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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pore-Edge Tailoring of Single-Atom Iron–Nitrogen Sites on Graphene for Enhanced CO 2 Reduction

Hosting atomically dispersed nitrogen-coordinated iron sites (Fe-N 4 ) on graphene offers unique opportunities for driving electrochemical CO 2 reduction reaction (CO 2 RR) to CO. However, the strong adsorption of *CO on the Fe-N 4 site embedded in intact graphene limits current density due to slow CO desorption process. Herein, we report how the manipulation of pore edges on graphene alters the local electronic structure of isolated Fe-N 4 sites and improves their intrinsic reactivity for prompting CO generation. We demonstrate that constructing holes on graphene basal plane to support Fe-N 4 can significantly enhance its CO 2 RR compared to the pore-deficient graphene-supported counterpart, exhibiting a CO Faradaic efficiency of 94% and a turnover frequency of 1630 h -1 at 0.58 V vs RHE. Mechanistic studies reveal that the incorporation of pore edges results in the downshifting of the d-band center of Fe sites, which weakens the strength of the Fe-C bond when the *CO intermediate adsorbs on edge-hosted Fe-N 4 , thus boosting the CO desorption and evolution rates. These findings suggest that engineering local support structure renders a way to design high-performance single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Evolution at the Edge: Real-Time Evolution for Neuromorphic Engine Control

Neuromorphic computing systems are attractive for real-time control at the edge because of their low power operation, real-time processing capabilities and their potential ability to do online learning. In this work, we describe an approach for performing real-time evolution of spiking neural networks for neuromorphic systems at the edge called Neuromorphic Optimization using Dynamic Evolutionary Systems or NODES. We apply this approach to real-time combustion engine control and develop an engine-specific hardware platform for NODES called FireBox. We demonstrate how the real-time evolution approach works in simulation and the performance of networks trained in simulation on the physical engine.

Maldonado Puente, Bryan [ORNL] (ORCID:000000033880↗
DOE OSTI2021

An Abrasive Wear Model of Knife Milling to Predict the Impact of Material Properties and Milling Parameters on Knife Edge Recession

A workable analytical abrasion model that relates critical knife-mill process parameters (geometry and rotational speed) to critical material attributes of inorganic mineral species in feedstock (density, size, and aspect ratio) and substrate (hardness and elastic modulus) was formulated to model wear of knives in knife-milling systems. Results of the model were compared to experimental observations of the edge recession of knives used in a knife mill marketed by Eberbach. Results showed good agreement between the predicted and measured shape of a worn knife and showed that a quality-by-design approach can be developed to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Manifold projection image segmentation for nano-XANES imaging

As spectral imaging techniques are becoming more prominent in science, advanced image segmentation algorithms are required to identify appropriate domains in these images. We present a version of image segmentation called manifold projection image segmentation (MPIS) that is generally applicable to a broad range of systems without the need for training because MPIS uses unsupervised machine learning with a few physically motivated hyperparameters. We apply MPIS to nanoscale x-ray absorption near edge structure (XANES) imaging, where XANES spectra are collected with nanometer spatial resolution. We show the superiority of manifold projection over linear transformations, such as the commonly used principal component analysis (PCA). Moreover, MPIS maintains accuracy while reducing computation time and sensitivity to noise compared to the standard nano-XANES imaging analysis procedure. Finally, we demonstrate how multimodal information, such as x-ray fluorescence data and spatial location of pixels, can be incorporated into the MPIS framework. We propose that MPIS is adaptable for any spectral imaging technique, including scanning transmission x-ray microscopy, where the length scale of domains is larger than the resolution of the experiment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

