the NiO was found to vary from 7-40 nm. The magnetic behavior of the nanoparticles of NiO was examined with a vibrating sample magnetometer, revealing that as the particle size diminishes, the magnetic ordering in NiO changes, leading to a small, measurable coercivity.

Studies on Aerosol Particle Emission, Sampling and Authenticity

Emissions of coal combustion fly ash through real scale ElectroStatic Precipitators (ESP) were studied in different coal combustion and operation conditions. Sub-micron fly-ash aerosol emission from a power plant boiler and the ESP were determined and consequently the aerosol penetration, as based on electrical mobility measurements, thus giving thereby an indication for an estimate on the size and the maximum extent that the small particles can escape. The experimentals indicate a maximum penetration of 4% to 20 % of the small particles, as counted on number basis instead of the normally used mass basis, while simultaneously the ESP is operating at a nearly 100% collection efficiency on mass basis. Although the size range as such seems to appear independent of the coal, of the boiler or even of the device used for the emission control, the maximum penetration level on the number basis depends on the ESP operating parameters. The measured emissions were stable during stable boiler operation for a fired coal, and the emissions seemed each to be different indicating that the sub-micron size distribution of the fly-ash could be used as a specific characteristics for recognition, for instance for authenticity, provided with an indication of known stable operation. Consequently, the results on the emissions suggest an optimum particle size range for environmental monitoring in respect to the probability of finding traces from the samples. The current work embodies also an authentication system for aerosol samples for post-inspection from any macroscopic sample piece. The system can comprise newly introduced new devices, for mutually independent use, or, for use in a combination with each other, as arranged in order to promote the sampling operation length and/or the tag selection diversity. The tag for the samples can be based on naturally occurring measures and/or added measures of authenticity in a suitable combination. The method involves not only military related applications but those in civil industries as well. Alternatively to the samples, the system can be applied to ink for note printing or other monetary valued papers, but also in a filter manufacturing for marking fibrous filters.

Structural and electrical transport of carbon nanofibers derived from dihydro-2,5-furandione

Carbon nanofibers of 50–500 nm diameter and several micrometer length were synthesized by high-temperature pyrolysis of dihydro-2,5-furandione (C4H4O3) in the temperature range of 600–980 °C. The formation of both graphitic and non-graphitic structured carbon fibers was observed in high-resolution transmission electron microscope. The Raman spectra of the samples showed the presence of both the D and G bands of varying intensity and sharpness. The low-temperature electrical transport studies on the samples have shown interesting metal–insulator transitions. The films showed variable range hopping conduction in the insulating regime and power law behavior in the critical regime at low temperatures.

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.

Atomic scale engineering of carbon nanotubes

Carbon nanotubes, seamless cylinders made from carbon atoms, have outstanding characteristics: inherent nano-size, record-high Young’s modulus, high thermal stability and chemical inertness. They also have extraordinary electronic properties: in addition to extremely high conductance, they can be both metals and semiconductors without any external doping, just due to minute changes in the arrangements of atoms. As traditional silicon-based devices are reaching the level of miniaturisation where leakage currents become a problem, these properties make nanotubes a promising material for applications in nanoelectronics. However, several obstacles must be overcome for the development of nanotube-based nanoelectronics. One of them is the ability to modify locally the electronic structure of carbon nanotubes and create reliable interconnects between nanotubes and metal contacts which likely can be used for integration of the nanotubes in macroscopic electronic devices. In this thesis, the possibility of using ion and electron irradiation as a tool to introduce defects in nanotubes in a controllable manner and to achieve these goals is explored. Defects are known to modify the electronic properties of carbon nanotubes. Some defects are always present in pristine nanotubes, and naturally are introduced during irradiation. Obviously, their density can be controlled by irradiation dose. Since different types of defects have very different effects on the conductivity, knowledge of their abundance as induced by ion irradiation is central for controlling the conductivity. In this thesis, the response of single walled carbon nanotubes to ion irradiation is studied. It is shown that, indeed, by energy selective irradiation the conductance can be controlled. Not only the conductivity, but the local electronic structure of single walled carbon nanotubes can be changed by the defects. The presented studies show a variety of changes in the electronic structures of semiconducting single walled nanotubes, varying from individual new states in the band gap to changes in the band gap width. The extensive simulation results for various types of defect make it possible to unequivocally identify defects in single walled carbon nanotubes by combining electronic structure calculations and scanning tunneling spectroscopy, offering a reference data for a wide scientific community of researchers studying nanotubes with surface probe microscopy methods. In electronics applications, carbon nanotubes have to be interconnected to the macroscopic world via metal contacts. Interactions between the nanotubes and metal particles are also essential for nanotube synthesis, as single walled nanotubes are always grown from metal catalyst particles. In this thesis, both growth and creation of nanotube-metal nanoparticle interconnects driven by electron irradiation is studied. Surface curvature and the size of metal nanoparticles is demonstrated to determine the local carbon solubility in these particles. As for nanotube-metal contacts, previous experiments have proved the possibility to create junctions between carbon nanotubes and metal nanoparticles under irradiation in a transmission electron microscope. In this thesis, the microscopic mechanism of junction formation is studied by atomistic simulations carried out at various levels of sophistication. It is shown that structural defects created by the electron beam and efficient reconstruction of the nanotube atomic network, inherently related to the nanometer size and quasi-one dimensional structure of nanotubes, are the driving force for junction formation. Thus, the results of this thesis not only address practical aspects of irradiation-mediated engineering of nanosystems, but also contribute to our understanding of the behaviour of point defects in low-dimensional nanoscale materials.

