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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Defects in C d 3 A s 2 epilayers via molecular beam epitaxy and strategies for reducing them

Molecular beam epitaxy offers an exciting avenue for investigating the behavior of the topological semimetal Cd 3 As 2 , by providing routes for doping, alloying, strain engineering, and heterostructure formation. To date, however, minimal exploration has been devoted to the impact of defects that are incorporated into epilayers due to constraints imposed by the substrate and narrow growth window. Here, we use a combination of lattice-matched Zn x Cd 1-x Te buffer layers, miscut substrates, and broadband illumination to study how dislocations, twins, and point defects influence the electron mobility of Cd 3 As 2 . In conclusion, a combination of defect suppression approaches produces Cd 3 As 2 epilayers with electron mobilities upwards of 15000 cm 2 /Vs at room temperature.

14 SOLAR ENERGY↗
DOE OSTI2020

Evolution of ferroelastic domain walls during phase transitions in barium titanate nanoparticles

In this work, ferroelastic domain walls inside BaTiO 3 (BTO) tetragonal nanocrystals are distinguished by Bragg peak position and studied with Bragg coherent x-ray diffraction imaging (BCDI). Convergence-related features of the BCDI method for strongly phased objects are reported. A ferroelastic domain wall inside a BTO crystal has been tracked and imaged across the tetragonal-cubic phase transition and proves to be reversible. The linear relationship of relative displacement between two twin domains with temperature is measured and shows a different slope for heating and cooling, while the tetragonality reproduces well over temperature changes in both directions. An edge dislocation is also observed and found to annihilate when heating the crystal close to the phase transition temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Effect of interfacial structures on phonon transport across atomically precise Si/Al heterojunctions

Phonons are important carriers of energy and information in many cryogenic devices used for quantum information science and in fundamental physics experiments such as dark matter detectors. In these systems phonon behavior can be dominated by interfaces, hence there is increasing demand for a more detailed understanding of interfacial phonon transport in relevant material systems. Previous studies have focused on understanding thermal transport over the entire phonon spectrum at and above room temperature. At ultra-low temperatures, however, knowledge is missing regarding athermal phonon behavior due to the challenge in modeling the extreme conditions in micro-scale, heterogeneous cryogenic systems, as well as extracting single-phonon information from a large ensemble. In this work, we delineate interfacial phonon transport using a combination of classical molecular dynamics (MD) and phonon wave packet simulations, to illustrate the consistency and differences between the ensemble- and single-phonon dynamics. We consider three single-crystal Si surface reconstructions --- (1×1), (v3×v3) and (7×7) --- and model both experimentally observed Si(1×1)/Al interfaces and hypothesized Si(v3×v3)/Al and Si(7×7)/Al interfaces. The overall interfacial thermal conductance calculated from non-equilibrium MD shows that for the Si(1×1)/Al system, the presence of Al twin grain boundaries can hinder phonon transport and reduce thermal conductance by 2--12% relative to single-crystal Al; whereas the Si (v3×v3) and (7×7) reconstructions can enhance it by 6--19%. Normal mode decomposition reveals that both the increase and decrease in conductance are related to inelastic phonon scattering. Single-phonon wave packet simulations show results consistent with NEMD, while further suggesting that phonon polarization conversion is significant even when elastic transmission dominates, and that the interfacial structures have anisotropic impacts on atomic vibrations along different lattice directions. Our findings suggest alternative perspectives in achieving selective phonon transport through controlling interfacial structures of materials with atomically-precise fabrication techniques, and that the phonon wave packet formalism is a potentially powerful method for developing a detailed understanding of non-equilibrium phenomena in the low-temperature limit.

