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At least 91 records · Page 5

Intra-microgrid communication architecture

A microgrid according to an exemplary aspect of the present disclosure includes, among other things, a plurality of intelligent electronic devices configured to communicate directly with one another in a first language. Each of the intelligent electronic devices includes a controller and a gateway. The gateway is configured to convert incoming messages from the first language to a second language native to the controller. The first language is different than the second language. A method is also disclosed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Controlling accesses to a branch prediction unit for sequences of fetch groups

An electronic device handles accesses of a branch prediction functional block when executing instructions in program code. The electronic device includes a processor having the branch prediction functional block that provides branch prediction information for control transfer instructions (CTIs) in the program code and a minimum predictor use (MPU) functional block. The MPU functional block determines, based on a record associated with a given fetch group of instructions, that a specified number of subsequent fetch groups of instructions that were previously determined to include no CTIs or conditional CTIs that were not taken are to be fetched for execution in sequence following the given fetch group. The MPU functional block then, when each of the specified number of the subsequent fetch groups is fetched and prepared for execution, prevents corresponding accesses of the branch prediction functional block for acquiring branch prediction information for instructions in that subsequent fetch group.

Agrawal, Varun↗

Controlling accesses to a branch prediction unit for sequences of fetch groups

An electronic device is described that handles control transfer instructions (CTIs) when executing instructions in program code. The electronic device has a processor that includes a branch prediction functional block and a sequential fetch logic functional block. The sequential fetch logic functional block determines, based on a record associated with a CTI, that a specified number of fetch groups of instructions that were previously determined to include no CTIs are to be fetched for execution in sequence following the CTI. When each of the specified number of fetch groups is fetched and prepared for execution, the sequential fetch logic prevents corresponding accesses of the branch prediction functional block for acquiring branch prediction information for instructions in that fetch group.

Yalavarti, Adithya↗

Preprocessing for Unintended Conducted Emissions Classification with ResNet

Characterization of Unintended Conducted Emissions (UCE) from electronic devices is important when diagnosing electromagnetic interference, performing nonintrusive load monitoring (NILM) of power systems, and monitoring electronic device health, among other applications. Prior work has demonstrated that UCE analysis can serve as a diagnostic tool for energy efficiency investigations and detailed load analysis. While explaining the feature selection of deep networks with certainty is often not fully comprehensive, or in other applications, quite lacking, additional tools/methods for further corroboration and confirmation can help further the understanding of the researcher. This is true especially in the subject application of the study in this paper. Often the focus of such efforts is the selected features themselves, and there is not as much understanding gained about the noise in the collected data. If selected feature and noise characteristics are known, it can be used to further shape the design of the deep network or associated preprocessing. This is additionally difficult when the available data are limited, as in the case which the authors investigated in this study. Here, the authors present a novel work (which is a proposed complementary portion of the overall solution to the deep network classification explainability problem for this application) by applying a systematic progression of preprocessing and a deep neural network (ResNet architecture) to classify UCE data obtained via current transformers. By using a methodical application of preprocessing techniques prior to a deep classifier, hypotheses can be produced concerning what features the deep network deems important relative to what it perceives as noise. For instance, it is hypothesized in this particular study as a result of execution of the proposed method and periodic inspection of the classifier output that the UCE spectral features are relatively close to each other or to the interferers, as systematically reducing the beta parameter of the Kaiser window produced progressively better classification performance, but only to a point, as going below the Beta of eight produced decreased classifier performance, as well as the hypothesis that further spectral feature resolution was not as important to the classifier as rejection of the leakage from a spectrally distant interference. This can be very important in unpredictable low-FNR applications, where knowing the difference between features and noise is difficult. As a side-benefit, much was learned regarding the best preprocessing to use with the selected deep network for the UCE collected from these low power consumer devices obtained via current transformers. Baseline rectangular windowed FFT preprocessing provided a 62% classification increase versus using raw samples. After performing a more optimal preprocessing, more than 90% classification accuracy was achieved across 18 low-power consumer devices for scenarios in which the in-band features-to-noise ratio (FNR) was very poor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Bottom-up synthesis of mesoscale nanomeshes of graphene nanoribbons on germanium

