Investigation of charge carrier depletion in freestanding nanowires by a multi-probe scanning tunneling microscope

Profiling of the electrical properties of nanowires (NWs) and NW heterocontacts with high spatial resolution is a challenge for any application and advanced NW device development. For appropriate NW analysis, we have established a four-point prober, which is combined in vacuo with a state-of-the-art vapor-liquid-solid preparation, enabling contamination-free NW characterization with high spatial resolution. With this ultrahigh-vacuum-based multi-tip scanning tunneling microscopy (MT-STM), we obtained the resistance and doping profiles of freestanding NWs, along with surface-sensitive information. Our in-system 4-probe STM approach decreased the detection limit for low dopant concentrations to the depleted case in upright standing NWs, while increasing the spatial resolution and considering radial depletion regions, which may originate from surface changes. Accordingly, the surface potential of oxide-free GaAs NW {112} facets has been estimated to be lower than 20 mV, indicating a NW surface with very low surface state density.

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High-resolution venography of the brain using magnetic resonance imaging

The purpose of this study was to evaluate a non-flow related magnetic resonance imaging method to visualize small veins independent of arteries in the human brain. A long TE, high-resolution 3D gradient echo MR acquisition was used to highlight venous information. The method is based on the paramagnetic property of deoxyhemoglobin and the resulting phase difference between veins and brain parenchyma at long echo times. The MR magnitude images were masked with a phase mask filter to enhance small structure visibility.. Venous information down to sub-pixel vessel diameters of several hundred microns is visible. Venous data are displayed in an angiographic manner using a minimum intensity projection algorithm. Both superficial veins and deep white matter veins are visible. The method has been successfully applied in volunteers. Preliminary results in patients with cerebral arteriovenous malformations indicate its potential in clinical applications. The proposed method is easy to implement and does not require administration of a contrast agent or application of specially designed rf pulses to highlight the veins. Rather it exploits the intrinsic magnetic properties (BOLD-effect) and the prolonged T ^_2* of venous blood. The method may be of diagnostic potential in the assessment of arteriovenous malformations or other vascular venous lesions. © 1998 Elsevier Science B.V. All rights reserved.     

Pressure dependence of superconductivity in Ba4C60

In Ba_xC₆₀ superconductivity (sc) at T_c=(6.8±0.2) K is associated with the x=4 phase. Here we present pressure studies of T_c of a Ba_xC₆₀ sample (dT_c/dp= –1.9 K/GPa) which exhibits a large volume fraction of the x=4 phase. In the alkali-fullerides K₆₀C₆₀ and Rb₃C₆₀ T_c is governed by the electronic density of states N(E_F) (T_c exp{–1/N(E_F)V}). The dependence of N(E_F) on volume can be approximated by N(E_F)=N₀ d _eff ³, where d_eff is the surface to surface distance of neighboured C₆₀-molecules. This relationship is corroborated by (T_C,d)-data of various compounds of the form A_3–xB_xC₆₀ (A: K, Rb; B: K, Rb, Cs; x2). Strong deviation from this behavior is found for the alkaline-fulleride superconductor Ba₄C₆₀. This deviation is attributed to the hybridization of alkaline-metal s-, d-states and C₆₀ -states.     

Combination problems for commutative/monoidal theories or how algebra can help in equational unification

We study the class of theories for which solving unification problems is equivalent to solving systems of linear equations over a semiring. It encompasses important examples like the theories of Abelian monoids, idempotent Abelian monoids, and Abelian groups. This class has been introduced by the authors independently of each other as commutative theories (Baader) and monoidal theories (Nutt).We show that commutative theories and monoidal theories indeed define the same class (modulo a translation of the signature), and we prove that it is undecidable whether a given theory belongs to it. In the remainder of the paper we investigate combinations of commutative/monoidal theories with other theories. We show that finitary commutative/monoidal theories always satisfy the requirements for applying general methods developed for the combination of unification algorithms for disjoint equational theories.Then we study the adjunction of monoids of homomorphisms to commutative/monoidal theories. This is a special case of a non-disjoint combination, which has an algebraic counterpart in the corresponding semiring. By studying equations over this semiring, we identify a large subclass of commutative/monoidal theories that are of unification type zero. We also show with methods from linear algebra that unitary and finitary commutative/monoidal theories do not change their unification type when they are augmented by a finite monoid of homomor-phisms, and how algorithms for the extended theory can be obtained from algorithms for the basic theory.     