To Dope Mn2+ in a Semiconducting Nanocrystal

It has been an outstanding problem that a semiconducting host in the bulk form can be doped to a large extent, while the same host in the nanocrystal form is found to resist any appreciable level of doping rather stubbornly, this problem being more acute in the wurtzite form compared to the zinc blende one. In contrast, our results based on the lattice parameter tuning in a ZnxCd1−xS alloy nanocrystal system achieves 7.5% Mn2+ doping in a wurtzite nanocrystal, such a concentration being substantially higher compared to earlier reports even for nanocrystal hosts with the “favorable” zinc-blende structure. These results prove a consequence of local strains due to a size mismatch between the dopant and the host that can be avoided by optimizing the composition of the alloyed host. Additionally, the present approach opens up a new route to dope such nanocrystals to a macroscopic extent as required for many applications. Photophysical studies show that the quantum efficiency per Mn2+ ion decreases exponentially with the average number of Mn2+ ions per nanocrystal; en route, a high quantum efficiency of 25% is achieved for a range of compositions.

Overview No.144 - Mechanical behavior of amorphous alloys

The mechanical properties of amorphous alloys have proven both scientifically unique and of potential practical interest, although the underlying deformation physics of these materials remain less firmly established as compared with crystalline alloys. In this article, we review recent advances in understanding the mechanical behavior of metallic glasses, with particular emphasis on the deformation and fracture mechanisms. Atomistic as well as continuum modeling and experimental work on elasticity, plastic flow and localization, fracture and fatigue are all discussed, and theoretical developments are connected, where possible, with macroscopic experimental responses. The role of glass structure on mechanical properties, and conversely, the effect of deformation upon glass structure, are also described. The mechanical properties of metallic glass-derivative materials – including in situ and ex situ composites, foams and nanocrystal-reinforced glasses – are reviewed as well. Finally, we identify a number of important unresolved issues for the field.

Molecular dynamics studies of nanoparticle impacts

This thesis concerns the dynamics of nanoparticle impacts on solid surfaces. These impacts occur, for instance, in space, where micro- and nanometeoroids hit surfaces of planets, moons, and spacecraft. On Earth, materials are bombarded with nanoparticles in cluster ion beam devices, in order to clean or smooth their surfaces, or to analyse their elemental composition. In both cases, the result depends on the combined effects of countless single impacts. However, the dynamics of single impacts must be understood before the overall effects of nanoparticle radiation can be modelled. In addition to applications, nanoparticle impacts are also important to basic research in the nanoscience field, because the impacts provide an excellent case to test the applicability of atomic-level interaction models to very dynamic conditions. In this thesis, the stopping of nanoparticles in matter is explored using classical molecular dynamics computer simulations. The materials investigated are gold, silicon, and silica. Impacts on silicon through a native oxide layer and formation of complex craters are also simulated. Nanoparticles up to a diameter of 20 nm (315000 atoms) were used as projectiles. The molecular dynamics method and interatomic potentials for silicon and gold are examined in this thesis. It is shown that the displacement cascade expansionmechanism and crater crown formation are very sensitive to the choice of atomic interaction model. However, the best of the current interatomic models can be utilized in nanoparticle impact simulation, if caution is exercised. The stopping of monatomic ions in matter is understood very well nowadays. However, interactions become very complex when several atoms impact on a surface simultaneously and within a short distance, as happens in a nanoparticle impact. A high energy density is deposited in a relatively small volume, which induces ejection of material and formation of a crater. Very high yields of excavated material are observed experimentally. In addition, the yields scale nonlinearly with the cluster size and impact energy at small cluster sizes, whereas in macroscopic hypervelocity impacts, the scaling 2 is linear. The aim of this thesis is to explore the atomistic mechanisms behind the nonlinear scaling at small cluster sizes. It is shown here that the nonlinear scaling of ejected material yield disappears at large impactor sizes because the stopping mechanism of nanoparticles gradually changes to the same mechanism as in macroscopic hypervelocity impacts. The high yields at small impactor size are due to the early escape of energetic atoms from the hot region. In addition, the sputtering yield is shown to depend very much on the spatial initial energy and momentum distributions that the nanoparticle induces in the material in the first phase of the impact. At the later phases, the ejection of material occurs by several mechanisms. The most important mechanism at high energies or at large cluster sizes is atomic cluster ejection from the transient liquid crown that surrounds the crater. The cluster impact dynamics detected in the simulations are in agreement with several recent experimental results. In addition, it is shown that relatively weak impacts can induce modifications on the surface of an amorphous target over a larger area than was previously expected. This is a probable explanation for the formation of the complex crater shapes observed on these surfaces with atomic force microscopy. Clusters that consist of hundreds of thousands of atoms induce long-range modifications in crystalline gold.

A semi-analytical solution for multilayer diffusion in a composite medium consisting of a large number of layers

Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.