Muhammad Mubasher Saleem

Modeling and experimental verification of thermally induced residual stress in RF-MEMS

Electrostatically actuated radio frequency microelectromechanical systems (RF-MEMS) generally consist of microcantilevers and clamped–clamped microbeams. The presence of residual stress in these microstructures affects the static and dynamic behavior of the device. In this study, nonlinear finite element method (FEM) modeling and the experimental validation of residual stress induced in the clamped–clamped microbeams and the symmetric toggle RF-MEMS switch (STS) is presented. The formation of residual stress due to plastic deformation during the thermal loading-unloading cycle in the plasma etching step of the microfabrication process is explained and modeled using the Bauschinger effect. The difference between the designed and the measured natural frequency and pull-in voltage values for the clamped–clamped microbeams is explained by the presence of the nonhomogenous tensile residual stress. For the STS switch specimens, three-dimensional (3D) FEM models are developed and the initial deflection at zero bias voltage, observed during the optical profile measurements, is explained by the residual stress developed during the plasma etching step. The simulated residual stress due to the plastic deformation is included in the STS models to obtain the switch pull-in voltage. At the end of the simulation process, a good correspondence is obtained between the FEM model results and the experimental measurements for both the clamped–clamped microbeams and the STS switch specimens.

Dissolved Concentrations, Sources, and Risk Evaluation of Selected Metals in Surface Water from Mangla Lake, Pakistan

The present study is carried out for the assessment of water quality parameters and selected metals levels in surface water from Mangla Lake, Pakistan. The metal levels (Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Sr, and Zn) were determined by flame atomic absorption spectrophotometry. Average levels of Cd, Co, Cr, Ni, and Pb were higher than the allowable concentrations set by national and international agencies. Principal component analysis indicated significant anthropogenic contributions of Cd, Co, Cr, Ni, and Pb in the water reservoir. Noncarcinogenic risk assessment was then evaluated using Hazard Quotient (HQing/derm) and Hazard Index (HIing/derm) following USEPA methodology. For adults and children, Cd, Co, Cr, and Pb (HQing > 1) emerged as the most important pollutants leading to noncarcinogenic concerns via ingestion route, whereas there was no risk via dermal contact of surface water. This study helps in establishing pollutant loading reduction goal and the total maximum daily loads, and consequently contributes to preserve public health and develop water conservation strategy.

Multiphysics design optimization of RF-MEMS switch using response surface methodology

Abstract This paper presents the multi-objective geometric design exploration and optimization of an electrostatic Symmetric Toggle RF-MEMS switch (STS), considering both the electromechanical and RF characteristics simultaneously. The output responses considered for the STS switch optimization are pull-in voltage, switching time, insertion loss in the on-state and isolation in the off-state. Metamodels for the output responses, with respect to geometric design parameters, are developed using Design of Experiments (DOE) based Response Surface Methodology (RSM) and Finite Element Method (FEM) simulations. A single optimization objective function, considering all the four output responses and microfabrication process constraints, is defined and optimized for the design factors using combined desirability function and heuristic search algorithm approach. The predicted values of the output responses are verified through both the electromechanical and electromagnetic FEM simulations. The effect of residual stress, developed in the RF-MEMS switch during the sacrificial layer removal step of the microfabrication process, on both the electromechanical and RF characteristics of the final optimized switch geometry is analyzed using coupled structural-thermal-electric FEM simulations. The proposed DOE and RSM based design optimization technique can be implemented for the design space exploration and optimization of complex MEMS devices which involve coupled multiphysics interactions.

Design optimization of RF-MEMS switch considering thermally induced residual stress and process uncertainties

Abstract This paper presents the Design of Experiments (DOE) based parametric design optimization of the Symmetric Toggle RF-MEMS Switch (STS) for minimizing the actuation voltage considering the fabrication process uncertainties and thermally induced residual stress. Initially, three-dimensional (3D) non-linear Finite Element Method (FEM) models are developed and the formation of residual stress during the plasma etching step of the microfabrication process is explained using the Bauschinger effect. The pull-in voltage values and the switch profiles obtained after the thermal loading–unloading cycle in the FEM models are compared with the experimental values and optical profile measurements which showed a close agreement. A DOE based Dual Response Surface Methodology (DRSM) is implemented to identify the significant design parameters affecting the STS switch pull-in voltage in the presence of thermally induced residual stress. Two separate response surface empirical models are developed; one for the mean pull-in voltage and other for variation in the pull-in voltage due to microfabrication process tolerances. The developed response surface models are optimized simultaneously using the desirability function approach. The optimal levels of the design parameters that result in minimum pull-in voltage with increased insensitivity to process uncertainties are obtained using the direct search algorithm.

