Design and Test of a Gate Driver with Variable Drive and Self-Test Capability Implemented in a Silicon Carbide CMOS Process

Discrete silicon carbide (SiC) power devices have long demonstrated abilities that outpace those of standard silicon (Si) parts. The improved physical characteristics allow for faster switching, lower on-resistance, and temperature performance. The capabilities unleashed by these devices allow for higher efficiency switch-mode converters as well as the advance of power electronics into new high-temperature regimes previously unimaginable with silicon devices. While SiC power devices have reached a relative level of maturity, recent work has pushed the temperature boundaries of control electronics further with silicon carbide integrated circuits. The primary requirement to ensure rapid switching of power MOSFETs was a gate drive buffer capable of taking a control signal and driving the MOSFET gate with high current required. In this work, the first integrated SiC CMOS gate driver was developed in a 1.2 μm SiC CMOS process to drive a SiC power MOSFET. The driver was designed for close integration inside a power module and exposure to high temperatures. The drive strength of the gate driver was controllable to allow for managing power MOSFET switching speed and potential drain voltage overshoot. Output transistor layouts were optimized using custom Python software in conjunction with existing design tool resources. A wafer-level test system was developed to identify yield issues in the gate driver output transistors. This method allowed for qualitative and quantitative evaluation of transistor leakage while the system was under probe. Wafer-level testing and results are presented. The gate driver was tested under high temperature operation up to 530 degrees celsius. An integrated module was built and tested to illustrate the capability of the gate driver to control a power MOSFET under load. The adjustable drive strength feature was successfully demonstrated

Integrated control and health management. Orbit transfer rocket engine technology program

To insure controllability of the baseline design for a 7500 pound thrust, 10:1 throttleable, dual expanded cycle, Hydrogen-Oxygen, orbit transfer rocket engine, an Integrated Controls and Health Monitoring concept was developed. This included: (1) Dynamic engine simulations using a TUTSIM derived computer code; (2) analysis of various control methods; (3) Failure Modes Analysis to identify critical sensors; (4) Survey of applicable sensors technology; and, (5) Study of Health Monitoring philosophies. The engine design was found to be controllable over the full throttling range by using 13 valves, including an oxygen turbine bypass valve to control mixture ratio, and a hydrogen turbine bypass valve, used in conjunction with the oxygen bypass to control thrust. Classic feedback control methods are proposed along with specific requirements for valves, sensors, and the controller. Expanding on the control system, a Health Monitoring system is proposed including suggested computing methods and the following recommended sensors: (1) Fiber optic and silicon bearing deflectometers; (2) Capacitive shaft displacement sensors; and (3) Hot spot thermocouple arrays. Further work is needed to refine and verify the dynamic simulations and control algorithms, to advance sensor capabilities, and to develop the Health Monitoring computational methods

Dynamics of embodied dissociated cortical cultures for the control of hybrid biological robots.

The thesis presents a new paradigm for studying the importance of interactions between an organism and its environment using a combination of biology and technology: embodying cultured cortical neurons via robotics. From this platform, explanations of the emergent neural network properties leading to cognition are sought through detailed electrical observation of neural activity. By growing the networks of neurons and glia over multi-electrode arrays (MEA), which can be used to both stimulate and record the activity of multiple neurons in parallel over months, a long-term real-time 2-way communication with the neural network becomes possible. A better understanding of the processes leading to biological cognition can, in turn, facilitate progress in understanding neural pathologies, designing neural prosthetics, and creating fundamentally different types of artificial cognition. Here, methods were first developed to reliably induce and detect neural plasticity using MEAs. This knowledge was then applied to construct sensory-motor mappings and training algorithms that produced adaptive goal-directed behavior. To paraphrase the results, most any stimulation could induce neural plasticity, while the inclusion of temporal and/or spatial information about neural activity was needed to identify plasticity. Interestingly, the plasticity of action potential propagation in axons was observed. This is a notion counter to the dominant theories of neural plasticity that focus on synaptic efficacies and is suggestive of a vast and novel computational mechanism for learning and memory in the brain. Adaptive goal-directed behavior was achieved by using patterned training stimuli, contingent on behavioral performance, to sculpt the network into behaviorally appropriate functional states: network plasticity was not only induced, but could be customized. Clinically, understanding the relationships between electrical stimulation, neural activity, and the functional expression of neural plasticity could assist neuro-rehabilitation and the design of neuroprosthetics. In a broader context, the networks were also embodied with a robotic drawing machine exhibited in galleries throughout the world. This provided a forum to educate the public and critically discuss neuroscience, robotics, neural interfaces, cybernetics, bio-art, and the ethics of biotechnology.Ph.D.Committee Chair: Steve M. Potter; Committee Member: Eric Schumacher; Committee Member: Robert J. Butera; Committee Member: Stephan P. DeWeerth; Committee Member: Thomas D. DeMars

Measurements of forced and unforced aerodynamic disturbances in a turbojet engine

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1993.Includes bibliographical references (leaves 212-213).by Jabin Todd Bell.M.S

New approaches to the measurement of chlorophyll, related pigments and productivity in the sea

In the 1984 SBIR Call for Proposals, NASA solicited new methods to measure primary production and chlorophyll in the ocean. Biospherical Instruments Inc. responded to this call with a proposal first to study a variety of approaches to this problem. A second phase of research was then funded to pursue instrumentation to measure the sunlight stimulated naturally occurring fluorescence of chlorophyll in marine phytoplankton. The monitoring of global productivity, global fisheries resources, application of above surface-to-underwater optical communications systems, submarine detection applications, correlation, and calibration of remote sensing systems are but some of the reasons for developing inexpensive sensors to measure chlorophyll and productivity. Normally, productivity measurements are manpower and cost intensive and, with the exception of a very few expensive multiship research experiments, provide no contemporaneous data. We feel that the patented, simple sensors that we have designed will provide a cost effective method for large scale, synoptic, optical measurements in the ocean. This document is the final project report for a NASA sponsored SBIR Phase 2 effort to develop new methods for the measurements of primary production in the ocean. This project has been successfully completed, a U.S. patent was issued covering the methodology and sensors, and the first production run of instrumentation developed under this contract has sold out and been delivered