Gallium Nitride and Related Materials - Device Processing and Materials Characterization for Power Electronics Applications
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Armstrong, Andrew Michael [Sandia National Laborat↗
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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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Design & Assembly of Atomically-Precise Quantum Materials & Devices (Final Report)
Atomic-layer honeycomb materials (Xene, where “X” may stand for a number of different elements) are a promising platform for new quantum states. When X is a heavier element such as tin (Sn) or bismuth (Bi), the edges of the honeycomb may conduct electron charge or spin without resistance - an effect that could persist up to room temperature in some cases. The type of edge states, and their robustness at room temperature, depend sensitively on (a) the substrate material that the Xene is sitting on; (b) out-of-plane buckling of the honeycomb structure; (c) the pattern of atoms or molecules sitting atop the honeycomb. This sensitivity suggests that Xene edge states could be tuned and rearranged to construct nanoscale electronic or spintronic devices. We report on theoretical progress in modeling the assembly and structure of Xenes, and their underlying substrates and overlaying atoms. Specifically, we model the stability of Sn atoms forming a single atomic layer (“stanene”), the stability and phase transitions
36 MATERIALS SCIENCE↗
Building next generation analog computers: materials, devices and systems
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Fuller, Elliot James [Sandia National Laboratories↗
Toward High-Throughput Deposition of III-V Materials and Devices Using Halide Vapor Phase Epitaxy: Preprint
III-V devices are used in countless applications due to their excellent physical properties. They could become more prevalent, especially in area-intensive applications such as solar power, if they can achieve significant cost decreases through increasing scale. The development of high-throughput growth systems can help to achieve this scale, leading to the use of III-V devices in areas where they are not currently economically feasible. Here, we describe a pilot production, pseudo inline HVPE reactor with the potential to greatly increase the throughput of III-V devices. We show computational modeling results that both informed system design and the understanding of the impact of different process parameters on the deposition. We show the throughput possibilities of this reactor with an example solar cell device design but note that this system is agnostic to the device structure and can be used to increase the throughput of lasers, LEDs, transistors, and more III-V devices.
high throughput↗
Device and material investigations of GaN enhancement-mode transistors for Venus and harsh environments
This Letter reports the device and material investigations of enhancement-mode p-GaN-gate AlGaN/GaN high electron mobility transistors (HEMTs) for Venus exploration and other harsh environment applications. The GaN transistor in this work was subjected to prolonged exposure (11 days) in a simulated Venus environment (460 °C, 94 bar, complete chemical environment including CO2/N2/SO2). The mechanisms affecting the transistor performance and structural integrity in harsh environment were analyzed using a variety of experimental, simulation, and modeling techniques, including in situ electrical measurement (e.g., burn-in) and advanced microscopy (e.g., structural deformation). Through transistor, Transmission Line Method (TLM), and Hall-effect measurements vs temperature, it is revealed that the mobility decrease is the primary cause of reduction of on-state performance of this GaN transistor at high temperature. Material analysis of the device under test (DUT) confirmed the absence of foreign elements from the Venus atmosphere. No inter-diffusion of the elements (including the gate metal) was observed. The insights of this work are broadly applicable to the future design, fabrication, and deployment of robust III-N devices for harsh environment operation.
Physics↗
Ultra low noise materials and devices for cryogenic superconductors and quantum bits
Materials, products, methods of use and fabrication thereof are disclosed. The materials are particularly well suited for application in products such as superconducting devices and quantum computing, due to ability to avoid undesirable effects from inherent noise and decoherence. The materials are formed from select isotopes having zero nuclear spin into a single crystal-phase film or layer of thickness depending on the desired application of the resulting device. The film/layer may be suspended or disposed on a substrate. The isotopes may be enriched from naturally-occurring sources of isotopically mixed elemental material(s). The single crystal is preferably essentially devoid of structural defects such as grain boundaries, inclusions, impurities and lattice vacancies.
Pereverzev, Sergey↗
Improving Predictions Under Uncertainty of Material Plasma Device Operations
Understanding the properties of materials when exposed to various plasma temperatures and fluxes is essential to the building and operating of fusion reactors. The Material Plasma Exposure eXperiment (MPEX) is an instrument currently being developed by the Department of Energy (DOE) for this purpose. MPEX is expected to come online in stages over the next five years. Proto-MPEX, the predecessor to MPEX, operated from 2014 to 2021, and was designed to understand the generation of plasma temperatures and fluxes at orders of magnitude below what will be obtained by MPEX. This work uses the recently developed stochastic neural network (SNN), a machine learning technique capable of operating under uncertainty to provide a surrogate model for the Proto-MPEX device. We demonstrate that SNN outperforms Bayesian neural network (BNN), a standard in the field of machine learning with uncertainty. The development of a robust surrogate of the Proto-MPEX will aid in the commissioning and operation of the MPEX device.
