Matching Items (8)
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- All Subjects: Microelectromechanical Systems
- Genre: Masters Thesis
- Creators: Bakkaloglu, Bertan
- Creators: Muthuswamy, Jitendran
- Creators: Chakraborty, Bijeta
Description
Micro Electro Mechanical Systems (MEMS) is one of the fastest growing field in silicon industry. Low cost production is key for any company to improve their market share. MEMS testing is challenging since input to test a MEMS device require physical stimulus like acceleration, pressure etc. Also, MEMS device vary with process and requires calibration to make them reliable. This increases test cost and testing time. This challenge can be overcome by combining electrical stimulus based testing along with statistical analysis on MEMS response for electrical stimulus and also limited physical stimulus response data. This thesis proposes electrical stimulus based built in self test(BIST) which can be used to get MEMS data and later this data can be used for statistical analysis. A capacitive MEMS accelerometer is considered to test this BIST approach. This BIST circuit overhead is less and utilizes most of the standard readout circuit. This thesis discusses accelerometer response for electrical stimulus and BIST architecture. As a part of this BIST circuit, a second order sigma delta modulator has been designed. This modulator has a sampling frequency of 1MHz and bandwidth of 6KHz. SNDR of 60dB is achieved with 1Vpp differential input signal and 3.3V supply
ContributorsKundur, Vinay (Author) / Bakkaloglu, Bertan (Committee member) / Ozev, Sule (Committee member) / Kiaei, Sayfe (Committee member) / Arizona State University (Publisher)
Created2013
Description
The applications which use MEMS accelerometer have been on rise and many new fields which are using the MEMS devices have been on rise. The industry is trying to reduce the cost of production of these MEMS devices. These devices are manufactured using micromachining and the interface circuitry is manufactured using CMOS and the final product is integrated on to a single chip. Amount spent on testing of the MEMS devices make up a considerable share of the total final cost of the device. In order to save the cost and time spent on testing, researchers have been trying to develop different methodologies. At present, MEMS devices are tested using mechanical stimuli to measure the device parameters and for calibration the device. This testing is necessary since the MEMS process is not a very well controlled process unlike CMOS. This is done using an ATE and the cost of using ATE (automatic testing equipment) contribute to 30-40% of the devices final cost. This thesis proposes an architecture which can use an Electrical Signal to stimulate the MEMS device and use the data from the MEMS response in approximating the calibration coefficients efficiently. As a proof of concept, we have designed a BIST (Built-in self-test) circuit for MEMS accelerometer. The BIST has an electrical stimulus generator, Capacitance-to-voltage converter, ∑ ∆ ADC. This thesis explains in detail the design of the Electrical stimulus generator. We have also designed a technique to correlate the parameters obtained from electrical stimuli to those obtained by mechanical stimuli. This method is cost effective since the additional circuitry needed to implement BIST is less since the technique utilizes most of the existing standard readout circuitry already present.
ContributorsJangala Naga, Naveen Sai (Author) / Ozev, Sule (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Kiaei, Sayfe (Committee member) / Arizona State University (Publisher)
Created2014
Description
Efficiency of components is an ever increasing area of importance to portable applications, where a finite battery means finite operating time. Higher efficiency devices need to be designed that don't compromise on the performance that the consumer has come to expect. Class D amplifiers deliver on the goal of increased efficiency, but at the cost of distortion. Class AB amplifiers have low efficiency, but high linearity. By modulating the supply voltage of a Class AB amplifier to make a Class H amplifier, the efficiency can increase while still maintaining the Class AB level of linearity. A 92dB Power Supply Rejection Ratio (PSRR) Class AB amplifier and a Class H amplifier were designed in a 0.24um process for portable audio applications. Using a multiphase buck converter increased the efficiency of the Class H amplifier while still maintaining a fast response time to respond to audio frequencies. The Class H amplifier had an efficiency above the Class AB amplifier by 5-7% from 5-30mW of output power without affecting the total harmonic distortion (THD) at the design specifications. The Class H amplifier design met all design specifications and showed performance comparable to the designed Class AB amplifier across 1kHz-20kHz and 0.01mW-30mW. The Class H design was able to output 30mW into 16Ohms without any increase in THD. This design shows that Class H amplifiers merit more research into their potential for increasing efficiency of audio amplifiers and that even simple designs can give significant increases in efficiency without compromising linearity.
