Ultralow Expansion Glass as Material for Advanced Micromechanical Systems

Ultralow expansion (ULE) glasses are of special interest for temperature stabilized systems for example in precision metrology. Nowadays, ULE materials are mainly used in macroscopic and less in micromechanical systems. Reasons for this are a lack of technologies for parallel fabricating high-quality released microstructures with a high accuracy. As a result, there is a high demand in transferring these materials into miniaturized application examples, realistic system modeling, and the investigation of microscopic material properties. Herein, a technological base for fabricating released micromechanical structures and systems with a structure height above 100 μm in ULE 7972 glass is established. Herein, the main fabrication parameters that are important for the system design and contribute thus to the introduction of titanium silicate as material for glass-based micromechanical systems are discussed. To study the mechanical properties in combination with respective simulation models, microcantilevers are used as basic mechanical elements to evaluate technological parameters and other impact factors. The implemented models allow to predict the micromechanical system properties with a deviation of only ±5% and can thus effectively support the micromechanical system design in an early stage of development.     

A Study of a Convex Variational Diffusion Approach for Image Segmentation and Feature Extraction

We analyze a variational approach to image segmentation that is based on a strictly convex non-quadratic cost functional. The smoothness term combines a standard first-order measure for image regions with a total-variation based measure for signal transitions. Accordingly, the costs associated with discontinuities are given by the length of level lines and local image contrast. For real images, this provides a reasonable approximation of the variational model of Mumford and Shah that has been suggested as a generic approach to image segmentation.The global properties of the convex variational model are favorable to applications: Uniqueness of the solution, continuous dependence of the solution on both data and parameters, consistent and efficient numerical approximation of the solution with the FEM-method.Various global and local properties of the convex variational model are analyzed and illustrated with numerical examples. Apart from the favorable global properties, the approach is shown to provide a sound mathematical model of a useful locally adaptive smoothing process. A comparison is carried out with results of a region-growing technique related to the Mumford-Shah model.     

The first measurement of an absolute surface concentration of reaction intermediates in ethylene hydrogenation

The first measurement of a turnover rate with respect to surface intermediate concentration in a high pressure heterogeneous catalytic reaction is reported. By using infrared-visible sum frequency generation to study the hydrogenation of ethylene on Pt(111), it was found that the surface concentration of -bonded ethylene, the key reaction intermediate, represented approximately 4% of a monolayer. Thus the absolute turnover rate per surface adsorbed ethylene molecule is 25 times faster than the rate measured per platinum atom. To explain these results, we propose a model of weakly adsorbed ethylene intermediates reacting on atop sites.     

Controlling patterns of geospatial phenomena

Modeling spatially distributed phenomena in terms of its controlling factors is a recurring problem in geoscience. Most efforts concentrate on predicting the value of response variable in terms of controlling variables either through a physical model or a regression model. However, many geospatial systems comprises complex, nonlinear, and spatially non-uniform relationships, making it difficult to even formulate a viable model. This paper focuses on spatial partitioning of controlling variables that are attributed to a particular range of a response variable. Thus, the presented method surveys spatially distributed relationships between predictors and response. The method is based on association analysis technique of identifying emerging patterns, which are extended in order to be applied more effectively to geospatial data sets. The outcome of the method is a list of spatial footprints, each characterized by a unique “controlling pattern”—a list of specific values of predictors that locally correlate with a specified value of response variable. Mapping the controlling footprints reveals geographic regionalization of relationship between predictors and response. The data mining underpinnings of the method are given and its application to a real world problem is demonstrated using an expository example focusing on determining variety of environmental associations of high vegetation density across the continental United States.     

The physiological mirror—a system for unconscious control of a virtual environment through physiological activity

This paper introduces a system for real-time physiological measurement, analysis, and metaphorical visualization within a virtual environment (VE). Our goal is to develop a method that allows humans to unconsciously relate to parts of an environment more strongly than to others, purely induced by their own physiological responses to the virtual reality (VR) displays. In particular, we exploit heart rate, respiration, and galvanic skin response in order to control the behavior of virtual characters in the VE. Such unconscious processes may become a useful tool for storytelling or assist guiding participants through a sequence of tasks in order to make the application more interesting, e.g., in rehabilitation. We claim that anchoring of subjective bodily states to a virtual reality (VR) can enhance a person’s sense of realism of the VR and ultimately create a stronger relationship between humans and the VR.     

Study on the replication quality of micro-structures in the injection molding process with dynamical tool tempering systems

The injection molding of micro-structures is a promising mass-production method for a broad range of materials. However, the replication quality of these structures depends significantly on the heat flow during the filling stage. In this paper, the filling and heat transfer of v-groove and random structures below 5 μm is investigated with the help of an AFM (atomic force microscope) and thermo couples. A numerical model is developed to predict the filling of surface structures during the filling and packing stage. The model implies the use of simple fully developed flow models taking the power-law material model into account. This permits investigation into which ways several processing parameters affect the polymer flow in the surface structures. The mold wall temperature, which has significant effects on the polymer flow, is varied by using a variothermal mold temperature control system to validate the model proposed.