Archibald, Rick↗
Synchrotron-based Characterization Techniques for Radiation Detection Materials and Devices: An Overview
High-performance room-temperature radiation detectors (high energy resolution for spectrometers, high spatial resolution for imaging devices, and low defect-density for high flux applications) are needed for photon energies (>20 keV) that are not well suited for silicon detectors. Applications for such radiation detectors include nonproliferation, synchrotron, medical, astrophysics, and homeland security. Material- and device- characterization to understand and solve the limiting factors of radiation detection materials and devices is a core element of a radiation detector development R&D program. This presentation will give an overview on the two main synchrotron-based characterization techniques that have been employed by the authors in the last ~20 years: (1) White Beam X-ray Diffraction Topography and (2) Micron-scale detector mapping. A perfect (one domain) crystal (radiation detection material) is a requirement to achieve a highperformance radiation detector. White Beam X-ray Diffraction Topography (WBXDT) allows the rapid screening of the crystallinity of the detector material. With WBXDT we can quickly screen CZT and other crystals to make sure they have only one domain, and to see the presence of extended defects and strain fields.
Camarda, Giuseppe S.↗
Rapid Cryogenic Electrical Characterization of Materials and Devices Using Gifford-McMahon Cryocoolers
Thin-film heterostructures are necessary building blocks for superconducting and phononic quantum computing devices. Many new generations of quantum hardware demand extensive materials research to optimize performances at cryogenic temperatures (below 10 K). Here, we demonstrate compact cryogenic measurement systems capable of reaching sub-10K temperatures in less than three hours with the ability to measure AC/DC resistance and dielectric properties of thin-film materials. Our platform utilizes Gifford-McMahon (GM) cryocoolers as effective tools for providing high throughput cooling-warming cycles. We successfully used the GM-based measurement systems to measure 1) the superconducting transition temperature for Nb thin films (T c ~7.8 K), and 2) the temperature dependence of the dielectric constant in SiO 2 thin films down to 10 K. The fast electrical characterization feedback will be critical in developing robust materials and components for cryogenic computing devices.
36 MATERIALS SCIENCE↗
Proton Conducting Neuromorphic Materials and Devices
Neuromorphic computing and artificial intelligence hardware generally aims to emulate features found in biological neural circuit components and to enable the development of energy-efficient machines. In the biological brain, ionic currents and temporal concentration gradients control information flow and storage. It is therefore of interest to examine materials and devices for neuromorphic computing wherein ionic and electronic currents can propagate. Protons being mobile under an external electric field offers a compelling avenue for facilitating biological functionalities in artificial synapses and neurons. In this review, we first highlight the interesting biological analog of protons as neurotransmitters in various animals. We then discuss the experimental approaches and mechanisms of proton doping in various classes of inorganic and organic proton-conducting materials for the advancement of neuromorphic architectures. Since hydrogen is among the lightest of elements, characterization in a solid matrix requires advanced techniques. We review powerful synchrotron-based spectroscopic techniques for characterizing hydrogen doping in various materials as well as complementary scattering techniques to detect hydrogen. First-principles calculations are then discussed as they help provide an understanding of proton migration and electronic structure modification. Outstanding scientific challenges to further our understanding of proton doping and its use in emerging neuromorphic electronics are pointed out.
36 MATERIALS SCIENCE↗
Roadmap on advanced and / real-time characterisation of solid state materials and devices for energy applications
A strong societal and political drive is motivating the development and optimization of novel energy conversion and storage systems for decarbonization. The successful implementation of solid state devices such as fuel cells and secondary batteries depends, however, on achieving ambitious targets in terms of performance, reliability and cost competitiveness. Research and technology are addressing these needs through a holistic approach including exploration of new materials and nanoarchitectures, as well as system engineering. These significant efforts require the support of appropriate characterization tools capable of assessing nanometer-scale phenomena such as concentration profiles of ionic and electronic charges, local chemical compositions and their evolution over time across interfaces. This roadmap provides an overview of selected advanced characterization techniques for energy materials and devices. Specific focus is put on in situ/operando methods for probing electrochemical phenomena in real-time under realistic working conditions. Experts in the field provide an extensive review of the current state of the art in 2025 and the current and future challenges for the characterization of local chemistry and kinetics in the bulk of the material, in nanoarchitectures (e.g. thin films) and at the interfaces (e.g. grain boundaries, phase contacts, solid/liquid and solid/gas interfaces) . The aim is to provide a detailed guide to the techniques, describing opportunities and bottlenecks for their practical deployment and examples of successful applications.
