Publications

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Evaluation of high temperature (HT) microcontrollers for Geothermal applications. The goal was to evaluate the limited microcontrollers capable of operating above 200 degrees Celsius. The knowledge obtained from this research has been documented for contributing to future development of high temperature geothermal tools. Along with this research, a HT data link for communications was developed and evaluated, also for HT geothermal tools.

Here we report on AlGaN high electron mobility transistor (HEMT)-based logic development, using combined enhancement- and depletion-mode transistors to fabricate inverters with operation from room temperature up to 500°C. Our development approach included: (a) characterizing temperature-dependent carrier transport for different AlGaN HEMT heterostructures, (b) developing a suitable gate metal scheme for use in high temperatures, and (c) over-temperature testing of discrete devices and inverters. Hall mobility data (from 30°C to 500°C) revealed the reference GaN-channel HEMT experienced a 6.9x reduction in mobility, whereas the AlGaN channel HEMTs experienced about a 3.1x reduction. Furthermore, a greater aluminum contrast between the barrier and channel enabled higher carrier densities in the two-dimensional electron gas for all temperatures. The combination of reduced variation in mobility with temperature and high sheet carrier concentration showed that an Al-rich AlGaN-channel HEMT with a high barrier-to-channel aluminum contrast is the best option for an extreme temperature HEMT design. Three gate metal stacks were selected for low resistivity, high melting point, low thermal expansion coefficient, and high expected barrier height. The impact of thermal cycling was examined through electrical characterization of samples measured before and after rapid thermal anneal. The 200-nm tungsten gate metallization was the top performer with minimal reduction in drain current, a slightly positive threshold voltage shift, and about an order of magnitude advantage over the other gates in on-to-off current ratio. After incorporating the tungsten gate metal stack in device fabrication, characterization of transistors and inverters from room temperature up to 500°C was performed. The enhancement-mode (e-mode) devices’ resistance started increasing at about 200°C, resulting in drain current degradation. This phenomenon was not observed in depletion-mode (d-mode) devices but highlights a challenge for inverters in an e-mode driver and d-mode load configuration.

The impact of 1.8 MeV proton irradiation on metalorganic chemical vapor deposition grown (010) β-Ga2O3 Schottky diodes is presented. It is found that after a 10.8 × 10 13 cm - 2 proton fluence the Schottky barrier height of (1.40 ± 0.05 eV) and the ideality factor of (1.05 ± 0.05) are unaffected. Capacitance-voltage extracted net ionized doping curves indicate a carrier removal rate of 268 ± 10 cm - 1. The defect states responsible for the observed carrier removal are studied through a combination of deep level transient and optical spectroscopies (DLTS/DLOS) as well as lighted capacitance-voltage (LCV) measurements. The dominating effect on the defect spectrum is due to the EC-2.0 eV defect state observed in DLOS and LCV. This state accounts for ∼ 75% of the total trap introduction rate and is the primary source of carrier removal from proton irradiation. Of the DLTS detected states, the EC-0.72 eV state dominated but had a comparably smaller contribution to the trap introduction. These two traps have previously been correlated with acceptor-like gallium vacancy-related defects. Several other trap states at EC-0.36, EC-0.63, and EC-1.09 eV were newly detected after proton irradiation, and two pre-existing states at EC-1.2 and EC-4.4 eV showed a slight increase in concentration after irradiation, together accounting for the remainder of trap introduction. However, a pre-existing trap at EC-0.40 eV was found to be insensitive to proton irradiation and, therefore, is likely of extrinsic origin. The comprehensive defect characterization of 1.8 MeV proton irradiation damage can aid the modeling and design for a range of radiation tolerant devices.

Ionizable polymers form dynamic networks with domains controlled by two distinct energy scales, ionic interactions and van der Waals forces; both evolve under elongational flows during their processing into viable materials. A molecular level insight of their nonlinear response, paramount to controlling their structure, is attained by fully atomistic molecular dynamics simulations of a model ionizable polymer, polystyrene sulfonate. As a function of increasing elongational flow rate, the systems display an initial elastic response, followed by an ionic fraction-dependent strain hardening, stress overshoot, and eventually strain-thinning. As the sulfonation fraction increases, the chain elongation becomes more heterogeneous. Finally, flow-driven ionic assembly dynamics that continuously break and reform control the response of the system.