KS4A-Omics1.0_FspDS682

Soil fungi facilitate the translocation of inorganic nutrients from soil minerals to other microorganisms and plants. This ability is particularly advantageous in impoverished soils, because fungal mycelial networks can bridge otherwise spatially disconnected and inaccessible nutrient hotspots. However, the molecular mechanisms underlying fungal mineral weathering and transport through soil remains poorly understood. Here, we addressed this knowledge gap by directly visualizing nutrient acquisition and transport through fungal hyphae in a mineral doped soil micromodel using a multimodal imaging approach. Here, we observed how a representative of common saprotrophic soil fungi, Fusarium sp. DS 682, exhibited a mechanosensory response (thigmotropism) around obstacles and through pore spaces (~12 μm) in the presence of minerals.This study establishes the significance of fungal biology and nutrient translocation mechanisms in maintaining fungal growth under water and nutrient limitations in a soil-like microenvironment, using a high-throughput multi-omic analysis approach. Data package KS4A-Omics.1.0_FspDS682 (Publication: Fungal Mineral Weathering Mechanisms Revealed Through Direct Molecular Visualization) contents reported here are the first version (1.0) and contain pre- and post-processed data using high throughput data capture technologies for multi-omic analysis and integration, this data package contains raw and post-processed experimental data for X-Ray Absorption Near Edge Structure Spectroscopy (XANES/XRF), Optical Microscopy, Proteomics, Scanning Electron Microscope (SEM), Time-of-Flight Secondary Ion Mass Spectroscopy (ToF-SIMS), X-Ray Diffraction Spectroscopy (XRD) files, and X- Ray Photoelectron Spectroscopy (XPS) using EMSL capabilities. This data package DOI contains a comprehensive collection of high-throughput multi-omics data and process metadata catalog. Support files include additional data download contents “Read Me” with dataset descriptor information and data source method application ontologies (see data dictionary section). Reported data download content is structured for compliance with reported guidelines provided by community standard initiatives and publisher stakeholder policies supporting FAIR data principles.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Synchrotron based transient x-ray absorption spectroscopy for emerging solid-state energy materials

The rational design of cutting-edge materials for an efficient solar energy conversion process is a challenging task, which demands a fundamental understanding of the mechanisms operative during the photoinduced physical and chemical reactions. In response to these issues, progress in the field has steered attention toward the use of time-resolved spectroscopic techniques to resolve the multiple intermediate species involved in these photoinduced reactions. Thanks to the advent of pump–probe technique, which leads to the development of various time-resolved spectroscopic methods, significant progress has been made in understanding the photophysical and photochemical properties (e.g., excited state dynamics, charge transfer mechanism, charge separation dynamics, etc.) of energy materials. Synchrotron-based x-ray transient absorption (XTA) spectroscopy is one of the most important time-resolved techniques to unravel the direct correlation of the material structure with their photophysical properties owing to its unique capability in directly observing electronic and structural evolution simultaneously. As a result, the aim of this work is to provide a systematic overview of the recent progress in using XTA for capturing the structural dynamics associated with excited state and charge separation dynamics in emerging solid-state energy materials.

14 SOLAR ENERGY↗
DOE OSTI2022

Degradation of Edge-Defined Film-Fed Silicon Glass–Glass Modules on Florida Rooftop After 22 Years

Thin silicon (< 100 μm) adoption can provide significantly lower cost. Kerfless technologies provide thin wafers while preventing material from being wasted. Understanding how this family of processing influences module reliability is important. A set of four edge-defined film-fed growth (EFG) silicon modules from a ten-module system in Florida is measured after 22 years of exposure. Power loss rates of 0.58–0.78% year -1 are measured for three modules, while a rate of 1.32% is measured for a module with severe delamination and corrosion. Short-circuit current degrades between 10.7% and 13.1% for all modules. Further, the losses are primarily optical and recombination based; however, series and shunt resistance effects play a non-negligible role. Pre-existing recombination losses exist but are exacerbated via degradation. Optical losses in short-circuit current are due in part to encapsulant yellowing. Electroluminescence (EL) images display the effects of processing on bulk quality by clearly showing lines of alternating brightness along the wafer length. To the authors’ knowledge, this is the first article displaying suns–V OC data, effective lifetime versus excess carrier density data, and module EL images for EFG silicon-based modules.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cell-Edge Detection via Selective Cooperation and Generalized Canonical Correlation

