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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

B 12 P 2 : Improved Epitaxial Growth and Evaluation of Alpha Irradiation on its Electrical Transport Properties

The wide bandgap (3.35 eV) semiconductor icosahedral boron phosphide (B 12 P 2 ) has been reported to self-heal from radiation damage from β particles (electrons) with energies up to 400 keV by demonstrating no lattice damage using transmission electron microscopy. This property could be exploited to create radioisotope batteries–semiconductor devices that directly convert the decay energy from a radioisotope to electricity. Such devices potentially have enormous power densities and decades-long lifetimes. To date, the radiation hardness of B 12 P 2 has not been characterized by electrical measurements nor have B 12 P 2 radioisotope batteries been realized. Therefore, this study was undertaken to evaluate the radiation hardness of B 12 P 2 after improving its epitaxial growth, developing ohmic electrical contacts, and reducing the residual impurities. Subsequently, the effects of radiation from a radioisotope on the electrical transport properties of B 12 P 2 were tested.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Zener Diode Compact Model Parameter Extraction Using Xyce-Dakota Optimization.

This report presents a detailed process for compact model parameter extraction for DC circuit Zener diodes. Following the traditional approach of Zener diode parameter extraction, circuit model representation is defined and then used to capture the different operational regions of a real diode's electrical behavior. The circuit model contains 9 parameters represented by resistors and characteristic diodes as circuit model elements. The process of initial parameter extraction, the identification of parameter values for the circuit model elements, is presented in a way that isolates the dependencies between certain electrical parameters and highlights both the empirical nature of the extraction and portions of the real diode physical behavior which of the parameters are intended to represent. Optimization of the parameters, a necessary part of a robost parameter extraction process, is demonstrated using a 'Xyce-Dakota' workflow, discussed in more detail in the report. Among other realizations during this systematic approach of electrical model parameter extraction, non-physical solutions are possible and can be difficult to avoid because of the interdependencies between the different parameters. The process steps described are fairly general and can be leveraged for other types of semiconductor device model extractions. Also included in the report are recommendations for experiment setups for generating optimum dataset for model extraction and the Parameter Identification and Ranking Table (PIRT) for Zener diodes.

42 ENGINEERING↗
DOE OSTI2015

High Performance Computing - Power Application Programming Interface Specification

Achieving practical exascale supercomputing will require massive increases in energy efficiency. The bulk of this improvement will likely be derived from hardware advances such as improved semiconductor device technologies and tighter integration, hopefully resulting in more energy efficient computer architectures. Still, software will have an important role to play. With every generation of new hardware, more power measurement and control capabilities are exposed. Many of these features require software involvement to maximize feature benefits. This trend will allow algorithm designers to add power and energy efficiency to their optimization criteria. Similarly, at the system level, opportunities now exist for energy-aware scheduling to meet external utility constraints such as time of day cost charging and power ramp rate limitations. Finally, future architectures might not be able to operate all components at full capability for a range of reasons including temperature considerations or power delivery limitations. Software will need to make appropriate choices about how to allocate the available power budget given many, sometimes conflicting considerations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Development, Demonstration and Validation of Data-Driven Compact Diode Models for Circuit Simulation and Analysis

Compact semiconductor device models are essential for efficiently designing and analyzing large circuits. However, traditional compact model development requires a large amount of manual effort and can span many years. Moreover, inclusion of new physics (e.g., radiation effects) into an existing model is not trivial and may require redevelopment from scratch. Machine Learning (ML) techniques have the potential to automate and significantly speed up the development of compact models. In addition, ML provides a range of modeling options that can be used to develop hierarchies of compact models tailored to specific circuit design stages. In this paper, we explore three such options: (1) table-based interpolation, (2) Generalized Moving Least-Squares, and (3) feedforward Deep Neural Networks, to develop compact models for a p-n junction diode. We evaluate the performance of these "data-driven" compact models by (1) comparing their voltage-current characteristics against laboratory data, and (2) building a bridge rectifier circuit using these devices, predicting the circuit's behavior using SPICE-like circuit simulations, and then comparing these predictions against laboratory measurements of the same circuit.

