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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34

Fast Growth of Ga2O3 on Highly Offcut (100)-Oriented Substrates

Beta-Ga2O3 has emerged as a leading candidate for next-generation power electronics, radio frequency (RF) switches, and extreme environment electronics due to a wide band gap (4.6 - 4.9 eV), high dopability (approximately 40 meV activation energy for an isolated silicon donor), and melt growth characteristics resulting in commercially available 4-inch substrates and commercial demonstrations of 6-inch substrates by multiple techniques. The (100) surface of Ga2O3 is highly desirable from a device and epitaxy standpoint - bulk growth of (100) material is more scalable than (010), the surface is nearly lattice-matched to p-type partner NiO, and Al2O3 incorporates at higher concentrations without phase separation. More importantly, the impact ionization coefficients along the [100] direction are low, leading to the highest possible critical fields. This is advantageous compared to the current state of the art, (001), due to reduced surface defects and increased possible breakdown voltage. However, the epitaxial growth rate on (100) surfaces is less than 10% of other faces due to weak bonding and favorable desorption, and on-axis (100) growth easily forms twin domains. Recent demonstrations have shown growth rate improvements from 0.4 nm/min to 1.5 nm/min by growing on (100) wafers that are offcut 6 degrees in the -c direction. These films show step-flow growth from (20-1) step-edges and high electron mobility due to suppressed twins. Despite these exciting results, offcuts greater than 6 degrees have not been explored due to the waste associated with grinding and polishing large offcuts. In this talk we will discuss the molecular beam epitaxy (MBE) growth and properties of Beta-Ga2O3 grown on (100) substrates offcut in the -c direction up to 13.4 degrees. These large offcuts are enabled by edge-fed film-defined growth (EFG) where the offcut is grown into the surface by pulling the crystal through the EFG die with the seed crystal rotated by the desired offcut angle. We will demonstrate that 13.4 degrees offcut substrates still exhibit a terraced (100) surface, and that a >10x increase (>5 nm/min) in growth rate is achieved. As previously reported on lower offcuts, we observe reversal of substrate twin domains around the (001) direction at the substrate-epilayer interface. We will discuss electrical properties including record-low (by MBE) unintentional doping densities of < 5E15 cm-3 and critical breakdown field in Schottky barrier diodes comparable with state-of-the-art (001) Ga2O3 without edge termination.

36 MATERIALS SCIENCE↗

CWDM transmit module for wavelength tuning and tracking

A photonic integrated circuit (PIC) includes a semiconductor substrate with a main bus waveguide disposed within the substrate. Two or more ring lasers are disposed within the substrate and are optically coupled to the main bus waveguide. The ring lasers have a wavelength control mechanism allowing change of a lasers emitted wavelength. A wavelength selective filter is optically coupled to the bus waveguide. A control circuit is electronically coupled to each wavelength control mechanism, and the wavelength selective filter. The control circuit in conjunction with the selective filter allows monitoring of a ring laser's wavelength on the main bus waveguide. Based on a determined wavelength, the control circuit may change a ring laser wavelength to a desired wavelength to achieve a desired wavelength spacing for each of the ring lasers. The PIC may be integrated as a coarse wave-length division multiplexing (CWDM) transmit module.

42 ENGINEERING↗

Compressive sensing optical design and simulation tool

A system or method for designing optical systems includes generating a mathematical model of an imaging system; tracing a plurality of light rays from a source through the model of the imaging system in a forward direction and a backward direction incident upon an arbitrarily defined detector location; calculating the total light rays incident upon the arbitrarily defined detector location in response to the plurality of light rays; tracing a series of calibration images first through the computational or compressive imager mathematical model; measuring an output set of parameters based on a plurality of detected rays calibration images at the defined detector location; storing the output set of parameters in software, and determining an estimated system transfer function.

42 ENGINEERING↗

Passive bias temperature compensation circuit module

A passive bias temperature compensation module for silicon photomultiplier, avalanche photodiodes and similar photodetectors that possess a moderately linear temperature coefficient of gain and that may be compensated by varying an applied bias voltage. The module includes an electrical circuit and a method for determining component values to provide a constant voltage source to stabilize the gain of one or more photodetector devices. A temperature sensor in the module is held in close thermal contact with the photodetector and a filter capacitor is electrically close to the photodetector. The module is based on the concept of temperature sensitive voltage division which is applicable to situations in which large numbers of photodetectors must be gain-compensated for temperature variations over a wide range while maintaining excellent gain matching. The passive bias temperature compensation method enables multiple photodetectors to share a single constant voltage supply without loss of matching performance.

42 ENGINEERING↗

Pattern generator circuit for high-speed pulse generation

A pattern generator circuit includes a high-speed shift register and a non-overlap generator. The shift register is programmable to produce a pulse train of pulses having a defined pulse duration and a defined pulse-to-pulse interval. The non-overlap generator deserializes the incoming pulse train, and it produces a time-separated reset pulse based on the pulse train. The shift register is configured to permit the pulse durations and pulse-to-pulse interval to be selected arbitrarily over specified ranges in increments of a basic time unit that depends on the oscillator period.

42 ENGINEERING↗

Bi-triaxial photoconductive switch module

Methods, systems, and devices describe bi-triaxial photoconductive switch modules that that eliminate the need for external DC blocking capacitors, while providing a highly compact structure that can produce bipolar output waveforms conducive to feeding to radio-frequency (RF) devices, such as antennas. Some implementations of the disclosed bi-triaxial photoconductive switch modules utilize unified cast-in-place capacitors that can be designed with an appropriate geometry, volume and orientation to provide desired energy storage capacity while eliminating or reducing parasitics.