Improving the uplink quality of service for users located around the boundaries between cells is a key challenge in cellular systems. Existing approaches relying on power control throttle the rates of cell-center users, while multi-user detection requires accurate channel estimates for the cell-edge users, which is another challenge due to their low received signal-to-noise ratio (SNR). Utilizing the fact that cell-edge user signals are weak but common (received at roughly equal power) at different base stations (BSs), this paper establishes a connection between cell-edge user detection and generalized canonical correlation analysis (GCCA). It puts forth a GCCA-based method that leverages selective BS cooperation to recover the cell-edge user signal subspace even at low SNR. The cell-edge user signals can then be extracted from the resulting mixture via algebraic signal processing techniques. The paper includes theoretical analysis showing why GCCA recovers the correct subspace containing the cell-edge user signals under mild conditions. The proposed method can also identify the number of cell-edge users in the system, i.e., the common subspace dimension. Simulations reveal significant performance improvement relative to various multiuser detection techniques. Cell-edge detection performance is further studied as a function of how many / which BSs are selected, and it is shown that using the closest three BS is always the best choice.

base station cooperation↗
DOE OSTI2023

Hypervelocity impact in stellar media: heat shielding, shock fronts and ablation clouds

The Frontier Plasma Science experiments proposed by our team will model the processes occurring during spacecraft atmospheric entries and meteorite planetary collisions by inserting material targets into the Scrape off Layer (SOL) and edge plasma of a tokamak. This project will investigate important plasma-material processes during high-enthalpy atmospheric entries, including heat flux generation and material ablation. Of particular interest is to explore heat and particle flux detachment in front of the sample using concepts and techniques developed in the latest studies of divertor detachment. Exploration missions to the Solar System’s gaseous giants and hyperbolic re-entries into the Earth’s atmosphere require spacecraft that can withstand high velocity (>10 km/s), high heat fluxes (>10 MW/m2), and corresponding enthalpies. Ablative materials have been used as thermal shields to protect the spacecraft from severe heating during entry. However, developing high enthalpy ablating materials is challenging due to the lack of adequate ground testing facilities. Our team stated that the performance of candidate shielding materials could be assessed in a laboratory environment with multiple in-situ diagnostics, which was enabled by the progress in the tokamak research. Modern machines feature relatively long discharges (~10 s) with well-controlled stable plasma conditions at the edge where the heat flux and the flow speed are similar to those experienced during atmospheric entries. The experiments were carried out at the DIII-D National Fusion Facility in San Diego, CA, operated by General Atomics (GA) for the DoE.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Site‐Specific Reduction‐Induced Hydrogenation of a Helical Bilayer Nanographene with K and Rb Metals: Electron Multiaddition and Selective Rb + Complexation

Abstract The chemical reduction of π‐conjugated bilayer nanographene 1 (C 138 H 120 ) with K and Rb in the presence of 18‐crown‐6 affords [K + (18‐crown‐6)(THF) 2 ][{K + (18‐crown‐6)} 2 (THF) 0.5 ][C 138 H 122 3− ] ( 2 ) and [Rb + (18‐crown‐6) 2 ][{Rb + (18‐crown‐6)} 2 (C 138 H 122 3− )] ( 3 ). Whereas K + cations are fully solvent‐separated from the trianionic core thus affording a “naked” 1 .3 − anion, Rb + cations are coordinated to the negatively charged layers of 1 .3 − . According to DFT calculations, the localization of the first two electrons in the helicene moiety leads to an unprecedented site‐specific hydrogenation process at the carbon atoms located on the edge of the helicene backbone. This uncommon reduction‐induced site‐specific hydrogenation provokes dramatic changes in the (electronic) structure of 1 as the helicene backbone becomes more compressed and twisted upon chemical reduction, which results in a clear slippage of the bilayers.

Zhou, Zheng↗
DOE OSTI2021

Site‐Specific Reduction‐Induced Hydrogenation of a Helical Bilayer Nanographene with K and Rb Metals: Electron Multiaddition and Selective Rb + Complexation

Abstract The chemical reduction of π‐conjugated bilayer nanographene 1 (C 138 H 120 ) with K and Rb in the presence of 18‐crown‐6 affords [K + (18‐crown‐6)(THF) 2 ][{K + (18‐crown‐6)} 2 (THF) 0.5 ][C 138 H 122 3− ] ( 2 ) and [Rb + (18‐crown‐6) 2 ][{Rb + (18‐crown‐6)} 2 (C 138 H 122 3− )] ( 3 ). Whereas K + cations are fully solvent‐separated from the trianionic core thus affording a “naked” 1 .3 − anion, Rb + cations are coordinated to the negatively charged layers of 1 .3 − . According to DFT calculations, the localization of the first two electrons in the helicene moiety leads to an unprecedented site‐specific hydrogenation process at the carbon atoms located on the edge of the helicene backbone. This uncommon reduction‐induced site‐specific hydrogenation provokes dramatic changes in the (electronic) structure of 1 as the helicene backbone becomes more compressed and twisted upon chemical reduction, which results in a clear slippage of the bilayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Discrete Green’s functions and spectral graph theory for computationally efficient thermal modeling