The synthesis of functional graphene nanostructures on Ge(001) provides an attractive route toward integrating graphene-based electronic devices onto complementary metal oxide semiconductor-compatible platforms. In this study, we leverage the phenomenon of the anisotropic growth of graphene nanoribbons from rationally placed graphene nanoseeds and their rotational self-alignment during chemical vapor deposition to synthesize mesoscale graphene nanomeshes over areas spanning several hundred square micrometers. Lithographically patterned nanoseeds are defined on a Ge(001) surface at pitches ranging from 50 to 100 nm, which serve as starting sites for subsequent nanoribbon growth. Rotational self-alignment of the nanoseeds followed by anisotropic growth kinetics causes the resulting nanoribbons to be oriented along each of the equivalent, orthogonal Ge < 110 > directions with equal probability. As the nanoribbons grow, they fuse, creating a continuous nanomesh. In contrast to nanomesh synthesis via top-down approaches, this technique yields nanomeshes with atomically faceted edges and covalently bonded junctions, which are important for maximizing charge transport properties. Additionally, we simulate the electrical characteristics of nanomeshes synthesized from different initial nanoseed-sizes, size-polydispersities, pitches, and device channel lengths to identify a parameter-space for acceptable on/off ratios and on-conductance in semiconductor electronics. The simulations show that decreasing seed diameter and pitch are critical to increasing nanomesh on/off ratio and on-conductance, respectively. With further refinements in lithography, nanomeshes obtained via seeded synthesis and anisotropic growth are likely to have superior electronic properties with tremendous potential in a multitude of applications, such as radio frequency communications, sensing, thin-film electronics, and plasmonics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Transfer-Free Synthesis of Atomically Precise Graphene Nanoribbons on Insulating Substrates

The rational bottom-up synthesis of graphene nanoribbons (GNRs) provides atomically precise control of widths and edges that give rise to a wide range of electronic properties promising for electronic devices such as field-effect transistors (FETs). Since the bottom-up synthesis commonly takes place on catalytic metallic surfaces, the integration of GNRs into such devices requires their transfer onto insulating substrates, which remains one of the bottlenecks in the development of GNR-based electronics. Herein, we report on a method for the transfer-free placement of GNRs on insulators. This involves growing GNRs on a gold film deposited onto an insulating layer followed by gentle wet etching of the gold, which leaves the nanoribbons to settle in place on the underlying insulating substrate. Scanning tunneling microscopy and Raman spectroscopy confirm that atomically precise GNRs of high density uniformly grow on the gold films deposited onto SiO 2 /Si substrates and remain structurally intact after the etching process. We have also demonstrated transfer-free fabrication of ultrashort channel GNR FETs using this process. A very important aspect of the present work is that the method can scale up well to 12 in. wafers, which is extremely difficult for previous techniques. Our work here thus represents an important step toward large-scale integration of GNRs into electronic devices.

36 MATERIALS SCIENCE↗

Switching charge states in quasi-2D molecular conductors

Abstract 2D molecular entities build next-generation electronic devices, where abundant elements of organic molecules are attractive due to the modern synthetic and stimuli control through chemical, conformational, and electronic modifications in electronics. Despite its promising potential, the insufficient control over charge states and electronic stabilities must be overcome in molecular electronic devices. Here, we show the reversible switching of modulated charge states in an exfoliatable 2D-layered molecular conductor based on bis(ethylenedithio)tetrathiafulvalene molecular dimers. The multiple stimuli application of cooling rate, current, voltage, and laser irradiation in a concurrent manner facilitates the controllable manipulation of charge crystal, glass, liquid, and metal phases. The four orders of magnitude switching of electric resistance are triggered by stimuli-responsive charge distribution among molecular dimers. The tunable charge transport in 2D molecular conductors reveals the kinetic process of charge configurations under stimuli, promising to add electric functions in molecular circuitry.

Huang, Yulong (ORCID:0000000296160134)↗

Arbitrary Low-Dimensional Film Transfer Enabled by GeO 2 Release Layer

Low-dimensional materials show great promise for enhanced computing and sensing performance in mission-relevant environments. However, integrating low-dimensional materials into conventional electronics remains a challenge. Here, we demonstrate a novel transfer method by which low-dimensional materials and their heterostructures can be transferred onto any arbitrary substrate. Our method relies on a water soluble GeO 2 substrate from which lowdimensional materials are transferred without significant perturbation. We apply the method to transfer a working electronic device based on a low-dimensional material. Process developments are achieved to enable the fabrication and transfer of a working electronic device, including the growth of high-k dielectric on GeO 2 by atomic layer deposition and inserting an indium diffusion barrier into the device gate stack. This work supports Sandia’s heterogeneous integration strategy to broaden the implementation of low-dimensional films and their devices.