Multi-Response Optimization of Electrothermal Micromirror Using Desirability Function-Based Response Surface Methodology

The design of a micromirror for biomedical applications requires multiple output responses to be optimized, given a set of performance parameters and constraints. This paper presents the parametric design optimization of an electrothermally actuated micromirror for the deflection angle, input power, and micromirror temperature rise from the ambient for Optical Coherence Tomography (OCT) system. Initially, a screening design matrix based on the Design of Experiments (DOE) technique is developed and the corresponding output responses are obtained using coupled structural-thermal-electric Finite Element Modeling (FEM). The interaction between the significant design factors is analyzed by developing Response Surface Models (RSM) for the output responses. The output responses are optimized by combining the individual responses into a composite function using desirability function approach. A downhill simplex method, based on the heuristic search algorithm, is implemented on the RSM models to find the optimal levels of the design factors. The predicted values of output responses obtained using multi-response optimization are verified by the FEM simulations.

Design and FEM modeling of notch effect in gold microbeams

This paper presents the design and modeling of the MEMS mechanical fatigue in the presence of stress raising notches. FEM models are realized to study the effect of notch geometric parameters on the stress concentration factor of the gold specimen subjected to tensile loading. Test structures with three different specimens, i.e. without notch, with single notch and with a double notch are modeled considering fabrication process constraints. Maximum axial stresses produced in the specimens and the corresponding stress concentration factors for the notched specimens are obtained using FEM modeling.

Network weight adjustment in a fractional fourier transform based multi-channel brain computer interface for person authentication

Brain is composed of unique complex neural structure thus electrical activity between neurons referred to as electroencephalogram (EEG) in different brain regions varies from one user to another. In this paper EEG distinctiveness is exploited through application to person authentication system based on five mental imagery tasks. Seven electrodes placed at C3, C4, P3, P4, O1, O2 and EOG are used to record EEG signals. A parallel structure of Exact Radial Basis (RBE) neural networks are used as classifiers. Individual classifier response for each mental task is evaluated and a weighting approach is used to regulate contribution of each channel within a multi-channel Brain Computer Interface (BCI) system. The estimated and experimental results indicate an average increase of 14% in system performance when tested on 722 trials of 1sec duration for 7 subjects. Fractional Fourier Transform (FRFT) with order optimization is used for feature extraction, and special one dimensional case of k-means clustering algorithm is used to calculate the threshold for individual classifiers.

Efficient FIR Filter Implementations for Multichannel BCIs Using Xilinx System Generator

Background. Brain computer interface (BCI) is a combination of software and hardware communication protocols that allow brain to control external devices. Main purpose of BCI controlled external devices is to provide communication medium for disabled persons. Now these devices are considered as a new way to rehabilitate patients with impunities. There are certain potentials present in electroencephalogram (EEG) that correspond to specific event. Main issue is to detect such event related potentials online in such a low signal to noise ratio (SNR). In this paper we propose a method that will facilitate the concept of online processing by providing an efficient filtering implementation in a hardware friendly environment by switching to finite impulse response (FIR). Main focus of this research is to minimize latency and computational delay of preprocessing related to any BCI application. Four different finite impulse response (FIR) implementations along with large Laplacian filter are implemented in Xilinx System Generator. Efficiency of 25% is achieved in terms of reduced number of coefficients and multiplications which in turn reduce computational delays accordingly.

Experimental characterization of elastic-plastic behavior of MEMS electroplated gold specimens

This paper presents the design, FEM modeling and experimental characterization of the elastic-plastic behavior of electroplated gold specimens undergoing tensile loading. The test structures are designed and optimized to achieve high stress values in the double-clamped specimen with a rectangular cross-section in the middle of the test structure. High stresses in the specimen are achieved by using electrostatic actuation to the plates, constrained using hinges. The range of electrostatic actuation is increased using bottom partial-plate electrodes on the substrate. The static deflection of the central specimen in the test structures under multiple loading cycles is obtained using experimental characterization and a change in the static pull-in voltage with each loading cycle is observed evaluating the permanent strain due to plasticity.

Effect of residual stress on electromagnetic characteristics of capacitive RFMEMS Switch

This paper presents the effect of the thermally induced residual stress on the RF characteristics of capacitive shunt Symmetric Toggle MEMS Switch (STS). The formation of residual stress is attributed to the thermal loading-unloading cycle of the switch at high temperatures during microfabrication process. Initially, 3D nonlinear FEM models are developed to simulate the thermal loading cycle and resultant deflection profile and induced residual stress are obtained. The STS switch is modeled in a shunt configuration on a 50Ω coplanar transmission line and corresponding scattering parameters (S-parameters) are obtained with and without considering residual stress. The RF characteristics has been improved due to the presence of the residual stress for the STS switch considered in this work.