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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reversible and Irreversible Layer Edge Relaxation in Laser–Radiation–Hardened 2D Organic–Inorganic Perovskite Crystals

The layer edge states or low energy state (LES) in 2D hybrid organic–inorganic perovskites demonstrate a prolonged carrier lifetime for better performance of optoelectronic devices. However, the fundamental understanding of LES in 2D perovskites is still inconclusive. Herein, a photoluminescence (PL) study of LES in 2D Ruddlesden–Popper perovskites is presented with n = 2 and n = 3 from their cleaved cross sections that are more stable than the natural edge. The PL measurements clearly observe reversible, and irreversible surface relaxations (case I and case II) in three laser intensity ranges, further supported by a PL excitation cycle from low to high laser intensity, and vice versa. The PL wavelength of LES is tunable with laser intensity and blueshifts with increasing laser intensity during irreversible surface relaxation process (case I). Fluorescence lifetime imaging (FLIM) shows that the LES has a longer lifetime than the band-edge emission in the sample without a photodegradation, while the BE lifetime becomes relatively longer in the area with a photodegradation. Furthermore, the presented laser tunable LES and the related irreversible relaxation process provide a new insight that can help improve the photostability in 2D perovskites and understand roles of LESs in optoelectronic device performance.

2D organic-inorganic perovskite↗
DOE OSTI2022

Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches

Abstract Wind power production is driven by, and varies with, the stochastic yet uncontrollable wind and environmental inputs. To compare a wind turbine's performance, a direct comparison on power outputs is always confounded by the stochastic effect of weather inputs. It is therefore crucial to control for the weather and environmental influence. Toward that objective, our study proposes an energy decomposition approach. We start with comparing the change in the total energy production and refer to the change in total energy as delta energy. On this delta energy, we apply our decomposition method, which is to separate the portion of energy change due to weather effects from that due to the turbine itself. We derive a set of mathematical relationships allowing us to perform this decomposition and examine the credibility and robustness of the proposed decomposition approach through extensive cross‐validation and case studies. We then apply the decomposition approach to Supervisory Control and Data Acquisition data associated with several wind turbines to which leading‐edge protection was carried out. Our study shows that the leading‐edge protection applied on blades may cause a small decline to the power production efficiency in the short term, although we expect the leading‐edge protection to benefit the blade's reliability in the long term.

17 WIND ENERGY↗
DOE OSTI2020

Edge-cloud computing performance benchmarking for IoT based machinery vibration monitoring

Advances in low cost and reliable sensing, connectivity (Internet of Things), computational power, and advanced analytics, are leading to a new wave of innovation in machinery status sensing and condition monitoring. Significant research efforts are directed towards cloud computing architectures. However, given the latency, bandwidth, cost, security, and privacy concerns, further supported by the ever-increasing capabilities of edge computing devices, there is a need to consider both edge and cloud computing together to make informed decisions based upon context and performance. In this work, we present an edge-cloud performance evaluation for IoT based machinery vibration monitoring, to foster deployment for the contexts considered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A Roadmap for Edge Computing Enabled Automated Multidimensional Transmission Electron Microscopy

The advent of modern, high-speed electron detectors has made the collection of multidimensional hyperspectral transmission electron microscopy datasets, such as 4D-STEM, a routine. However, many microscopists find such experiments daunting since analysis, collection, long-term storage, and networking of such datasets remain challenging. Some common issues are their large and unwieldy size that often are several gigabytes, non-standardized data analysis routines, and a lack of clarity about the computing and network resources needed to utilize the electron microscope. The existing computing and networking bottlenecks introduce significant penalties in each step of these experiments, and thus, real-time analysis-driven automated experimentation for multidimensional TEM is challenging. One solution is to integrate microscopy with edge computing, where moderately powerful computational hardware performs the preliminary analysis before handing off the heavier computation to high-performance computing (HPC) systems. In this work, we trace the roots of computation in modern electron microscopy, demonstrate deep learning experiments running on an edge system, and discuss the networking requirements for tying together microscopes, edge computers, and HPC systems.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Elucidating Anomalous Intensity Ratios in Chlorine L-Edge X-ray Absorption Spectroscopy: Multiplet Effects and Core Rydberg Transitions