Here, this work concerns solutions of the heat equation with the spectral graph method, for which the temperature is defined at discrete points in the domain and the spatial relationship among the points is described by a graph. The heat equation on the graph is solved using matrix techniques involving the eigenvectors and eigenvalues of the Laplacian matrix. The spectral graph approach precludes the computationally intensive meshing and numerous time-integration steps of the finite element method. In the present work, the spectral graph method is extended to include heat loss at the boundaries with a generalized boundary condition, and physics-based edge weights are introduced which simplify the calibration process. From this approach a discrete Green’s function is defined which allows for solutions under a variety of heating conditions including: space-varying initial conditions; time-and-space varying internal heating; and, time-and-space-varying heating at boundaries of type 1 (Dirichlet), type 2 (Neumann) and type 3 (Robin). Results are provided for benchmark heat transfer problems in one spatial dimension and in three spatial dimensions, and verification is provided by comparison with exact analytical solutions and finite difference solutions. The spectral graph method converges within 0.4% error of the analytical solution. The practical utility of the approach is demonstrated by thermal simulation of a multilayer additive manufacturing process. The spectral graph results are compared to experimentally-obtained temperature data for two metal parts, with error less than 5% of the experimental measurements, with computation time less than one minute on a desktop computer.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Deciphering the Dynamic Molecular Program of Radiation-Induced Endothelial Senescence

Radiation-induced cellular senescence is a double-edged sword, acting as both a tumor suppression process limiting tumor proliferation, and a crucial process contributing to normal tissue injury. Endothelial cells play a role in normal tissue injury after radiation therapy. Recently, a study observed an accumulation of senescent endothelial cells (ECs) around radiation-induced lung focal lesions following stereotactic radiation injury in mice. However, the effect of radiation on EC senescence remains unclear because it depends on dose and fractionation, and because the senescent phenotype is heterogeneous and dynamic.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Neural network representation of electronic structure from ab initio molecular dynamics

Despite their rich information content, electronic structure data amassed at high volumes in ab initio molecular dynamics simulations are generally under-utilized. Here we introduce a transferable high-fidelity neural network representation of such data in the form of tight-binding Hamiltonians for crystalline materials. This predictive representation of ab initio electronic structure, combined with machine-learning boosted molecular dynamics, enables efficient and accurate electronic evolution and sampling. When it is applied to a one-dimension charge-density wave material, carbyne, we are able to compute the spectral function and optical conductivity in the canonical ensemble. The spectral functions evaluated during soliton-antisoliton pair annihilation process reveal significant renormalization of low-energy edge modes due to retarded electron-lattice coupling beyond the Born–Oppenheimer limit. The availability of an efficient and reusable surrogate model for the electronic structure dynamical system will enable calculating many interesting physical properties, paving the way to previously inaccessible or challenging avenues in materials modeling.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Shining a Light on Some Fundamental Research Opportunities in Semiconductor Photoelectrochemistry

Decades of research in semiconductor photoelectrochemistry have yielded a deep understanding of charge transfer, energetics, and stability at solid−liquid interfaces. Theoretical frameworks developed by Gerischer and contemporaries, together with extensive experimental validation, have clarified the key principles affecting the interfacial kinetics and energetics of semiconductor photoelectrodes. Nevertheless, significant opportunities remain for advances in fundamental understanding of semiconductor photoelectrochemistry. Exciting opportunities include exploiting advances in theory, synthesis, and instrumentation to determine the chemical identity and reactivity of surface states; exerting control of band-edge energetics through molecular-level surface modification processes; and systematically improving emerging photoelectrode protection strategies to enable long-term photoelectrode operation under both oxidative and reductive conditions. Advanced morphologies, such as nanowire and microwire arrays, present new pathways to combine efficient light absorption with effective charge collection and catalyst integration. Unique light−matter interactions during photoelectrochemical deposition of p-type semiconductors readily allow preparation at scale of complex 3D morphologies that are difficult, if not impossible, to access by other methods. Continued exploration of these avenues will expand the fundamental understanding of semiconductor−liquid interfaces and could additionally advance the realization of efficient, stable, and scalable systems for solar fuel generation and other emerging photoelectrochemical applications.

