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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Kinetically controlled metal-elastomer nanophases for environmentally resilient stretchable electronics

Nanophase mixtures, leveraging the complementary strengths of each component, are vital for composites to overcome limitations posed by single elemental materials. Among these, metal-elastomer nanophases are particularly important, holding various practical applications for stretchable electronics. However, the methodology and understanding of nanophase mixing metals and elastomers are limited due to difficulties in blending caused by thermodynamic incompatibility. Here, we present a controlled method using kinetics to mix metal atoms with elastomeric chains on the nanoscale. We find that the chain migration flux and metal deposition rate are key factors, allowing the formation of reticular nanophases when kinetically in-phase. Moreover, we observe spontaneous structural evolution, resulting in gyrified structures akin to the human brain. The hybridized gyrified reticular nanophases exhibit strain-invariant metallic electrical conductivity up to 156% areal strain, unparalleled durability in organic solvents and aqueous environments with pH 2–13, and high mechanical robustness, a prerequisite for environmentally resilient devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Visual Style Elements in Human–System Interface Design for Nuclear Power Operations: Does Style Affect Performance and Preference?

As the world increasingly adopts renewable and sustainable energy systems, transitionary solutions include nuclear power, which currently provides 20% of the United States’ electricity and is the largest single source of carbon-free electricity generation. Advanced reactors are a critical component of a carbon-free mixed energy portfolio that require careful design of first-of-a-kind control rooms. The application of Human Factors Engineering (HFE) is essential for scientific and iterative testing of novel human–system interface (HSI) concepts to ensure effective, efficient, and safe plant operations. Microworlds are simulators that use simplified physics models and control systems to distill nuclear power operations into essential functions. HFE scientists used the Rancor Microworld Simulator to obtain preference and performance metrics for novel and traditional static HSI design styles. Participants comprised advanced reactor company employees and nuclear industry consultants. A mixture of quantitative and qualitative data was captured. There was a preference for the basic graphical style that included high contrast and traditional color scheme elements. No single HSI design outperformed the others, and the participants did not perform better using their preferred HSI style. We report this experiment is the first in a series of HFE testing for HSIs in advanced reactor control room development. Clear user preferences emerged for elements within static displays. The cutting-edge neumorphic style was the least preferred. Future directions include tests of dynamic displays. HFE is used in evaluating and designing HSI devices that will improve the efficiency and safety of advanced nuclear power operations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Multiscale design of nonlinear materials using a Eulerian shape optimization scheme

Motivated by recent advances in manufacturing, the design of materials is the focal point of interest in the material research community. One of the critical challenges in this field is finding optimal material microstructure for a desired macroscopic response. This work presents a computational method for the mesoscale-level design of particulate composites for an optimal macroscale-level response. The method relies on a custom shape optimization scheme to find the extrema of a nonlinear cost function subject to a set of constraints. Three key “modules” constitute the method: multiscale modeling, sensitivity analysis, and optimization. Multiscale modeling relies on a classical homogenization method and a nonlinear NURBS-based generalized finite element scheme to efficiently and accurately compute the structural response of particulate composites using a nonconformal discretization. A three-parameter isotropic damage law is used to model microstructure-level failure. An analytical sensitivity method is developed to compute the derivatives of the cost/constraint functions with respect to the design variables that control the microstructure's geometry. The derivation uncovers subtle but essential new terms contributing to the sensitivity of finite element shape functions and their spatial derivatives. Several structural problems are solved to demonstrate the applicability, performance, and accuracy of the method for the design of particulate composites with a desired macroscopic nonlinear stress-strain response.

42 ENGINEERING↗
DOE OSTI2025

Grain Boundary Segregation Suppresses Local Short‐Range Ordering in Nanocrystalline High‐Entropy Alloys

