In this paper, we present design, fabrication, and test results of a novel wavelength-selective MEMS switch for integrated optics. The device is based on switching of a ring resonator add-drop filter by use of an electrostatically-actuated MEMS bridge. We have demonstrated the wavelength-dependant switching capabilities of a prototype device; however, the residual stress in the bridge caused sagging of the bridge and high insertion loss to the optical output. Therefore, we are investigating the use of titanium nitride (TiN) for the MEMS bridge material. TiN has ideal characteristics both mechanically and electrically. It can also be annealed to lower the residual stress to almost zero. We have fabricated the MEMS bridge with TiN and done some preliminary experiments on the structure. The results show promise for the use of this material in our device, and more generally as a structural material. We have also designed closed-loop feedback control for precision positioning of the bridge. This enables this device to tune the selected wavelength over one full channel (30nm) for use as a tunable optical filter. The feedback scheme is based on using the bridge as one electrode of a capacitive sensor, and simulations indicate that the bridge position can be controlled to 2.5pm accuracy. Modifications of the device could also be used as a variable optical attenuator.
The purpose of this study is to present a method of material design of functionally graded material (FGM) plate exhibiting the functions of absorption and shield of plane electromagnetic wave under thermal environment. The FGM plate is divided into n homogeneous layers, which have distinct, constant electromagnetic properties, and then the approximate analytical solutions are derived for reflection attenuation and shielding effect. The numerical calculations are carried out for the FGM plate with the graded complex permittivity expressed in the form of power function.
The present paper deals with measurements of the diffusion coefficients as well as the saturated solubilities of single component gases such as N(2), O(2) and CO(2) to a mineral oil. The method to determine the diffusivity is based upon measuring the pressure changes caused by the one-dimensional diffusion between the gas and the oil enclosed in an airtight container. For N(2) and O(2) the profiles of the measured pressure changes agree well with those predicted by diffusion theory, whereas that is not the case with CO(2). Although the reason why CO(2) does not seem to obey diffusion theory has yet to be studied, it may suggest the possibility that the diffusion coefficient varies with the pressure, considering that the range of pressure change in the diffusivity measurement was much obtained by this method fell within ±30% around the average. Moreover the solubility measurements have made clear that Henry's law holds true between the three pure gases and the oils tested, and that O(2) and CO(2) dissolve into the oil approximately two and ten times more, respectively, than N(2).
Recently the design of experiments is used to decide optimum processing conditions. However when the control factor interaction between the several control factors becomes large, the calculated accuracy using the design of experiments becomes very bad. Then everybody should check the results regarding the best and the worst conditions in the experiments. If differences between the calculated vale and the experimental value for the best and the worst conditions become large, the results using the design of experiments are never used. Therefore, in the previous research, we have developed the tool for easily finding the control factor interaction in the design of experiments. This control factor interaction between the several control factors action is large fault, an obstacle for innovation and disliked by everybody. However when the reaction between the several control factors becomes large effect which is surpassed the estimate, the control factor interaction becomes the synergistic effect which is liked by everybody, the synergistic effect finally brings large profit, excellent license and innovation. Therefore in this research, the tool for easily finding the synergistic effects between the control factors was developed and evaluated using the program in the previous research. The program was the tool for finding the control factor interaction in the design of experiments, it was improved for the easily finding the synergistic effects by using the new algorithm, and was evaluated by the several mathematical models and the experiment. It is concluded from the result that (1) the new program can clear the synergistic effects between the control factors, (2) the program also can clear the complex multiplier effects and (3) the program can clear the synergistic effects with innovative profit in the actual example.