A relativistic core–valence-separated equation-of-motion coupled cluster (CVS-EOM-CC) study of chlorine L 2,3 -edge X-ray absorption near-edge structure (XANES) spectra using CH 3 Cl and CH 2 ICl as representative molecules is reported. The nearly identical intensity for the main features in the L 2 - and L 3 -edge XANES spectra is attributed to multiplet effects and the overlap between core–valence and core Rydberg transitions. The multiplet effects originating from the interaction between the core hole and the C–Cl σ* orbitals account for around half of the deviation of the L 3 and L 2 intensity ratio from the 2:1 ratio of the numbers of 2p 3/2 and 2p 1/2 electrons. The 2p 3/2 → 4s core Rydberg transitions are shown to overlap with the 2p 1/2 → σ* transitions and contribute to the other half of the intensity anomaly. Here, we demonstrate that triple excitations in CVS-EOM-CC calculations play important roles in accurate simulation of the overlap between the 2p 1/2 → σ* and 2p 3/2 → 4s transitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

One-Dimensional Edge Transport in Few-Layer WTe 2

WTe 2 is a layered transitional-metal dichalcogenide (TMD) with a number of intriguing topological properties. Recently, WTe 2 has been predicted to be a higher-order topological insulator (HOTI) with topologically protected hinge states along the edges. The gapless nature of WTe 2 complicates the observation of one-dimensional (1D) topological states in transport due to their small contribution relative to the bulk. Here, we study the behavior of the Josephson effect in magnetic field to distinguish edge from bulk transport. The Josephson effect in few-layer WTe 2 reveals 1D states residing on the edges and steps. Moreover, our data demonstrates a combination of Josephson transport properties observed solely in another HOTI—bismuth, including Josephson transport over micrometer distances, extreme robustness in a magnetic field, and nonsinusoidal current-phase relation (CPR). Our observations strongly suggest the topological origin of the 1D states and that few-layer WTe 2 is a HOTI.

1D edge states↗
DOE OSTI2020

Band-edge Engineering to Eliminate Radiation-Induced Defect States in Perovskite Scintillators

Under radiative environments such as extended hard X- or γ-rays, degradation of scintillation performance is often due to irradiation-induced defects. To overcome the effect of deleterious defects, novel design mitigation strategies are needed to identify and design more resilient materials. The potential for band-edge engineering to eliminate the effect of radiation-induced defect states in rare-earth-doped perovskite scintillators is explored, taking Ce 3+ -doped LuAlO 3 as a model material system, using density functional theory (DFT)-based DFT + U and hybrid Heyd–Scuseria–Ernzerhof (HSE) calculations. Furthermore, from spin-polarized hybrid HSE calculations, the Ce 3+ activator ground-state 4f position is determined to be 2.81 eV above the valence band maximum in LuAlO 3 . Except for the oxygen vacancies which have a deep level inside the band gap, all other radiation-induced defects in LuAlO 3 have shallow defect states or are outside the band gap, that is, relatively far away from either the 5d 1 or the 4f Ce 3+ levels. Finally, we examine the role of Ga doping at the Al site and found that LuGaO 3 has a band gap that is more than 2 eV smaller than that of LuAlO 3 . Specifically, the lowered conduction band edge envelopes the defect gap states, eliminating their potential impact on scintillation performance and providing direct theoretical evidence for how band-edge engineering could be applied to rare-earth-doped perovskite scintillators.

36 MATERIALS SCIENCE↗
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 OSTI2024

Edge treatment for spurious mode suppression in thin-film lithium niobate resonators

Abstract Thin-film lithium niobate is an attractive material for RF acoustic devices because of its high electromechanical coupling. However, due to the large coupling and the high anisotropy, thin-film lithium niobate resonators are prone to accidental resonances called spurious modes. These modes compromise the frequency response of the resonators, limiting their use in filter and oscillator applications. In this work, we present a novel method of spurious mode suppression through a special edge treatment etch process. Two thin-film lithium niobate resonators were fabricated, one with smooth sidewalls and one with the edge treatment. It was found that the edge-treated resonators show a weaker spurious mode response. This is potentially a new way to mitigate spurious resonances, a major issue in lithium niobate Lamb wave devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Light-powered end-to-end neutron detection and imaging with an edge-deployed optical AI chip