Multi-principal-element alloys like high-entropy alloys (HEAs) have potential applications in many engineering fields due to their unique mechanical/functional properties. While HEAs are generally considered random solid solutions, recent studies revealed that they are prone to short-range-ordering (SRO) due to the complex multi-pair-wise interactions among the constituent elements. Meanwhile, SROs' evolution can sometimes be deleterious, and it is necessary to have control over their evolution. Examining the AlCoCrFe-Zr model alloy, long-range ordering occurs following the expectation of enthalpic predictions. Advanced characterization techniques—transmission electron microscopy, high-energy synchrotron X-ray diffraction/pair distribution function, and atom probe tomography, reveal that SRO is suppressed in as-milled and GB-decorated NC-(AlCoCrFe)100-xZrx (x = 0–1.5 atomic %). Warren-Cowley coefficient calculations are further used to validate the suppression of SRO. Besides the low segregation enthalpies of Cr, Fe, and Zr, and the high-mixing enthalpy of Cr and Fe, the short diffusion path to GBs due to high-GB density in the NC-HEAs and the higher energy state of the GBs than the matrix promotes GB-segregation that further alters the matrix chemistry and consequently disfavors SRO formation within the matrix. Despite the GB-segregation of Cr, Fe, and Zr, the matrices and GBs remain in a random solid solution.

36 MATERIALS SCIENCE↗
DOE OSTI2022

COMPILE: a GWAS computational pipeline for gene discovery in complex genomes

Abstract Background Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity. Results COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer ( Ostrinia nubilalis ). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity. Conclusions The relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Machine learning approaches to streamline and enhance the analysis of multiscale imaging data for bioaerosol and soil particles

Bioaerosol and soil particles are ubiquitous in the environment. They are multicomponent and complex in nature displaying mixed inorganic and organic components. The way components are mixed in a bioaerosol sample is referred to as its mixing state. Soil particles are also a mixture of inorganic (mineral) and organic (soil organic matter) components. Bioaerosol particles contribute to a major fraction of coarse mode atmospheric particles, especially in the tropical areas, contributing up to 80 % of the particle mass concentration. The mixing state of particles is crucial to evaluate because it impacts several important environmental processes such as warm and cold cloud formation and radiation budget. Mixing states in aerosols are accompanied by chemical reactions across solid-liquid-gas interfaces. In this study, we utilized elemental compositions and microcopy images of thousands of atmospheric particles acquired by computer-controlled scanning electron microscope equipped with an energy-dispersive x-ray spectrometer to compute the mixing state of atmospheric particles. A 2D convolutional neural network (CNN), also known as convnet, was used to model the relationship between low resolution imaging data and higher resolution spectroscopy data, with the former as training input and the latter as target output. Two types of CNNs were implemented and tested; a basic CNN and an Inception-v3 network. For binary classification, the basic CNN achieved an accuracy of 84.29 % across all atom types, and the Inception-v3-like network achieved an accuracy 85.51 %. This study demonstrates the applicability of deep learning to handle large amounts of imaging/chemical spectroscopy data efficiently and evaluate particle mixing state from a range of environmental samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Review on Metallic Alloys Fabrication Using Elemental Powder Blends by Laser Powder Directed Energy Deposition Process

The laser powder directed energy deposition process is a metal additive manufacturing technique, which can fabricate metal parts with high geometric and material flexibility. The unique feature of in-situ powder feeding makes it possible to customize the elemental composition using elemental powder mixture during the fabrication process. Thus, it can be potentially applied to synthesize industrial alloys with low cost, modify alloys with different powder mixtures, and design novel alloys with location-dependent properties using elemental powder blends as feedstocks. This paper provides an overview of using a laser powder directed energy deposition method to fabricate various types of alloys by feeding elemental powder blends. At first, the advantage of laser powder directed energy deposition in manufacturing metal alloys is described in detail. Then, the state-of-the-art research and development in alloys fabricated by laser powder directed energy deposition through a mix of elemental powders in multiple categories is reviewed. Finally, critical technical challenges, mainly in composition control are discussed for future development.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Adjustable-beam luminaires with automatic beam controller

A luminaire for providing configurable static lighting or dynamically-adjustable lighting. The luminaire uses an array of focusing elements that act on light provided via a corresponding array of sources or via an edge-lit lightguide. Designs are provided for adjusting the number of distinct beams produced by the luminaire, as well as the angular width, angular profile, and pointing angle of the beams. Designs are also provided for systems utilizing the adjustable luminaires in various applications.