1N4148 switching diode↗
DOE OSTI2019

Additively Manufactured Photovoltaic Inverter (AMPVI)

Successful integration of hundreds of gigawatts of solar photovoltaics (PV) into the electric power system requires transformative power conversion system design that optimizes various trade-offs among conflicting objectives, such as performance, reliability, functionality, and cost. To address this need, National Renewable Energy Laboratory, Oak Ridge National Laboratory, and Purdue University teamed up to develop a unique PV inverter design. The Additively Manufactured Photovoltaic Inverter (AMPVI) combines newer wide bandgap high-voltage silicon carbide (SiC) semiconductor devices with revolutionary concepts such as additive manufacturing and multi-objective magnetic design optimization. The AMPVI will not only provide superior technical capabilities in terms of energy conversion but also mitigate market barriers for SiC-based PV inverters. The benefits for this design will include better utilization of PV power due to higher DC voltage, lower operations and maintenance costs, better system efficiency, longer system lifetime, and advanced grid support functionalities for easier grid integration. All these advantages will lead to a significant reduction of the levelized cost of energy for PV systems. Activities in Budget Period 1 (BP1) of this 3-year integrated project were focused on development and component-level validation of the foundational building blocks needed for the AMPVI. Multiple interrelated tasks were completed in parallel during work towards the initial development of the high-voltage SiC-based power block, gate driver, controller board, and control algorithms. Initial development of magnetic design tools and initial inverter thermal and mechanical design was also completed in this period. All these activities ensured that the initial prototype (called “alpha-prototype”) power block and controller would be ready after BP1 for integration into the first inverter prototype (i.e., the alpha-prototype inverter) in BP2.

14 SOLAR ENERGY↗
DOE OSTI2020

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Charon User Manual (V.2.1) (Rev.01)

This manual gives usage information for the Charon semiconductor device simulator. Charon was developed to meet the modeling needs of Sandia National Laboratories and to improve on the capabilities of the commercial TCAD simulators; in particular, the additional capabilities are running very large simulations on parallel computers and modeling displacement damage and other radiation effects in significant detail. The parallel capabilities are based around the MPI interface which allows the code to be ported to a large number of parallel systems, including linux clusters and proprietary "big iron" systems found at the national laboratories and in large industrial settings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Collaborative Research: Advancing the Physics of Magnetized Dusty Plasmas (Final Scientific /Technical Report)

A plasma is a gas of charged particles – electrons and positive ions in roughly equal concentrations. Plasmas are formed by stripping electrons from neutral atoms and molecules. It is believed that the plasma state of matter comprises over 99% of the universe. Often the plasma coexists with small (1/1000 of a millimeter) dust particles. Some of the plasma particles collect on the dust grains which cause it to be electrically charged, and so become an integral part of the plasma, forming what is called a “dusty plasma”. The large objects in the universe (planets, asteroids, comets, stars) are formed by combining dust grains into larger and larger objects, eventually held together by their self-gravitational attraction. Thus, an understanding of the processes that control the structure and evolution of the universe, requires that we understand the behavior of dusty plasmas. These plasmas also often are embedded in magnetic fields which has a strong influence on their structure and behavior. Thus, developing an understanding of dusty plasmas in magnetic fields, so-called magnetized dusty plasmas, is also essential. In addition to the dusty plasmas occurring in nature, dusty plasmas play an important role in many plasma-based technologies, such as the production of semiconductor devices, and in the next generation of clean-and-green-energy producing devices based on nuclear fusion. The purpose of the work performed with funding provided in this grant by the United States Department of Energy was to produce and investigate the physics of magnetized dusty plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Charon User Manual: v. 2.2 (revision1)

This manual gives usage information for the Charon semiconductor device simulator. Charon was developed to meet the modeling needs of Sandia National Laboratories and to improve on the capabilities of the commercial TCAD simulators; in particular, the additional capabilities are running very large simulations on parallel computers and modeling displacement damage and other radiation effects in significant detail. The parallel capabilities are based around the MPI interface which allows the code to be ported to a large number of parallel systems, including linux clusters and proprietary “big iron” systems found at the national laboratories and in large industrial settings.