Bean, Paul J. L. [California Institute of Technolo↗
DOE OSTI2023

Efficient QAOA Optimization using Directed Restarts and Graph Lookup

Variational Quantum Algorithms (VQA) aim to enhance the capabilities of Noisy Intermediate-Scale Quantum (NISQ) devices. These algorithms utilize parameterized circuits and classical optimizers to iteratively execute circuits with varying parameters. However, VQA faces computational overheads due to repeated iterations and random restarts. Prior work suggests using basic sub-graphs to transfer parameters for the input graph, reducing optimizer overheads but limiting applicability to structured regular graphs. In real-world applications, random irregular graphs are common, and existing methods are not scalable or practical for such graphs. This paper presents a framework that aims to improve random irregular graphs in VQA. The framework uses graph similarity and important features like total edge counts, average edge counts, and variance. It follows an iterative process to choose basis sub-graphs from a small database and adjust parameters accordingly. Classical optimizers then utilize these parameters to determine when to restart and perform gradient descent. This approach increases the chances of reaching global maximum points.

Wang, Meng↗
DOE OSTI2022

Guide to the Distributed Energy Resource Risk Management Framework

The emergence of distributed energy resources (DERs) has transformed the electric power sector and will likely have even more profound impacts on the future evolution of the United States energy sector as it modernizes and becomes more reliant upon complex informatics programming and systems to ensure that our power grid remains safe from malicious interference. To mitigate risks associated with the increased and diversified use of DERs, the Distributed Energy Resource Cybersecurity Framework (DER-CF) was developed in 2019. The National Renewable Energy Laboratory extended the scope of the DER-CF to include the RMF. To address the challenges faced by federal energy managers and energy system stakeholders in applying the RMF to DER systems, the Distributed Energy Resource Risk Manager (DER-RM) is a six-step process to proactively manage cybersecurity risk in a methodical manner. The DER-RM is independent of the DER-CF's existing assessment, allowing users to focus specifically on the RMF steps. The tools are targeted to different processes - DER-CF enables organizations to perform self-assessments to improve their cybersecurity posture, while DER-RM assists organizations in achieving compliance with specific requirements. This document provides an overview of the DER-RM. The RMF process outlined in this report serves as a guide to diagnose information and operational system threats, gather required materials to comply with industry standards, and document plans for achieving Authority to Operate. Using the DER-RM, federal agencies and other organizations can easily and intuitively follow the RMF process, manage the risks to their grid-edge infrastructure through the integration of their on-site DERs, and comply with appropriate requirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

X-ray Spectroscopic Studies of a Solid-Density Germanium Plasma Created by a Free Electron Laser

The generation of solid-density plasmas in a controlled manner using an X-ray free electron laser (XFEL) has opened up the possibility of diagnosing the atomic properties of hot, strongly coupled systems in novel ways. Previous work has concentrated on K-shell emission spectroscopy of low Z (<= 14) elements. Here, we extend these studies to the mid-Z(=32) element Germanium, where the XFEL creates copious L-shell holes, and the plasma conditions are interrogated by recording of the associated L-shell X-ray emission spectra. Given the desirability of generating as uniform a plasma as possible, we present here a study of the effects of the FEL photon energy on the temperatures and electron densities created, and their uniformity in the FEL beam propagation direction. We show that good uniformity can be achieved by tuning the photon energy of the XFEL such that it does not overlap significantly with L-shell to M-shell bound-bound transitions, and lies below the L-edges of the ions formed during the heating process. Reasonable agreement between experiment and simulations is found for the emitted X-ray spectra, demonstrating that for these higher Z elements, the selection of appropriate XFEL parameters is important for achieving uniformity in the plasma conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