Gladden, Christopher↗
DOE OSTI2020

Computationally aided, entropy-driven synthesis of highly efficient and durable multi-elemental alloy catalysts

Multi-elemental alloy nanoparticles (MEA-NPs) hold great promise for catalyst discovery in a virtually unlimited compositional space. However, rational and controllable synthesize of these intrinsically complex structures remains a challenge. Here, we report the computationally aided, entropy-driven design and synthesis of highly efficient and durable catalyst MEA-NPs. The computational strategy includes prescreening of millions of compositions, prediction of alloy formation by density functional theory calculations, and examination of structural stability by a hybrid Monte Carlo and molecular dynamics method. Selected compositions can be efficiently and rapidly synthesized at high temperature (e.g., 1500 K, 0.5 s) with excellent thermal stability. We applied these MEA-NPs for catalytic NH 3 decomposition and observed outstanding performance due to the synergistic effect of multi-elemental mixing, their small size, and the alloy phase. We anticipate that the computationally aided rational design and rapid synthesis of MEA-NPs are broadly applicable for various catalytic reactions and will accelerate material discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Adaptive shape control of wavefront-preserving X-ray mirrors with active cooling and heating

This article describes the development and testing of a novel, water cooled, active optic mirror system (called “REAL: Resistive Element Adjustable Length”) that combines cooling with applied auxiliary heating, tailored to the spatial distribution of the thermal load generated by the incident beam. This technique is theoretically capable of sub-nanometer surface figure error control even at high power density. Tests conducted in an optical metrology laboratory and at synchrotron X-ray beamlines showed the ability to maintain the mirror profile to the level needed for the next generation storage rings and FEL mirrors.

42 ENGINEERING↗
DOE OSTI2026

How Inverter-Based Resources (IBRs) Affect Protection Relay Elements

This presentation starts with the details of IEEE 2800-2022 requirements of IBR for balanced and unbalanced faults. Then, it shows how to design a droop based GFM control to be IEEE 2800-2022 compliant. An performance evaluation is carried out to see if three OEM GFM inverters 2800-2022 compliant or not. And finally we show how IEEE 2800-2022 complaint and non-compliant GFM inverter will impact the transmission line protection elements, such as directional element and FID. Finally, recommendations are made if the GFM is not IEEE 2800-2022 compliant to disable the protection elements that rely on reliable and regulated negative sequence current.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Thermal Management of Wide-Bandgap Semiconductor Amplifiers Used for Plasma Heating and Control

Princeton Fusion Systems (PFS) has designed, built, and tested a Load Switch printed circuit board (PCB) to demonstrate the capabilities of 2 kV silicon carbide (SiC) cascodes in development by Qorvo towards plasma heating and control applications. Initial tests have been conducted at low power (~100 W) for validation with thermal finite element analysis (FEA) modeling performed by the National Renewable Energy Laboratory (NREL). Comparisons of experimental data with the thermal modeling results, along with considerations for operating in plasma systems, will be discussed.

CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SU↗
DOE OSTI2021

A Nuclear Security Enterprise Study of High-Reliability Systems, Collaboration, and Data

It may seem simple and trivial, but defining the difference between data and information is contested and has implications that may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and controlling them. Control is necessary to ensure that data and information are not inadvertently released to foreign governments, the public, or those without Need-to-Know. A primary concern in the practice of security is the control of data to avoid the inadvertent conversion to sensitive information. The complexity of this concern is further augmented when institutions are part of tightly coupled networks that informally share data and information. Additionally, those that share data as a function of legislative action—and/or formally integrate data and information system infrastructures—may be a higher security risk. This paper will present a case study that utilizes elements of literature from Knowledge Management and networks to tell a story of an issue in security—specifically, controlling the conversion of data to information.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

MASTODON: An Open-Source Software for Seismic Analysis and Risk Assessment of Critical Infrastructure

Seismic analysis and risk assessment of safety-critical infrastructure like hospitals, nuclear power plants, dams, and facilities handling radioactive materials involve computationally intensive numerical models and coupled multiphysics scenarios. They are also performed in a strict regulatory environment that requires high software quality assurance standards, and in the case of safety-related nuclear facilities, a conformance to the American Society of Mechanical Engineers Nuclear Quality Assurance (NQA-1) standard. This paper introduces the open-source finite-element software, MASTODON (Multi-hazard Analysis of Stochastic Time-Domain Phenomena), which implements state-of-the-art seismic analysis and risk assessment tools in a quality-controlled environment. MASTODON is built on MOOSE (Multi-physics Object-Oriented Simulation Environment), which is a highly parallelizable, NQA-1 conforming, coupled multiphysics, finite-element framework developed at Idaho National Laboratory. MASTODON is capable of fault rupture and source-to-site wave propagation using the domain reduction method, nonlinear site response, and soil-structure interaction analysis, implicit and explicit time integration, automated stochastic simulations, and seismic probabilistic risk assessment. When coupled with other MOOSE applications, MASTODON can also solve strongly and weakly coupled multiphysics problems. This paper presents a summary of the capabilities of MASTODON and some demonstrative examples.