36 MATERIALS SCIENCE↗

Phonon- and defect-limited electron and hole mobility of diamond and cubic boron nitride: A critical comparison

Diamond and cBN are two of the most promising ultra-wide bandgap semiconductors for applications in high-power high-frequency electronic devices. Despite extensive studies on carrier transport in these materials, there are large discrepancies in their reported carrier mobilities. In this work, we investigate the phonon- and dopant-limited electron and hole mobilities of cBN and diamond with atomistic first-principles calculations in order to understand their fundamental upper bounds to carrier transport. Our results show that although the phonon-limited electron mobilities are comparable between cBN and diamond, the hole mobility is significantly lower in cBN due to its heavier hole effective mass. Moreover, although lattice scattering dominates the mobility at low doping, neutral impurity scattering becomes the dominant scattering mechanism at higher dopant concentrations due to the high dopant ionization energies. Our analysis provides critical insights and reveals the intrinsic upper limits to the carrier mobilities of diamond and cBN as a function of doping and temperature for applications in high-power electronic devices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Tailored Graphene Micropatterns by Wafer-Scale Direct Transfer for Flexible Chemical Sensor Platform

2D materials, such as graphene, exhibit great potential as functional materials for numerous novel applications due to their excellent properties. The grafting of conventional micropatterning techniques on new types of electronic devices is required to fully utilize the unique nature of graphene. However, the conventional lithography and polymer-supported transfer methods often induce the contamination and damage of the graphene surface due to polymer residues and harsh wet-transfer conditions. In this work, a novel strategy to obtain micropatterned graphene on polymer substrates using a direct curing process is demonstrated. Employing this method, entirely flexible, transparent, well-defined self-activated graphene sensor arrays, capable of gas discrimination without external heating, are fabricated on 4 in. wafer-scale substrates. Finite element method simulations show the potential of this patterning technique to maximize the performance of the sensor devices when the active channels of the 2D material are suspended and nanoscaled. This study contributes considerably to the development of flexible functional electronic devices based on 2D materials.

2D materials, Graphene, Microscale patterning, Che↗

Wide bandgap semiconductor materials and devices

The technological and societal impacts of electronic devices based on Ge, Si, and compound semiconductors like GaAs have been profound, fueling the decades long quest in identifying ever-larger bandgap semiconductors to untap new applications and possibilities. Specifically, an increase in the bandgap leads to shorter wavelength emission and an increased breakdown electric field, which has direct consequences for solid-state lighting like light-emitting diodes (LEDs) and laser diodes (LDs) from the visible (blue-green, blue, and violet) and beyond (UV and deep-UV) spectral range and for radically improved power devices supported by a higher intrinsic breakdown strength. Wide bandgap (WBG) semiconductors represent the frontier of materials that satisfy these criteria and include group IV, III–V, and II–VI material families like SiC (3.2 eV), GaN (3.4 eV), and ZnO (3.4 eV), respectively. With even larger bandgaps exceeding 4 eV, ultrawide bandgap (UWBG) semiconductors include diamond, III-nitrides incorporating Al and B (e.g., AlN, BN, and AlGaN), and sesquioxides like Ga 2 O 3 and (Al,Ga) 2 O 3 . These materials span widely varying stages of technological maturity, with SiC and GaN platforms among the most mature with commercially available devices in RF and high-power electronics, while other platforms such as Ga 2 O 3 rapidly advancing and poised to enable new UV and deep-UV optoelectronic devices. This Special Topic on Wide Bandgap Semiconductor Materials and Devices covers broad research subtopics on WBG and UWBG materials that span bulk crystals, epitaxy and substrate technologies, fundamental defect science, and doping, as well as electronic and optoelectronic device fabrication and characterization. Here, we highlight works from the collection, which we categorize by material platform of SiC, III-nitrides, and Ga 2 O 3 and related alloys.

36 MATERIALS SCIENCE↗

Tuning Phase Lock Loop Controller of Grid Following Inverters by Reinforcement Learning to Support Networked Microgrid Operations

The dynamic operation of networked microgrids leads to varying topological configurations and generator commitments and dispatches. These variations correspond to systems with different electrical characteristics. The fixed control gains of high-speed power electronic devices may result in undesirable system performance when the electrical characteristics change significantly. As such, it is necessary to tune the control gains of power electronics devices to adapt to the changing system characteristics. This paper uses observer-based reinforcement learning to automatically tune the proportional-integral (PI) gains of phase lock loop (PLL) controller of grid-following (GFL) inverters to adapt to the changing system strengths, that would be seen in networked microgrid operations. Simulation results using an operational electric distribution system, modeled as networked microgrids, are presented to demonstrate the need and effectiveness of the proposed adaptive controls.