25 ENERGY STORAGE↗
New perspectives on materials and device dynamics using time-resolved full-field diffraction X-ray imaging
Understanding how materials evolve during synthesis, processing, or device operation requires experimental access to structural dynamics across wide ranges of length and time scales, often in bulk samples or even within packaged devices. Time-resolved full-field diffraction X-ray microscopy has recently emerged as a powerful way to meet this need by combining the penetration and structural sensitivity of X-ray diffraction with objective-lens-based magnification, sensitive high-resolution X-ray imaging detectors, and pump-probe and real-time imaging strategies. Advances in full-field X-ray diffraction microscopy, often termed dark-field X-ray microscopy (DFXM), enable simultaneous imaging of extended fields of view while retaining crystallographic selectivity. Time-resolved DFXM promises to enable advances in materials processing and dynamics, electrochemical and photochemical processes, and the design of electronic devices. This Perspective summarizes the key instrumental concepts that define the performance of these methods, including the choice of imaging optics, detector considerations, and the impact of source time structure at synchrotron light sources and X-ray free-electron lasers (XFELs). We discuss the simultaneous use of complementary imaging modes that are increasingly used in practice. The early demonstrations of the potential of time-resolved DFXM include real-time defect and grain-boundary dynamics during metal annealing, stroboscopic imaging of functional devices with high strain sensitivity, and ultrafast pump-probe implementations at XFELs that directly visualize acoustic-wave propagation and energy dissipation in bulk crystals.
Dark-field X-ray microscopy↗
Mitigating thermal runaway in lithium ion batteries using damage-initiating materials or devices
A method of manufacturing a battery includes introducing a first material to the battery, providing an anode, a cathode and a separator of the battery; and assembling the anode, the separator and the cathode. The first material is configured and arranged to increase the internal impedance of the battery upon mechanical or thermal loading.
Qiao, Yu↗
AI-guided framework for the design of materials and devices for magnetic-tunnel-junction-based true random number generators
Not Available
36 MATERIALS SCIENCE↗
AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation (Workshop Report)
The Artificial Intelligence Enhanced Co-Design for Next Generation Microelectronics virtual workshop was held April 4-5, 2023, and attended by subject matter experts from universities, industry, and national laboratories. This was the third in a series of workshops to motivate the research community to identify and address major challenges facing microelectronics research and production. The 2023 workshop focused on a set of topics from materials to computing algorithms, and included discussions on relevant federal legislation and such as the Creating Helpful Incentives to Produce Semiconductors and Science Act (CHIPS Act) which was signed into law in the summer of 2022. Talks at the workshop included edge computing in radiation environments, new materials for neuromorphic computing, advanced packaging for microelectronics, and new AI techniques. We also received project updates from several of the Department of Energy (DOE) microelectronics co-design projects funded in the fall of 2021, and from three of the Energy Frontier Research Centers (EFRCs) that had been funded in the fall of 2022. The workshop also conducted a set of breakout discussions around the five principal research directions (PRDs) from the 2018 Department of Energy workshop report: 1) define innovative material, device, and architecture requirements driven by applications, algorithms, and software; 2) revolutionize memory and data storage; 3) re-imagine information flow unconstrained by interconnects; 4) redefine computing by leveraging unexploited physical phenomena; 5) reinvent the electricity grid through new materials, devices, and architectures. We tasked each breakout group to consider one primary PRD (and other PRDs as relevant topics arose during discussions) and to address questions such as whether the research community has embraced co-design as a methodology and whether new developments at any level of innovation from materials to programming models requires the research community to reevaluate the PRDs developed back in 2018.
97 MATHEMATICS AND COMPUTING↗
Stacking Order Engineering of Two-Dimensional Materials and Device Applications
Not provided.
Chemistry↗
Characterization of ECRAM materials and devices
As the limits of Moore’s Law approaches, new computing paradigms are developing to breakthrough this bottleneck. One such computer architecture is neuromorphic computing, which models the brain. Electrochemical random-access memory (ECRAM) is a low power and energy efficient memory due to characteristics, such as in-memory compute, ion modulation of the channel conductance, and computation distribution with large scale array integration.
97 MATHEMATICS AND COMPUTING↗