Neutron detection is widely used in many applications including nuclear physics, nuclear energy, nuclear technologies and nuclear safeguards. Developing an end-to-end neutron detection and imaging workflow paves way towards fully automated processes for many applications. We implemented an automated workflow for neutron detection experiments which use a solid state image sensor to capture neutron hits as a digital image. We deploy the workflow to an edge-based optical neural network (ONN) to increase the radiation-hardness and lifetime of neutron detection instruments. We present a two-stage neural network framework for detection of neutrons at sub-pixel resolution. The first stage uses a region proposal network to efficiently detect and extract neutron hits from the input camera image. The second stage feeds the extracted hits into a fully connected neural network to predict the sub-pixel hit position. The performance of the two-stage framework is evaluated using the edge-based ONN. The results show that we can achieve above 96% neutron detection accuracy as well as sub-pixel and sub-micron position resolution, while enjoying the advantages of the ONN hardware including radiation-hardness, low energy consumption and high computing speed for integrated edge camera and hardware deployment, when compared with electronic counterparts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Plasma performance and operational space with an RMP-ELM suppressed edge

Abstract The operational space and global performance of plasmas with edge-localized modes (ELMs) suppressed by resonant magnetic perturbations (RMPs) are surveyed by comparing AUG, DIII-D, EAST, and KSTAR stationary operating points. RMP-ELM suppression is achieved over a range of plasma currents, toroidal fields, and RMP toroidal mode numbers. Consistent operational windows in edge safety factor are found across devices, while windows in plasma shaping parameters are distinct. Accessed pedestal parameters reveal a quantitatively similar pedestal-top density limit for RMP-ELM suppression in all devices of just over 3 × 10 19 m −3 . This is surprising given the wide variance of many engineering parameters and edge collisionalities, and poses a challenge to extrapolation of the regime. Wide ranges in input power, confinement time, and stored energy are observed, with the achieved triple product found to scale like the product of current, field, and radius. Observed energy confinement scaling with engineering parameters for RMP-ELM suppressed plasmas are presented and compared with expectations from established H and L-mode scalings, including treatment of uncertainty analysis. Different scaling exponents for individual engineering parameters are found as compared to the established scalings. However, extrapolation to next-step tokamaks ITER and SPARC find overall consistency within uncertainties with the established scalings, finding no obvious performance penalty when extrapolating from the assembled multi-device RMP-ELM suppressed database. Overall this work identifies common physics for RMP-ELM suppression and highlights the need to pursue this no-ELM regime at higher magnetic field and different plasma physical size.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Distributed Aerodynamic Control using Active Trailing-Edge Flaps for Large Wind Turbines

This work presents a numerical framework to investigate distributed aerodynamic control devices for application in large wind turbines. Tool capabilities were extended to facilitate multiple aerodynamic polar tables. The airfoil aerodynamics characteristics were automatically determined, and blade-pitch, generator-torque, and trailing-edge-flap controllers were tuned in-the-loop according to a specific blade design. This automated workflow allows analysis and optimization of trailing-edge flaps, enabling codesign studies. Results targeted reductions of root-flap-bending moment derivatives. The applied trailing-edge-flap control reduced the standard deviation of root-flap-bending moments by more than 6% and benefit related parameters, e.g., reduce blade-tip deflections, by up to 8%. Because of varying thrust distributions along the blade span, different flap designs have nonlinear characteristics in terms of the control objective and show best performance when located at the radial position with maximum thrust. In general, larger flaps provide a greater influence to reduce the target control objective.

17 WIND ENERGY↗
DOE OSTI2023

Kondo interaction of quantum spin Hall edge channels with charge puddles

Under time-reversal symmetry, quantum spin Hall edge channels are protected against elastic backscattering. However, even for samples which exhibit conductance quantization due to the quantum spin Hall effect, reproducible fluctuations shape the quantization plateau when the chemical potential is tuned through the bulk gap. Here, we examine those fluctuations in micron-sized HgTe quantum well devices. By performing temperature- and gate-dependent measurements, we conclude that “charge puddles” in the narrow-gap material have a Kondo-type interaction with the edge channels resulting in the observed conductance fluctuations. Our results provide insight into the underlying mechanisms of scattering in quantum spin Hall edge channels.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Magnetic edge fields in UTe 2 near zero background fields

Chiral superconductors are theorized to exhibit spontaneous edge currents. Here, in this study, we found magnetic fields at the edges of UTe 2 , a candidate odd-parity chiral superconductor, that seem to agree with predictions for a chiral order parameter. However, we did not detect the chiral domains that would be expected, and recent polar Kerr and muon spin relaxation data in nominally clean samples argue against chiral superconductivity. Our results show that hidden sources of magnetism must be carefully ruled out when using spontaneous edge currents to identify chiral superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Low-energy edge signatures of the Kitaev spin liquid