networked microgrids, reinforcement learning, grid↗

Gallium Oxide Heterojunction Diodes for 400 °C High‐Temperature Applications

β ‐Ga 2 O 3 ‐based semiconductor devices are expected to have significantly improved high‐power and high‐temperature performance due to its ultrawide bandgap of close to 5 eV. However, the high‐temperature operation of these ultrawide‐bandgap devices is usually limited by the relatively low 1–2 eV built‐in potential at the Schottky barrier with most high‐work‐function metals. Herein, heterojunction p ‐NiO/n‐ β ‐Ga 2 O 3 diodes fabrication and optimization for high‐temperature device applications are reported, demonstrating a current rectification ratio ( I ON / I OFF ) of more than 10 6 at 410 °C. The NiO heterojunction diode can achieve higher turn‐on ( V ON ) voltage and lower reverse leakage current compared to the Ni‐based Schottky diode fabricated on the same single‐crystal β ‐Ga 2 O 3 substrate, despite charge transport dominated by interfacial recombination. Electrical characterization and device modeling show that these advantages are due to a higher built‐in potential and additional band offset. These results suggest that heterojunction p–n diodes based on β ‐Ga 2 O 3 can significantly improve high‐temperature electronic device and sensor performance.

Sohel, Shahadat H.↗

Machine learning to accelerate screening for Marcus reorganization energies

Understanding and predicting the charge transport properties of π-conjugated materials is an important challenge for designing new organic electronic devices, such as solar cells, plastic transistors, light-emitting devices, and chemical sensors. A key component of the hopping mechanism of charge transfer in these materials is the Marcus reorganization energy which serves as an activation barrier to hole or electron transfer. While modern density functional methods have proven to accurately predict trends in intramolecular reorganization energy, such calculations are computationally expensive. In this work, we outline active machine learning methods to predict computed intramolecular reorganization energies of a wide range of polythiophenes and their use toward screening new compounds with low internal reorganization energies. Our models have an overall root mean square error (RMSE) of ±0.113 eV, but a much smaller RMSE of only ±0.036 eV on the new screening set. Since the larger error derives from high-reorganization energy compounds, the new method is highly effective to screen for compounds with potentially efficient charge transport parameters.

14 SOLAR ENERGY↗

Electron and hole mobility of rutile GeO 2 from first principles: An ultrawide-bandgap semiconductor for power electronics

Rutile germanium dioxide (r-GeO 2 ) is a recently predicted ultrawide-bandgap semiconductor with potential applications in high-power electronic devices, for which the carrier mobility is an important material parameter that controls the device efficiency. We apply first-principles calculations based on density functional and density functional perturbation theory to investigate carrier-phonon coupling in r-GeO 2 and predict its phonon-limited electron and hole mobilities as a function of temperature and crystallographic orientation. The calculated carrier mobilities at 300 K are μ elec , ⊥ c → = 244 cm 2 V –1 s –1 , μ elec , ∥ c → = 377 cm 2 V –1 s –1 , μ hole , ⊥ c → = 27 cm 2 V –1 s –1 , and μ hole , ∥ c → = 29 cm 2 V –1 s –1 . At room temperature, carrier scattering is dominated by the low-frequency polar-optical phonon modes. The predicted Baliga figure of merit of n -type r-GeO 2 surpasses several incumbent semiconductors such as Si, SiC, GaN, and β -Ga 2 O 3 , demonstrating its superior performance in high-power electronic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Millimeter wave traveling wave tubes for the 21st Century

Traveling wave tubes are rapidly evolving to provide unprecedented power level in comparison to solid state devices in the millimeter waves region of the spectrum (80–300 GHz) thus enabling a wide range of applications. Wireless communications, imaging, plasma diagnostics, healthcare and many others will gain substantial features if high power at millimeter waves would be available from compact sources. The development of fabrication technologies is proving crucial for introducing new topologies and structures for millimeter wave vacuum electronic devices, compatible with the dimensions dictated by the short wavelength that poses substantial manufacturing challenges due to tight tolerances. This review paper will provide an overview of the principles, evolution and state of the art of one of the most widely utilized vacuum electronic device, the traveling wave tube (TWT). The wide band, high gain features of TWTs make those devices the most promising solutions for high power at millimeter waves and THz frequencies.

42 ENGINEERING↗