ContributorsPeterson, Cory (Author) / Bakkaloglu, Bertan (Thesis advisor) / Barnaby, Hugh (Committee member) / Kiaei, Sayfe (Committee member) / Arizona State University (Publisher)
Created2013
Description
Microelectrodes have been used as the neural interface to record brain's neural activities. Most of these electrodes are fixed positioned. Neural signal normally degrades over time due to the body immune response and brain micromotion that move the neurons away from the microelectrode. MEMS technology under SUMMiT VTM processes has developed miniaturized version of moveable microelectrodes that have the ability to recover the neural signal degradation by searching new cluster of neurons. To move the MEMS microelectrode a combination of four voltage waveforms must be applied to four thermally actuated microactuators. Previous design has used OmneticTM interconnect to transfer the waveforms from the external signal generators to the MEMS device. Unfortunately, the mechanism to attach and detach the OmneticTM interconnect introduce mechanical stress into the brain tissue that often caused raptures in the blood vessel. The goal of this project is to create an integrated System-On-Package Signal Generator that can be implanted on the brain of a rodent. A wireless system and a microcontroller are integrated together with the signal generators. The integrated system can be used to generate a series of voltage waveforms that can be customized to drive an array of MEMS movable microelectrodes when a triggered signal is received wirelessly. 3D stacking technique has been used to develop this Integrated System. 3D stacks lead to several favorable factors, such as (a) reduction in the power consumption of the system, (b) reduction in the overall form-factor of the package, and (c) significant reduction the weight of the package. There are a few challenges that must be overcome in this project, such as a commercially available microcontroller normally have an output voltage of 3.3 V to 5.5 V; however, a voltage of 7 - 8V is required to move the MEMS movable microelectrodes. To acquire higher density neural recording, more number of microelectrodes are needed. In this project, SoP Signal Generator is design to drive independently 3 moveable microelectrodes. Therefore, 12 voltage waveform are required. . However, the use of 12 signal generators is not a workable option since the system will be significantly large. This brings us to the other challenge, the limiting size of the rodent brain. Due to this factor, the SoP Signal Generator has to be deisgned to be able to fit without causing much pressure to the rodent's brain. For the first challenge, which is the limited output voltage of 3.3V on the microcontroller, the RC555 timers are used as an amplifier in addition to generating the signals. Demultiplexers have been for the next challenge, which is the need of 24 waveforms to drive 3 electrodes. For each waveform, 1 demultiplexer is used, making a total of 4 demultiplexers used in the entire system, which is a significant improvement from using 12 signal generators. The last challenge can be approached using 3D system stacking technique as mentioned above. The research aims of this project can be described as follows: (1) the testing and realization of the system part, and the designing of the system in a PCB level, (2) implementing and testing the SoP Signal Generator with the MEMS movable microelectrodes, The final outcome of this project can be used not only for neural applications, but also for more general applications that requires customized signal generations and wireless data transmission.
ContributorsTee, Zikai (Author) / Muthuswamy, Jitendran (Thesis advisor) / Sutanto, Jemmy (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2012
Description
There is a tremendous need for wireless biological signals acquisition for the microelectrode-based neural interface to reduce the mechanical impacts introduced by wire-interconnects system. Long wire connections impede the ability to continuously record the neural signal for chronic application from the rodent's brain. Furthermore, connecting and/or disconnecting Omnetics interconnects often introduces mechanical stress which causes blood vessel to rupture and leads to trauma to the brain tissue. Following the initial implantation trauma, glial tissue formation around the microelectrode and may possibly lead to the microelectrode signal degradation. The aim of this project is to design, develop, and test a compact and power efficient integrated system (IS) that is able to (a) wirelessly transmit triggering signal from the computer to the signal generator which supplies voltage waveforms that move the MEMS microelectrodes, (b) wirelessly transmit neural data from the brain to the external computer, and (c) provide an electrical interface for a closed loop control to continuously move the microelectrode till a proper quality of neural signal is achieved. One of the main challenges of this project is the limited data transmission rate of the commercially available wireless system to transmit 400 kbps of digitized neural signals/electrode, which include spikes, local field potential (LFP), and noise. A commercially available Bluetooth module is only capable to transmit at a total of 115 kbps data transfer rate. The approach to this challenge is to digitize the analog neural signal with a lower accuracy ADC to lower the data rate, so that is reasonable to wirelessly transfer neural data of one channel. In addition, due to the limited space and weight bearing capability to the rodent's head, a compact and power efficient integrated system is needed to reduce the packaged volume and power consumption. 3D SoP technology has been used to stack the PCBs in a 3D form-factor, proper routing designs and techniques are implemented to reduce the electrical routing resistances and the parasitic RC delay. It is expected that this 3D design will reduce the power consumption significantly in comparison to the 2D one. The progress of this project is divided into three different phases, which can be outlined as follow: a) Design, develop, and test Bluetooth wireless system to transmit the triggering signal from the computer to the signal generator. The system is designed for three moveable microelectrodes. b) Design, develop, and test Bluetooth wireless system to wirelessly transmit an amplified (200 gain) neural signal from one single electrode to an external computer. c) Design, develop, and test a closed loop control system that continuously moves a microelectrode in searching of an acceptable quality of neural spikes. The outcome of this project can be used not only for the need of neural application but also for a wider and general applications that requires customized signal generations and wireless data transmission.