Associating visual textures with human perceptions using genetic algorithms

This paper deals with an approach allowing to associate visual textures with given human perceptions. Hereby, based on a forward model associating human perceptions for given visual textures, the deduction of an reverse process is presented which is able to associate and characterize visual textures for given human perceptions. For doing so, we propose a constraint-based genetic algorithm approach, which is able to minimize a specific optimization problem containing constraints in form of band-widths for valid individuals (low level features extracted from textures) in a population. The constraints are determined by relationships between (low level) features characterizing textures in form of high-dimensional approximation models. Additionally, in each iteration step checking for valid individuals is carried out with a texture/non-texture classifier or by using a convex hull over a set of valid textures. The whole approach is evaluated based on a real-world texture set used as a start population in the genetic algorithm and by defining various kinds of human perceptions (for which textures are sought) represented by adjective vectors in the aesthetic space. The generated individuals (low level feature vectors) have a high level of fitness (they are quite close to the pre-defined adjective vectors) and a small distance to the initial population. The textures synthesized based on the generated individuals are visualized and compared with textures synthesized by a time-intensive direct texture mixing and re-combination method based on a real-world texture data base.     

Parallel machine problems with equal processing times: a survey

The basic scheduling problem we are dealing with is the following. There are n jobs, each requiring an identical execution time. All jobs have to be processed on a set of parallel machines. Preemptions can be either allowed or forbidden. The aim is to construct a feasible schedule such that a given criterion is minimized. In this paper, we survey existing approaches for the problem class considered.     

Crease Surfaces: From Theory to Extraction and Application to Diffusion Tensor MRI

Crease surfaces are two-dimensional manifolds along which a scalar field assumes a local maximum (ridge) or a local minimum (valley) in a constrained space. Unlike isosurfaces, they are able to capture extremal structures in the data. Creases have a long tradition in image processing and computer vision, and have recently become a popular tool for visualization. When extracting crease surfaces, degeneracies of the Hessian (i.e., lines along which two eigenvalues are equal) have so far been ignored. We show that these loci, however, have two important consequences for the topology of crease surfaces: First, creases are bounded not only by a side constraint on eigenvalue sign, but also by Hessian degeneracies. Second, crease surfaces are not, in general, orientable. We describe an efficient algorithm for the extraction of crease surfaces which takes these insights into account and demonstrate that it produces more accurate results than previous approaches. Finally, we show that diffusion tensor magnetic resonance imaging (DT-MRI) stream surfaces, which were previously used for the analysis of planar regions in diffusion tensor MRI data, are mathematically ill-defined. As an example application of our method, creases in a measure of planarity are presented as a viable substitute.     

Estimating body shape of dressed humans

The paper presents a method to estimate the detailed 3D body shape of a person even if heavy or loose clothing is worn. The approach is based on a space of human shapes, learned from a large database of registered body scans. Together with this database we use as input a 3D scan or model of the person wearing clothes and apply a fitting method, based on ICP (iterated closest point) registration and Laplacian mesh deformation. The statistical model of human body shapes enforces that the model stays within the space of human shapes. The method therefore allows us to compute the most likely shape and pose of the subject, even if it is heavily occluded or body parts are not visible. Several experiments demonstrate the applicability and accuracy of our approach to recover occluded or missing body parts from 3D laser scans.     

Animating Pictures of Fluid using Video Examples

We propose a system that allows the user to design a continuous flow animation starting from a still fluid image. The basic idea is to apply the fluid motion extracted from a video example to the target image. The system first decomposes the video example into three components, an average image, a flow field and residuals. The user then specifies equivalent information over the target image. The user manually paints the rough flow field, and the system automatically refines it using the estimated gradients of the target image. The user semi-automatically transfers the residuals onto the target image. The system then approximates the average image and synthesizes an animation on the target image by adding the transferred residuals and warping them according to the user-specified flow field. Finally, the system adjusts the appearance of the resulting animation by applying histogram matching. We designed animations of various pictures, such as rivers, waterfalls, fires, and smoke.     

Study on TSV isolation liners for a Via Last approach with the use in 3D-WLP for MEMS

This paper discusses approaches for the isolation of deep high aspect ratio through silicon vias (TSV) with respect to a Via Last approach for micro-electro-mechanical systems (MEMS). Selected TSV samples have depths in the range of 170…270 µm and a diameter of 50 µm. The investigations comprise the deposition of different layer stacks by means of subatmospheric and plasma enhanced chemical vapour deposition (PECVD) of tetraethyl orthosilicate; Si(OC₂H₅)₄ (TEOS). Moreover, an etch-back approach and the selective deposition on SiN were also included in the investigations. With respect to the Via Last approach, the contact opening at the TSV bottom by means of a specific spacer-etching method have been addressed within this paper. Step coverage values of up to 74 % were achieved for the best of those approaches. As an alternative to the SiO₂-isolation liners a polymer coating based on the CVD of Parylene F was investigated, which yields even higher step coverage in the range of 80 % at the lower TSV sidewall for a surface film thickness of about 1000 nm. Leakage current measurements were performed and values below 0.1 nA/cm² at 10 kV/cm were determined for the Parylene F films which represents a promising result for the aspired application to Via Last MEMS-TSV.