42 ENGINEERING↗

System and method for portable multi-band black body simulator

The present disclosure relates to an apparatus for simulating a black body spectrum. The apparatus makes use of a broadband light source and a light guide configured to receive light generated by the light source and to generate first and second optical signals. A first signal processing subsystem may be used to enable adjustment of both a signal spectrum and an intensity of the first optical signal. A second signal processing subsystem may be used to enable adjustment of both a signal spectrum and an intensity of the second optical signal. A beam cube may be used to combine the first and second optical signals to produce a final light output signal having a desired signal spectrum and a desired intensity.

42 ENGINEERING↗

Internally-cooled compressor diaphragm

An internally-cooled diaphragm for an internally-cooled compressor is provided. The internally-cooled diaphragm may include an annular body configured to cool a process fluid flowing through a fluid pathway of the internally-cooled compressor. The annular body may define a return channel of the fluid pathway, and a cooling pathway in thermal communication with the fluid pathway. The return channel may be configured to at least partially diffuse and de-swirl the process fluid flowing therethrough, and the cooling pathway may be configured to receive a coolant to absorb heat from the process fluid flowing through the return channel.

42 ENGINEERING↗

System and method for controlling an energy beam of an additive manufacturing system

An additive manufacturing system includes an energy beam generator that generates an energy beam to melt and fuse raw materials for a part and a computing device that controls operation of the energy beam generator. The computing device includes a memory element that stores or access a three-dimensional model of the part, and a processing element that receives at least a portion of the three-dimensional model and controls a parameter of the energy beam generator according to a gradient function so as to apply a variable amount of heat to the raw material that forms an overhang on the part.

42 ENGINEERING↗

Glass/Glass Focus Group: Module Technology and Durability Roadmap

The G/G Focus Group was created one year ago with a mission to identify critical research directions in G/G packaging and how research in DuraMAT 2.0 can drive this area forward. This is a summary of the research on Glass/Glass modules discussed over the past year.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,E↗

Tandem Solar Cells Part 1

This tutorial was given at the 8th World Conference on Photovoltaic Energy Conversion during PV Academy.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,E↗

Applying Quantum Computing to Simulate Power System Dynamics

Power system dynamics are generally modeled by high dimensional nonlinear differential-algebraic equations due to a large number of generators, loads, and transmission lines. Thus, its computational complexity grows exponentially with the system size. This paper demonstrates the potential use of quantum computing algorithms to model the power system dynamics. Leveraging a symbolic programming framework, we equivalently convert the power system dynamics’ differential algebraic equations (DAEs) into ordinary differential equations (ODEs), where the data of the state vector can be encoded into quantum computers via amplitude encoding. The system's nonlinearity is captured by Taylor polynomial expansion, the quantum state tensor, and Hamiltonian simulation, whereas state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can simulate the dynamics of the power system with high accuracy, whereas its complexity is polynomial in the logarithm of the system dimension. Our work also illustrates the use of scientific machine learning tools for implementing scientific computing concepts, e.g., Taylor expansion, DAEs/ODEs transform, and quantum computing solver, in the field of power engineering.

Tran, Huynh↗

Ion-Depleted Microenvironments During Lithium Deposition Revealed by Operando Freezing Cryogenic Electron Microscopy

Local structures and chemistry at active electrochemical interfaces are critical to determining safety, lifetime, and energy density in lithium metal batteries and other devices, but they are challenging to characterize at the nanoscale. We address this issue by developing operando freezing cryogenic electron microscopy (cryo-EM) to preserve battery interfaces in an active state for subsequent high-resolution characterization. We find that ion-depleted microenvironments form locally in the electrolyte adjacent to the lithium deposition interface in lithium metal batteries and are linked to heterogenous growth morphologies. These depleted environments arise locally even under conditions for which ion depletion is not predicted at steady state; this provides a mechanistic explanation for why dangerous lithium morphologies can still propagate in such systems and lead to thermal runaway. Operando freezing cryo-EM thus provides a method to directly visualize nanoscale heterogeneities that arise locally at electrochemical interfaces and play key roles in device failure.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,E↗

Catalytic enhancement in the performance of the microscopic two-stroke heat engine

Here we consider a model of heat engine operating in the microscopic regime: the two-stroke engine. It produces work and exchanges heat in two discrete strokes that are separated in time. The working body of the engine consists of two d-level systems initialized in thermal states at two distinct temperatures. Additionally, an auxiliary nonequilibrium system called catalyst may be incorporated with the working body of the engine, provided the state of the catalyst remains unchanged after the completion of a thermodynamic cycle. This ensures that the work produced by the engine arises solely from the temperature difference. Upon establishing the rigorous thermodynamic framework, we characterize twofold improvement stemming from the inclusion of a catalyst. Firstly, we prove that in the noncatalytic scenario, the optimal efficiency of the two-stroke heat engine with a working body composed of two-level systems is given by the Otto efficiency, which can be surpassed by incorporating a catalyst with the working body. Secondly, we show that incorporating a catalyst allows the engine to operate in frequency and temperature regimes that are not accessible for noncatalytic two-stroke engines. We conclude with a general conjecture about the advantage brought by a catalyst: including the catalyst with the working body always allows to improve efficiency over the noncatalytic scenario for any microscopic two-stroke heat engines. We prove this conjecture for two-stroke engines where the working body is composed of two d-level systems initialized in thermal states at two distinct temperatures, as long as the final joint state leading to optimal efficiency in the noncatalytic scenario is not a product state, or at least one of the d-level system is not thermal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