ContributorsZhou, Li (Author) / Muthuswamy, Jitendran (Thesis advisor) / Sutanto, Jemmy (Thesis advisor) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2012
Description
Class D Amplifiers are widely used in portable systems such as mobile phones to achieve high efficiency. The demands of portable electronics for low power consumption to extend battery life and reduce heat dissipation mandate efficient, high-performance audio amplifiers. The high efficiency of Class D amplifiers (CDAs) makes them particularly attractive for portable applications. The Digital class D amplifier is an interesting solution to increase the efficiency of embedded systems. However, this solution is not good enough in terms of PWM stage linearity and power supply rejection. An efficient control is needed to correct the error sources in order to get a high fidelity sound quality in the whole audio range of frequencies. A fundamental analysis on various error sources due to non idealities in the power stage have been discussed here with key focus on Power supply perturbations driving the Power stage of a Class D Audio Amplifier. Two types of closed loop Digital Class D architecture for PSRR improvement have been proposed and modeled. Double sided uniform sampling modulation has been used. One of the architecture uses feedback around the power stage and the second architecture uses feedback into digital domain. Simulation & experimental results confirm that the closed loop PSRR & PS-IMD improve by around 30-40 dB and 25 dB respectively.
ContributorsChakraborty, Bijeta (Author) / Bakkaloglu, Bertan (Thesis advisor) / Garrity, Douglas (Committee member) / Ozev, Sule (Committee member) / Arizona State University (Publisher)
Created2012
Description
In this thesis, a digital input class D audio amplifier system which has the ability
to reject the power supply noise and nonlinearly of the output stage is presented. The main digital class D feed-forward path is using the fully-digital sigma-delta PWM open loop topology. Feedback loop is used to suppress the power supply noise and harmonic distortions. The design is using global foundry 0.18um technology.
Based on simulation, the power supply rejection at 200Hz is about -49dB with
81dB dynamic range and -70dB THD+N. The full scale output power can reach as high as 27mW and still keep minimum -68dB THD+N. The system efficiency at full scale is about 82%.
to reject the power supply noise and nonlinearly of the output stage is presented. The main digital class D feed-forward path is using the fully-digital sigma-delta PWM open loop topology. Feedback loop is used to suppress the power supply noise and harmonic distortions. The design is using global foundry 0.18um technology.
Based on simulation, the power supply rejection at 200Hz is about -49dB with
81dB dynamic range and -70dB THD+N. The full scale output power can reach as high as 27mW and still keep minimum -68dB THD+N. The system efficiency at full scale is about 82%.
ContributorsBai, Jing (Author) / Bakkaloglu, Bertan (Thesis advisor) / Arizona State University (Publisher)
Created2015
Description
Long-term monitoring of deep brain structures using microelectrode implants is critical for the success of emerging clinical applications including cortical neural prostheses, deep brain stimulation and other neurobiology studies such as progression of disease states, learning and memory, brain mapping etc. However, current microelectrode technologies are not capable enough of reaching those clinical milestones given their inconsistency in performance and reliability in long-term studies. In all the aforementioned applications, it is important to understand the limitations & demands posed by technology as well as biological processes. Recent advances in implantable Micro Electro Mechanical Systems (MEMS) technology have tremendous potential and opens a plethora of opportunities for long term studies which were not possible before. The overall goal of the project is to develop large scale autonomous, movable, micro-scale interfaces which can seek and monitor/stimulate large ensembles of precisely targeted neurons and neuronal networks that can be applied for brain mapping in behaving animals. However, there are serious technical (fabrication) challenges related to packaging and interconnects, examples of which include: lack of current industry standards in chip-scale packaging techniques for silicon chips with movable microstructures, incompatible micro-bonding techniques to elongate current micro-electrode length to reach deep brain structures, inability to achieve hermetic isolation of implantable devices from biological tissue and fluids (i.e. cerebrospinal fluid (CSF), blood, etc.). The specific aims are to: 1) optimize & automate chip scale packaging of MEMS devices with unique requirements not amenable to conventional industry standards with respect to bonding, process temperature and pressure in order to achieve scalability 2) develop a novel micro-bonding technique to extend the length of current polysilicon micro-electrodes to reach and monitor deep brain structures 3) design & develop high throughput packaging mechanism for constructing a dense array of movable microelectrodes. Using a combination of unique micro-bonding technique which involves conductive thermosetting epoxy’s with hermetically sealed support structures and a highly optimized, semi-automated, 90-minute flip-chip packaging process, I have now extended the repertoire of previously reported movable microelectrode arrays to bond conventional stainless steel and Pt/Ir microelectrode arrays of desired lengths to steerable polysilicon shafts. I tested scalable prototypes in rigorous bench top tests including Impedance measurements, accelerated aging and non-destructive testing to assess electrical and mechanical stability of micro-bonds under long-term implantation. I propose a 3D printed packaging method allows a wide variety of electrode configurations to be realized such as a rectangular or circular array configuration or other arbitrary geometries optimal for specific regions of the brain with inter-electrode distance as low as 25 um with an unprecedented capability of seeking and recording/stimulating targeted single neurons in deep brain structures up to 10 mm deep (with 6 μm displacement resolution). The advantage of this computer controlled moveable deep brain electrodes facilitates potential capabilities of moving past glial sheath surrounding microelectrodes to restore neural connection, counter the variabilities in signal amplitudes, and enable simultaneous recording/stimulation at precisely targeted layers of brain.
ContributorsPalaniswamy, Sivakumar (Author) / Muthuswamy, Jitendran (Thesis advisor) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Arizona State University (Publisher)
Created2016