Tyler Scott Jordan

Electrical and optical characterization of the metal-insulator transition temperature in Cr-doped VO2 thin films

The effect of Cr doping on electrical and optical properties of CrxV1−xO2 thin films across the metal-insulator transition has been studied. Resistance, Hall effect, and infrared reflectance show that Cr doping systematically increases the transition temperature Tc from 59 °C at x = 0 to 70 °C at x = 0.11 with similar transition width and hysteresis from DC to infrared, but the effect appears to saturate. The conductance contrast between insulating and metallic phases decreases with Cr doping. The effects of carrier density and mobility changes across Tc will be discussed.

Model and Characterization of

This paper investigates and models the dc behavior of thin-film-based switching devices. The devices are based on sputtered vanadium dioxide thin films that transition from 200 kΩ/□ at room temperature to 390 Ω/□ at temperatures above 68°C, with the transition occurring over a narrow temperature range. The device resistance is characterized over temperature and under current- and voltage-sourced electrical bias. The finite-element model predicts the devices nonuniform switching behavior. Electrothermally heated devices show the same transition ratio and switching behavior as externally heated devices suggesting a purely electrothermal switching mechanism.

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This paper presents the findings of using convolutional neural networks (CNNs) to classify human activity from micro-Doppler features. An emphasis on activities involving potential security threats such as holding a gun are explored. An automotive 24 GHz radar on chip was used to collect the data and a CNN (normally applied to image classification) was trained on the resulting spectrograms. The CNN achieves an error rate of 1.65 % on classifying running vs. walking, 17.3 % error on armed walking vs. unarmed walking, and 22 % on classifying six different actions.

Thin-Film Switching Devices

The design and simulation of a frequency selective surface (FSS) with integrated limiter for receiver-protection are presented. The FSS operates as normal until a certain power threshold is reached, at which point the temperature increase triggers a dramatic resistance change across the element, and the insertion loss changes from 0.2 dB to 20 dB. The limiting action is completely passive and automatically reversible. By placing the limiter outside of the system, no portion of the front-end risks damage from high-power signals, a level of protection not offered in conventional limiters. Finally, the design is compatible with standard lithography processes, requires no diodes, ferrites, or additional components, and can potentially be integrated on flexible substrates.

Using convolutional neural networks for human activity classification on micro-Doppler radar spectrograms

The concept for a new, frequency-selective limiting filter is presented. This is accomplished by placing a phase change vanadium dioxide (VO2) film at the proper node of the filter. When the high-powered microwave signal reaches a certain threshold, the VO2 undergoes a phase transition from the monoclinic “insulator state” to the tetragonal “metallic state”. This crystallographic change is accompanied by a 3 order of magnitude drop in the films resistivity, and creates a short circuit at a section of the filter, changing a pole to a zero, and rejecting further undesirable high-powered signals from damaging sensitive receiver components. This paper details the design and simulation of the filter, along with measurement results from VO2 films and the filter element. This filter element begins rejecting at about 2 W input power, with isolation of over 16 dB to over 23 W input power, and is unaffected by an out-of band interferer of over 25 W. The architecture presented allows for filter banks capable of automatically-rejecting interferers, yet allowing signals of interest to pass.