Using Micro-Raman Spectroscopy to Assess MEMS Si/SiO2 Membranes Exhibiting Negative Spring Constant Behavior

We introduce a novel micro-mechanical structure that exhibits two regions of stable linear positive and negative stiffness. Springs, cantilevers, beams and any other geometry that display an increasing return force that is proportional to the displacement can be considered to have a “Hookean” positive spring constant, or stiffness. Less well known is the opposite characteristic of a reducing return force for a given deflection, or negative stiffness. Unfortunately many simple negative stiffness structures exhibit unstable buckling and require additional moving components during deflection to avoid deforming out of its useful shape. In Micro-Electro-Mechanical Systems (MEMS) devices, buckling caused by stress at the interface of silicon and thermally grown SiO₂ causes tensile and compressive forces that will warp structures if the silicon layer is thin enough. The 1 mm² membrane structures presented here utilizes this effect but overcome this limitation and empirically demonstrates linearity in both regions. The Si/SiO₂ membranes presented deflect ~17 μm from their pre-released position. The load deflection curves produced exhibit positive linear stiffness with an inflection point holding nearly constant with a slight negative stiffness. Depositing a 0.05 μm titanium and 0.3 μm layer of gold on top of the Si/SiO₂ membrane reduces the initial deflection to ~13.5 μm. However, the load deflection curve produced illustrates both a linear positive and negative spring constant with a fairly sharp inflection point. These results are potentially useful to selectively tune the spring constant of mechanical structures used in MEMS. The structures presented are manufactured using typical micromachining techniques and can be fabricated in-situ with other MEMS devices.     

SRRs Embedded with MEMS Cantilevers to Enable Electrostatic Tuning of the Resonant Frequency

A microelectromechanical systems (MEMS) cantilever array was monolithically fabricated in the gap region of a split ring resonator (SRR) to enable electrostatic tuning of the resonant frequency. The design consisted of two concentric SRRs each with a set of cantilevers extending across the split region. The cantilever array consisted of five beams that varied in length from 300 to 400 μm, with each beam adding about 2 pF to the capacitance as it actuated. The entire structure was fabricated monolithically to reduce its size and minimize losses from externally wire bonded components. The beams actuate one at a time, longest to shortest with an applied voltage ranging from 30–60 V. The MEMS embedded SRRs displayed dual resonant frequencies at 7.3 and 14.2 GHz or 8.4 and 13.5 GHz depending on the design details. As the beams on the inner SRR actuated the 14.2 GHz resonance displayed tuning, while the cantilevers on the outer SRR tuned the 8.4 GHz resonance. The 14.2 GHz resonant frequency shifts 1.6 GHz to 12.6 GHz as all the cantilevers pulled-in. Only the first two beams on the outer cantilever array pulled-in, tuning the resonant frequency 0.4 GHz from 8.4 to 8.0 GHz.     

Fabrication Process Comparison and Dynamics Evaluation of Electrothermal Actuators for a Prototype MEMS Safe and Arming Devices

Electrothermal actuators fabricated using the Polysilicon Multi-User MEMS Process (PolyMUMPs) and the Sandia Ultra-Planar, Multi-Level MEMS Technology 5 (SUMMiT V) have been investigated for use in integrated microelectromechanical systems (MEMS) safe and arming devices. The fabricated electrothermal actuators have been dynamically tested to determine and compare the responses of devices from both processes. Furthermore, the integration of these devices into a safe and arming device were tested and investigated for each process. Initial results indicate that the SUMMiT devices provide the most optimum results based on consistency of operation and reliability.     

Stress Monitoring of Post-processed MEMS Silicon Microbridge Structures Using Raman Spectroscopy

Inherent residual stresses during material deposition can have profound effects on the functionality and reliability of fabricated Micro-Electro-Mechanical Systems (MEMS) devices. Residual stress often causes device failure due to curling, buckling, or fracture. Typically, the material properties of thin films used in surface micromachining are not well controlled during deposition. The residual stress; for example, tends to vary significantly for different deposition methods. Currently, few nondestructive techniques are available to measure residual stress in MEMS devices prior to the final release etch. In this research, micro-Raman spectroscopy is used to measure the residual stresses in polysilicon MEMS microbridge devices. This measurement technique was selected since it is nondestructive, fast, and provides the potential for in-situ stress monitoring. Raman spectroscopy residual stress profiles on unreleased and released MEMS microbridge beams are compared to analytical and FEM models to assess the viability of micro-Raman spectroscopy as an in-situ stress measurement technique. Raman spectroscopy was used during post-processing phosphorus ion implants on unreleased MEMS devices to investigate and monitor residual stress levels at key points during the post-processing sequences. As observed through Raman stress profiles and verified using on-chip test structures, the post-processing implants and accompanying anneals resulted in residual stress relaxation of over 90%.     

Signal-to-noise ratio enhancement based on wavelet filtering in ultrasonic testing

In ultrasonic non-destructive testing of materials with a coarse-grained structure the scattering from the grains causes backscattering noise, which masks flaw echoes in the measured signal. Several filtering methods have been proposed for improving the signal-to-noise ratio. In this paper we present a comparative study of methods based on the wavelet transform. Experiments with stationary, discrete and wavelet packet de-noising are evaluated by means of signal-to-noise ratio enhancement. Measured and simulated ultrasonic signals are used to verify the proposed de-noising methods. For comparison, we use signal-to-noise ratio enhancement related to fault echo amplitudes and filtering efficiency specific for ultrasonic signals. The best results in our setup were achieved with the wavelet packet de-noising method.