42 ENGINEERING↗
DOE OSTI2022

Considerations of Radiation-Hardened Electronics for Alpha Detectors in Molten Salt Reactors

Along with advanced generations of reactors quickly becoming reality, the need for instrumentation to provide reliable information for their safety and operation is also becoming relevant. Instrumentation-wise, molten salt reactors (MSRs) represent an especially challenging case in which detectors must survive extreme temperatures, high amounts of radiation, and a highly corrosive coolant. Adding to the complexity, tight material control and accounting must be maintained with any special nuclear material (SNM), a practice made more difficult by the nature of a loop of flowing fuel. Alpha spectroscopy offers a unique window into investigating the isotopic concentrations of actinides within just such a molten salt environment. The characteristic α emissions of specific actinide isotopes in the salt enable quantification of their concentrations. Semiconductor devices based on wide bandgap materials such as silicon carbide and gallium oxide can withstand the extreme temperatures within MSRs and offer good chemical stability with the corrosive salt. Collaborators at The Ohio State University are fabricating and testing a β gallium oxide α particle sensor that could identify actinide concentrations within the fuel salt to help improve the material control and accounting required for complicated system inherent to MSRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Next-Generation Modular Flexible Low-Cost SiC-based High-Frequency-Link Transformer (Final Technical Report)

This project, led by the small business NextWatt LLC, led to the design and development of a novel high-frequency-link (HFL) transformer that yields reduce number of semiconductor devices compared to conventional solid-state transformers (SSTs). The HFL transformer is based on SiC device technology and nanocrystalline-core-based magnetics techniology. The control actuation of the SiC devices are algorithmically implemented in digital signal processor (DSP) platform. The overall HFL transformer technology is conceived and developed using a modular approach. During the course of the project the novel technology and its experimental performances at the module, multi-phase, and cascaded multi-phase levels have been demonstrated to the sponsor U.S. Department of Energy (DOE).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Understanding the Structure and Dynamics of Conjugated Polymers by Advancing Deuteration Chemistry and Neutron Scattering (Final Report)

The overarching goal of the proposed work was to set up a partnership between the University of Southern Mississippi (USM) and Oak Ridge National Laboratory (ORNL) to develop novel approaches to measure the backbone rigidity of conjugated polymers (CPs) and understand the critical role of sidechains on the backbone conformation and the materials macroscopic property. The backbone rigidity greatly influences the electronic properties of CPs, which ultimately determines the functionality and performance of these materials. Improvements in the electronic properties of CPs would allow for enhanced charge transport in semiconductor devices, improved photovoltaic performance, recycling of waste heat in thermoelectrics, and discovery of new phenomena that will enable the next generation of energy technologies. Although significant progress has been made to optimize the optical and electronic properties of CPs, largely through Edisonian methodologies, it remains a challenge to experimentally characterize conjugated backbone conformation (chain rigidity, torsion, planarity, and short-range order) and relate these to the fundamental optical and electronic properties (electronic coupling, charge transport, etc.). This has left fundamental gaps in our knowledge of the most basic structure/property relationships within these systems, precluded the study of fundamental physical phenomena, and constrained the design and realization of new electronic and device functionalities. Thus, the major goal of this work is to use novel deuteration methodologies via systematic synthetic approaches, and neutron scattering techniques to comprehensively characterize the structural and dynamic properties of CPs in contrast-matching solvents. Our work would, for the first time, elucidate the relationship between backbone rigidity and macroscopic properties. They will also allow a rational formulation of design principles for next-generation CPs that are resilient to disorder through precise control of the delocalized electrons along the polymer backbone. Overall, this project will advance our understanding of the structure, dynamics, and fundamental physics of these materials, which is crucial for enabling the prediction, design, control, and manipulation of current and emerging material electronic properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Single DC Source Based Cascaded Multilevel Inverter

The objective of this project is to develop a high-efficiency solid-state transformer that converts a fixed DC voltage to a medium-voltage AC for utility distribution network connections without having the conventional low-frequency bulky transformers and switch gears. The initial target of 99% efficiency was achieved with the use of wide bandgap semiconductor devices using a proposal novel multilevel inverter. The medium-voltage was successfully tested at 7.2/12.47 kV phase/line voltage level for a 100-kW three-phase inverter.