Recent experimental work indicates that the Kitaev spin liquid may be realizable close to zero magnetic field in exfoliated 𝛼−RuCl 3 flakes, thus providing a more versatile setting for studying non-Abelian anyons. Here, we propose a robust nanoscale signature of the Kitaev spin liquid that results from its edge states and manifests in the low-energy spin dynamics. In particular, we highlight a singular peak in the dynamical spin structure factor of a zigzag edge whose energy scales linearly with only one component of the magnetic field. This sharp feature in the local spin dynamics directly reflects the bond-directional Kitaev spin interactions and, more generally, the projective symmetries of the Kitaev spin liquid. In conclusion, we demonstrate that our proposed signature survives in the presence of edge disorder as well as non-Kitaev interactions, and provide detailed guidelines for experimentally observing it using inelastic electron tunneling spectroscopy and color-center relaxometry.

Color centers↗
DOE OSTI2021

Oxygen K -edge X-ray absorption spectra of liquids with minimization of window contamination

We report oxygen K-edge X-ray absorption spectroscopy is used routinely to study a range of solid materials. However, liquid samples are studied less frequently at the oxygen K-edge due to the combined challenges of high-vacuum conditions and oxygen contamination of window materials. A modular sample holder design with a twist-seal sample containment system that provides a simple method to encapsulate liquid samples under high-vacuum conditions is presented. This work shows that pure silicon nitride windows have lower oxygen contamination than both diamond- and silicon-rich nitride windows, that the levels of oxygen contamination are related to the age of the windows, and provides a protocol for minimizing the background oxygen contamination. Acid-washed 100 nm-thick silicon nitride windows were found to give good quality oxygen K-edge data on dilute liquid samples.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Deep Reinforcement Learning-Based Edge Caching in Wireless Networks

With the purpose to offload data traffic in wireless networks, content caching techniques have recently been studied intensively. Using these techniques and caching a portion of the popular files at the local content servers, the users can be served with less delay. Most of the content replacement policies are based on the content popularity, that depends on the users' preferences. In practice, such information varies over time. Therefore, an approach to determine the file popularity patterns must be incorporated into caching policies. In this context, we study content caching at the wireless network edge using a deep reinforcement learning framework with Wolpertinger architecture. In particular, we propose deep actor-critic reinforcement learning based policies for both centralized and decentralized content caching. For centralized edge caching, we aim at maximizing the cache hit rate. In decentralized edge caching, we consider both the cache hit rate and transmission delay as performance metrics. These proposed frameworks are assumed to neither have any prior information on the file popularities nor know the potential variations in such information. Via simulation results, the superiority of the proposed frameworks is verified by comparing them with other policies, including least frequently used (LFU), least recently used (LRU), and first-in-first-out (FIFO) policies.

42 ENGINEERING↗
DOE OSTI2023

A Mobile Edge Computing Framework for Traffic Optimization At Urban Intersections Through Cyber-Physical Integration

The stop-and-go traffic pattern on urban roads often results in excessive energy consumption because of unnecessary vehicle braking, idling, and accelerations. With the widespread and increased use of automobiles, this traffic pattern creates many negative impacts (e.g., delayed travel time, air pollution, and additional carbon emission) on the sustainability of our cities. Taking advantage of the recent emerging Internet of Things (IoT) and edge computing paradigms, we propose a mobile edge computing framework that integrates the capability of real-time vehicle-to-infrastructure communication and intelligent speed optimization algorithms into a mobile app to optimize individual vehicles' driving speed at signalized intersections. The optimization aims to mitigate the stop-and-go traffic pattern and its undesirable consequences in urban transportation systems. The framework consists of (1) a cyberinfrastructure-enabled dynamic messaging system for retrieving and delivering real-time traffic and signal phase and timing information from IoT-connected signal controllers and sensors, (2) a real-time speed optimization algorithm for generating intelligent speed advisory using vehicle's information (e.g., GPS and driving directions from mobile sensing) and corresponding signal and traffic information, and (3) an ad-hoc mobile computing environment that converts drivers' smartphones into edge devices to host the speed optimization algorithms for enabling intelligent advisory on the vehicle's driving speed within signalized corridors. The paper presents the design and implementation of the proposed framework. Finally, we demonstrate the feasibility, usefulness, and energy-saving benefits of our proposed framework and its prototyping mobile app on urban transportation systems through traffic simulation, real-vehicle laboratory experiments, an evaluative survey, and field communication tests. The simulation-based energy evaluation results show that the 100% usage of the mobile app can achieve 24% energy savings in the transportation system.

33 ADVANCED PROPULSION SYSTEMS↗