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A light-addressable potentiometric sensor (LAPS) can measure the concentration of one or several analytes at the sensor surface simultaneously in a spatially resolved manner. A modulated light pointer stimulates the semiconductor structure at the area of interest and a responding photocurrent can be read out. By simultaneous stimulation of several areas with light pointers of different modulation frequencies, the read out can be performed at the same time. With the new proposed controller electronic based on a field-programmable gate array (FPGA), it is possible to control the modulation frequencies, phase shifts, and light brightness of multiple light pointers independently and simultaneously. Thus, it is possible to investigate the frequency response of the sensor, and to examine the analyte concentration by the determination of the surface potential with the help of current/voltage curves and phase/voltage curves. Additionally, the ability to individually change the light intensities of each light pointer is used to perform signal correction.
In our case the double-side-method is used to minimize the complexity of a matrix-readout. Here the number of channels is reduced to 2√N̅. It is also possible to benefit from the method in a single pixel readout system. One signal can be used to measure position and energy of the event, the other one can be applied to a fast trigger-circuit at the same time. In a next step we will investigate timing behavior and electrical crosstalk of the circuit.
This paper presents a novel numerical procedure for computing limit and shakedown loads of structures using a node-based smoothed FEM in combination with a primal–dual algorithm. An associated primal–dual form based on the von Mises yield criterion is adopted. The primal-dual algorithm together with a Newton-like iteration are then used to solve this associated primal–dual form to determine simultaneously both approximate upper and quasi-lower bounds of the plastic collapse limit and the shakedown limit. The present formulation uses only linear approximations and its implementation into finite element programs is quite simple. Several numerical examples are given to show the reliability, accuracy, and generality of the present formulation compared with other available methods.