Semiclassical theory of shot noise in ballistic n+in+ semiconductor structures: relevance of Pauli and long range Coulomb interactions

We work out a semiclassical theory of shot noise in ballistic n+-i-n+ semiconductor structures aiming at studying two fundamental physical correlations coming from Pauli exclusion principle and long-range Coulomb interaction. The theory provides a unifying scheme which, in addition to the current-voltage characteristics, describes the suppression of shot noise due to Pauli and Coulomb correlations in the whole range of system parameters and applied bias. The whole scenario is summarized by a phase diagram in the plane of two dimensionless variables related to the sample length and contact chemical potential. Here different regions of physical interest can be identified where only Coulomb or only Pauli correlations are active, or where both are present with different relevance. The predictions of the theory are proven to be fully corroborated by Monte Carlo simulations.

Raman microstructural analysis of silicon-on-insulator formed by high dose oxygen ion implantation: As-implanted structures

A microstructural analysis of silicon-on-insulator samples obtained by high dose oxygen ion implantation was performed by Raman scattering. The samples analyzed were obtained under different conditions thus leading to different concentrations of defects in the top Si layer. The samples were implanted with the surface covered with SiO2 capping layers of different thicknesses. The spectra measured from the as-implanted samples were fitted to a correlation length model taking into account the possible presence of stress effects in the spectra. This allowed quantification of both disorder effects, which are determined by structural defects, and residual stress in the top Si layer before annealing. These data were correlated to the density of dislocations remaining in the layer after annealing. The analysis performed corroborates the existence of two mechanisms that generate defects in the top Si layer that are related to surface conditions during implantation and the proximity of the top Si/buried oxide layer interface to the surface before annealing.

Evaluation of PCC Long-Term Durability Using Intermediate Sized Gravels to Optimize Mix Gradations, April 2010

With the implementation of the 2000 Q-MC specification, an incentive is provided to produce an optimized gradation to improve placement characteristics. Also, specifications for slip-formed barrier rail have changed to require an optimized gradation. Generally, these optimized gradations have been achieved by blending an intermediate aggregate with the coarse and fine aggregate. The demand for this intermediate aggregate has been satisfied by using crushed limestone chips developed from the crushing of the parent concrete stone. The availability, cost, and physical limitations of crushed limestone chips can be a concern. A viable option in addressing these concerns is the use of gravel as the intermediate aggregate. Unfortunately, gravels of Class 3I durability are limited to a small geographic area in Mississippi river sands north of the Rock River. Class 3 or Class 2 durability gravels are more widely available across the state. The durability classification of gravels is based on the amount and quality of the carbonate fraction of the material. At present, no service histories or research exists to assess the impact of using Class 3 or 2 durability gravels would have on the long-term durability of Portland cement concrete (PCC) pavement requiring Class 3I aggregate.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Analysis of micro- and nano-structures of the corneal surface of Drosophila and its mutants by atomic force microscopy and optical diffraction.

Drosophila melanogaster is a model organism instrumental for numerous biological studies. The compound eye of this insect consists of some eight hundred individual ommatidia or facets, ca. 15 µm in cross-section. Each ommatidium contains eighteen cells including four cone cells secreting the lens material (cornea). High-resolution imaging of the cornea of different insects has demonstrated that each lens is covered by the nipple arrays--small outgrowths of ca. 200 nm in diameter. Here we for the first time utilize atomic force microscopy (AFM) to investigate nipple arrays of the Drosophila lens, achieving an unprecedented visualization of the architecture of these nanostructures. We find by Fourier analysis that the nipple arrays of Drosophila are disordered, and that the seemingly ordered appearance is a consequence of dense packing of the nipples. In contrast, Fourier analysis confirms the visibly ordered nature of the eye microstructures--the individual lenses. This is different in the frizzled mutants of Drosophila, where both Fourier analysis and optical imaging detect disorder in lens packing. AFM reveals intercalations of the lens material between individual lenses in frizzled mutants, providing explanation for this disorder. In contrast, nanostructures of the mutant lens show the same organization as in wild-type flies. Thus, frizzled mutants display abnormal organization of the corneal micro-, but not nano-structures. At the same time, nipples of the mutant flies are shorter than those of the wild-type. We also analyze corneal surface of glossy-appearing eyes overexpressing Wingless--the lipoprotein ligand of Frizzled receptors, and find the catastrophic aberration in nipple arrays, providing experimental evidence in favor of the major anti-reflective function of these insect eye nanostructures. The combination of the easily tractable genetic model organism and robust AFM analysis represents a novel methodology to analyze development and architecture of these surface formations.

Surface collective oscillations of metal clusters and spheres: Random-phase-approximation sum-rules approach

Using the once and thrice energy-weighted moments of the random-phase-approximation strength function, we have derived compact expressions for the average energy of surface collective oscillations of clusters and spheres of metal atoms. The L=0 volume mode has also been studied. We have carried out quantal and semiclassical calculations for Na and Ag systems in the spherical-jellium approximation. We present a rather thorough discussion of surface diffuseness and quantal size effects on the resonance energies.

Static dipole polarizability of alkali-metal clusters: Electronic exchange and correlation effects

Nonlocal approximations for the electronic exchange and correlation effects are used to compute, within density-functional theory, the polarizability and surface-plasma frequencies of small jelliumlike alkali-metal clusters. The results are compared with those obtained using the local-density approximation and with available experimental data, showing the relevance of these effects in obtaining an accurate description of the surface response of metallic clusters.

Barrier for the reaction X20+ + X20+ -> X402+ in alkali-metal clusters related to electron density at the bond midpoint of the supermolecule (X20+)2

Using the extended Thomas-Fermi version of density-functional theory (DFT), calculations are presented for the barrier for the reaction Na20++Na20+¿Na402+. The deviation from the simple Coulomb barrier is shown to be proportional to the electron density at the bond midpoint of the supermolecule (Na20+)2. An extension of conventional quantum-chemical studies of homonuclear diatomic molecular ions is then effected to apply to the supermolecular ions of the alkali metals. This then allows the Na results to be utilized to make semiquantitative predictions of position and height of the maximum of the fusion barrier for other alkali clusters. These predictions are confirmed by means of similar DFT calculations for the K clusters.

Influence of configurational atomic order on the relative stability of bcc and close-packed structures in Cu-based alloys

We present a study of the influence of atomic order on the relative stability of the bcc and the 18R martensitic structures in a Cu2.96Al0.92Be0.12 crystal. Calorimetric measurements have shown that disorder increases the stability of the 18R phase, contrary to what happens in Cu-Zn-Al alloys for which it is the bcc phase that is stabilized by disordering the system. This different behavior has been explained in terms of a model recently reported. We have also proved that the entropy change at the martensitic transition is independent of the state of atomic order of the crystal, as predicted theoretically. Our results suggest that differences in the vibrational spectrum of the crystal due to different states of atomic order must be equal in the bcc and in the close-packed phases.

Two-dimensional clusters of liquid 4He

The binding energies of two-dimensional clusters (puddles) of¿4He are calculated in the framework of the diffusion Monte Carlo method. The results are well fitted by a mass formula in powers of x=N-1/2, where N is the number of particles. The analysis of the mass formula allows for the extraction of the line tension, which turns out to be 0.121 K/Å. Sizes and density profiles of the puddles are also reported.