Automation of rate-coefficient calculations for gas-phase organic species became possible in recent years and has transformed how we explore these complicated systems computationally. Kinetics workflow tools bring rigor and speed and eliminate a large fraction of manual labor and related error sources. In this paper we give an overview of this quickly evolving field and illustrate, through five detailed examples, the capabilities of our own automated tool, KinBot. We bring examples from combustion and atmospheric chemistry of C-, H-, O-, and N-atom-containing species that are relevant to molecular weight growth and autoxidation processes. The examples shed light on the capabilities of automation and also highlight particular challenges associated with the various chemical systems that need to be addressed in future work.

Bifurcations are commonly encountered during force controlled swept and stepped sine testing of nonlinear structures, which generally leads to the so-called jump-down or jump-up phenomena between stable solutions. There are various experimental closed-loop control algorithms, such as control-based continuation and phase-locked loop, to stabilize dynamical systems through these bifurcations, but they generally rely on specialized control algorithms that are not readily available with many commercial data acquisition software packages. A recent method was developed to experimentally apply sequential continuation using the shaker voltage that can be readily deployed using commercially available software. By utilizing the stabilizing effects of electrodynamic shakers and the force dropout phenomena in fixed frequency voltage control sine tests, this approach has been demonstrated to stabilize the unstable branch of a nonlinear system with three branches, allowing for three multivalued solutions to be identified within a specific frequency bandwidth near resonance. Recent testing on a strongly nonlinear system with vibro-impact nonlinearity has revealed jumping behavior when performing sequential continuation along the voltage parameter, like the jump phenomena seen during more traditional force controlled swept and stepped sine testing. Here, this paper investigates the stabilizing effects of an electrodynamic shaker on strongly nonlinear structures in fixed frequency voltage control tests using both numerical and experimental methods. The harmonic balance method is applied to the coupled shaker-structure system with an electromechanical model to simulate the fixed voltage control tests and predict the stabilization for different parameters of the model. The simulated results are leveraged to inform the design of a set of experiments to demonstrate the stabilization characteristics on a fixture-pylon assembly with a vibro-impact nonlinearity. Through numerical simulation and experimental testing on two different strongly nonlinear systems, the various parameters that influence the stability of the coupled shaker-structure are revealed to better understand the performance of fixed frequency voltage control tests.

Vibrational spectroscopy is a nondestructive technique commonly used in chemical and physical analyses to determine atomic structures and associated properties. However, the evaluation and interpretation of spectroscopic profiles based on human-identifiable peaks can be difficult and convoluted. To address this challenge, we present a reliable protocol based on supervised manifold learning techniques meant to connect vibrational spectra to a variety of complex and diverse atomic structure configurations. As an illustration, we examined a large database of virtual vibrational spectroscopy profiles generated from atomistic simulations for silicon structures subjected to different stress, amorphization, and disordering states. We evaluated representative features in those spectra via various linear and nonlinear dimensionality reduction techniques and used the reduced representation of those features with decision trees to correlate them with structural information unavailable through classical human-identifiable peak analysis. We show that our trained model accurately (over 97% accuracy) and robustly (insensitive to noise) disentangles the contribution from the different material states, hence demonstrating a comprehensive decoding of spectroscopic profiles beyond classical (human-identifiable) peak analysis.

Hydrocarbon polymers are used in a wide variety of practical applications. In the field of dynamic compression at extreme pressures, these polymers are used at several high energy density (HED) experimental facilities. One of the most common polymers is poly(methyl methacrylate) or PMMA, also called Plexiglass® or Lucite®. Here, we present high-fidelity, hundreds of GPa range experimental shock compression data measured on Sandia's Z machine. We extend the principal shock Hugoniot for PMMA to more than threefold compression up to 650 GPa and re-shock Hugoniot states up to 1020 GPa in an off-Hugoniot regime, where experimental data are even sparser. These data can be used to put additional constraints on tabular equation of state (EOS) models. The present results provide clear evidence for the need to re-examine the existing tabular EOS models for PMMA above ∼120 GPa as well as perhaps revisit EOSs of similar hydrocarbon polymers commonly used in HED experiments investigating dynamic compression, hydrodynamics, or inertial confinement fusion.

Accurately modeling the impact force used in the analysis of loosely constrained cantilevered pipes conveying fluid is imperative. If little information is known of the motion-limiting constraints used in experiments, the analysis of the system may yield inaccurate predictions. Here in this work, multiple forcing representations of the impact force are defined and analyzed for a cantilevered pipe that conveys fluid. Depending on the representation of the impact force, the dynamics of the pipe can vary greatly when only the stiffness of the constraints is known from experiments. Three gap sizes of the constraints are analyzed, and the representation of the impact force used to analyze the system is found to significantly affect the response of the pipe at each gap size. An investigation on the effects of the vibro-impact force representation is performed through using basin of attraction analysis and nonlinear characterization of the system’s response.