42 ENGINEERING↗
DOE OSTI2024

Protocol-dependent frictional granular jamming simulations: cyclical, compression, and expansion

Granular matter takes many paths to pack in natural and industrial processes. The path influences the packing microstructure, particularly for frictional grains. We perform discrete element modeling simulations of different paths to construct packings of frictional spheres. Specifically, we explore four stress-controlled protocols implementing packing expansions and compressions in various combinations thereof. We characterize the eventual packed states through their dependence of the packing fraction and coordination number on packing pressure, identifying non-monotonicities with pressure that correlate with the fraction of frictional contacts. These stress-controlled, bulk-like particle simulations access very low-pressure packings, namely, the marginally stable limit, and demonstrate the strong protocol dependence of frictional granular matter.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Zn‐Doped P‐Type InAs Nanocrystal Quantum Dots

Abstract Doped heavy metal‐free III–V semiconductor nanocrystal quantum dots (QDs) are of great interest both from the fundamental aspects of doping in highly confined structures, and from the applicative side of utilizing such building blocks in the fabrication of p–n homojunction devices. InAs nanocrystals (NCs), that are of particular relevance for short‐wave IR detection and emission applications, manifest heavy n‐type character poising a challenge for their transition to p‐type behavior. The p‐type doping of InAs NCs is presented with Zn – enabling control over the charge carrier type in InAs QDs field effect transistors. The post‐synthesis doping reaction mechanism is studied for Zn precursors with varying reactivity. Successful p‐type doping is achieved by the more reactive precursor, diethylzinc. Substitutional doping by Zn 2+ replacing In 3+ is established by X‐ray absorption spectroscopy analysis. Furthermore, enhanced near infrared photoluminescence is observed due to surface passivation by Zn as indicated from elemental mapping utilizing high‐resolution electron microscopy corroborated by X‐ray photoelectron spectroscopy study. The demonstrated ability to control the carrier type, along with the improved emission characteristics, paves the way towards fabrication of optoelectronic devices active in the short‐wave infrared region utilizing heavy‐metal free nanocrystal building blocks.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Site Energy Management System Platform Development

A site energy management system is a critical component of future high-power EV charging hubs. It monitors and supervises all inter-hub operations, coordinates grid interactions, and implements energy management strategies and load-sharing controls at various levels and time scales. This report provides a comprehensive high-level overview and guidelines on the essential elements of such energy management systems. These elements primarily focus on the core functions, architecture, and monitoring aspects of site energy management. The core functions define the grid services and operational objectives that a charging hub is expected to provide and achieve. The architectural section investigates the coordination between hub assets, different control schemes, and their potential benefits and drawbacks. Lastly, the report discusses the needs, types, and functionalities of a monitoring and visualization system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Leveraging slow $\mathrm{DOTA}$ f-element complexation kinetics to enable separations by kinetic design

The design of metal-concerned solvent extraction systems frequently leverages thermodynamically derived differences in selectivity. An alternative approach, leveraging kinetic control, has been considered much less seriously. Our recent manuscript describing DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) complexation kinetics across the lanthanide series shows the observed rate constant steadily increases across the series, with some non-monotonic behavior observed at terbium and thulium. This contrasts the thermodynamic stability constant trend, where lanthanide-DOTA stability constants initially increase and then plateau as a function of ionic radii after samarium. To leverage the kinetic differences of DOTA with the lanthanides across the series, kinetically based separations must be utilized. Since DOTA has very slow complexation kinetics, a separations system must expedite DOTA-metal complexation to allow a separation approximating practical application. Here in this report, a DOTA-based solvent extraction system, where DOTA is the aqueous holdback reagent and bis-2,4,4-trimethylpentylphosphinic acid (Cyanex 272) is the organic phase extractant, is demonstrated and compares the separations chemistry of Nd, Eu and Am. The slowness of DOTA complexation was addressed by heating the system. Results showed, in general, separation between metals is better during early phase contact, and diminishes under longer contact times. Under all conditions, separations are better than would be predicted based on a thermodynamic basis. This report suggests that while slowly complexing ligands classically used for biological applications may not be appropriate for thermodynamically designed metal separations, their use for kinetically based systems may be appropriate and enable a new design basis for f-element separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