14 SOLAR ENERGY↗
DOE OSTI2023

Electrification: 2023 Final Progress Report

This project proposes to develop a high-power density, high speed traction motor architecture called QMag, driven by a high-power density motor drive inverter using silicon carbide semiconductor devices. This new architecture will achieve the efficiency and power density targets by means of innovative winding and rotor structures, high bandwidth controls, and advanced thermal management solutions. The project team will pursue the goals of the project systematically, through Finite Element Analysis for machine design, through simulation and co-simulation techniques for power electronics and controls evaluation, and finally system design, fabrication, testing and evaluation. If this project successfully achieves and demonstrates the DOE targets for power density, cost, and reliability, the technology has the potential to become a core enabler of the flagship higher power product portfolio in commercial traction businesses, which has so far been confined to DC, induction, Brush Less DC (BLDC), Permanent Magnet AC (PMAC), and reluctance machines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

MLSPICE: Machine Learning based SPICE Modeling Platform for Power Magnetics

Electrical power converters are critical to a wide range of applications ranging from renewable integration to transportation electrification, and can be a key factor determining the size, weight, and efficiency of energy conversion systems. Magnetic components are typically the largest and least efficient components in power electronics. While there have been major strides in the modeling and analysis of power semiconductor devices and circuit simulations, the necessary advances in the design of power magnetics have lagged. In this project, we have transformed the modeling and design of power magnetics with machine learning enabled methods and catalyze simultaneous disruptive improvements for ML-based power electronics design tools. A fully automated open-source machine learning based magnetics modeling platform – the MagNet project - with innovations in full stack have been developed to greatly accelerate the design process and provide new insights to magnetic material and geometry design. The ARPA-E funded MagNet platform contains three major building blocks: 1) a ML-Integrated Data Acquisition System (MIDAS): a highly automated data acquisition testbed which is capable of measuring a large number of magnetic cores with a wide range of electrical circuit excitations; 2) a ML-integrated Core Loss Model (MICLM): a machine-learning trained modeling method for modeling the core loss and saturation effects of magnetic materials for arbitrary excitation waveforms; 3) ML-guided Magnetics SPICE Simulation Tool (PMSPICE): a fully integrated CAD tool which can simulate the magnetics in SPICE. It can help the designers to quickly model the linear and non-linear characteristics of magnetic components and evaluate their behavior in SPICE simulations. The developed MagNet system has fully demonstrated the proposed performance target and has been open sourced to the entire power electronics community to advance the modeling and design of power magnetics from many different angles.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Prediction of Alpha-Particle-Immune Gate-All-Around Field-Effect Transistors (GAA-FET) Based SRAM Design

Alpha particles are known to be a major source of particles creating soft errors in semiconductor devices, such as content flipping in Static Random-Access Memory (SRAM). Recent advancements in transistor nodes have led to the introduction of Gate-All-Around Field Effect Transistors (GAA-FETs), which have better gate control, thus better electrostatics. Moreover, the introduction of bottom dielectric isolation (BDI) eliminates substrate leakage and thus is expected to enhance its radiation hardness. It is thus important to explore if one can design an SRAM that is completely radiation-hard to alpha particles. In this paper, using 3D Technology Computer-Aided-Design (TCAD) simulations, we show that it is possible to design an SRAM using GAA-FET technology so that it is immune to single alpha particle radiation error. In other words, with the design, there will be no single-event upset (SEU) due to alpha particles. We first use ab initio calculations in PHITS to show that there is a maximum linear energy transfer (LET), LET max , for the alpha particle in Si and Si x Ge 1-x . Based on that, by de signing a sub-7nm GAA-FET-based SRAM with BDI, we show that the SRAM does not flip even if the particle strike is in the worst-case scenario for LET > LET max .

42 ENGINEERING↗
DOE OSTI2025

Detector Performance on Surface Passivation and its Long-Term Stability

Surface passivation is an ideal technique to prepare the surfaces of fabrication Cadmium Zinc Telluride (CZT) and related semiconductor devices such as Cadmium Zinc Tellurium Selenide (CZTS). Surface passivation techniques reduce the effects of aging in the detector [1]. Surface performance effects on material performance can result in fluctuations in energy resolution over time (such as periods of a year or more). The long-term stability of surface passivation with Potassium Hydroxide (KOH) was observed with measurement of 1) current (nano Amp) vs voltage (V) and 2) spectral response and energy resolution throughout the years. Three CZTS detector samples of M2, M3, and M4 were examined using a photomultiplier tube and voltage amplifier. The Bridgman technique is used to grow the CZTS used in this study.

Johnson, Kirsten [Morgan State Univ., Baltimore, M↗