Lu, Zexi↗
DOE OSTI2022

Deformation behavior of crystalline/amorphous Al-Si nanocomposites with nanolaminate or nanofibrous microstructures

Deformation mechanisms in sputter-deposited crystalline Al/amorphous Si nanocomposites with nanolaminate or nanofibrous morphology are characterized by nanoindentation, micropillar compression testing and transmission electron microscopy (TEM). The nanofibrous composite having crystalline Al nanofibers with ~40–50 nm in length and 15–20 nm in diameter embedded in amorphous Si exhibits strain hardening to a maximum flow stress of 2.9 GPa and no shear band (SB) formation in compression up to plastic strain exceeding 24%. On the other hand, nanolaminate composite that is composed of 80 nm crystalline Al layers and 20 nm amorphous Si layers exhibits catastrophic SBs starting at plastic strains in the range of 5–10%. Cross-sectional TEM of the deformed samples reveals a high density of stacking faults and twin boundaries in Al nanofibers and no microshear bands in the nanofibrous composite, suggesting plastic deformation in amorphous Si phase and crystalline Al nanofibers. Further, molecular dynamics simulations revealed that the plastic deformation in amorphous Si phase in the cosputtered films could be favored by the decrease in flow strength of amorphous Si with increasing Al solute concentration trapped in Si.

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

Quantum-enhanced distributed phase sensing with a truncated SU(1,1) interferometer

In recent years, distributed quantum sensing has gained interest for a range of applications requiring networks of sensors, from global-scale clock synchronization to high energy physics. In particular, a network of entangled sensors can improve not only the sensitivity beyond the shot noise limit, but also enable a Heisenberg scaling with the number of sensors. Here, using bright entangled twin beams, we theoretically and experimentally demonstrate the detection of a linear combination of two distributed phases beyond the shot noise limit with a truncated SU(1,1) interferometer. Specifically, we show a quantum noise reduction of 1.7 ± 0.3 dB below what is possible with the corresponding classical configuration. Additionally, we theoretically extend the use of a truncated SU(1,1) interferometer to a multi-phase-distributed sensing scheme that leverages entanglement as a resource to achieve a quantum improvement in the scaling with the number of sensors in the network. Our results pave the way for developing quantum-enhanced sensor networks that can achieve an entanglement-enhanced sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Quantum Frequency Combs with Path Identity for Quantum Remote Sensing

Quantum sensing promises to revolutionize sensing applications by employing quantum states of light or matter as sensing probes. Photons are the clear choice as quantum probes for remote sensing because they can travel to and interact with a distant target. Existing schemes are mainly based on the quantum illumination framework, which requires quantum memory to store a single photon of an initially entangled pair until its twin reflects off a target and returns for final correlation measurements. Existing demonstrations are limited to tabletop experiments, and expanding the sensing range faces various roadblocks, including long-time quantum storage and photon loss and noise when transmitting quantum signals over long distances. We propose a novel quantum sensing framework that addresses these challenges using quantum frequency combs with path identity for remote sensing of signatures (“qCOMBPASS”). The combination of one key quantum phenomenon and two quantum resources—namely, quantum-induced coherence by path identity, quantum frequency combs, and two-mode squeezed light—allows for quantum remote sensing without requiring quantum memory. The proposed scheme is akin to a quantum radar based on entangled frequency-comb pairs that uses path identity to detect, range, or sense a remote target of interest by measuring pulses of one comb in the pair that never traveled to the target but that contains target information “teleported” by quantum-induced coherence by path identity from the other comb in the pair that traveled to the target but is not detected. We develop the basic qCOMBPASS theory, analyze the properties of the qCOMBPASS transceiver, and introduce the qCOMBPASS equation—a quantum analog of the well-known LIDAR equation in classical remote sensing. We also describe an experimental scheme to demonstrate the concept using two-mode squeezed quantum combs. qCOMBPASS can strongly impact various applications in remote quantum sensing, imaging, metrology, and communications. These applications include detection and ranging of low-reflectivity objects, measurement of small displacements of a remote target with precision beyond the standard quantum limit (SQL), standoff hyperspectral quantum imaging, discreet surveillance from space with low detection probability (detect without being detected), very-long-baseline interferometry, quantum Doppler sensing, quantum clock synchronization, and networks of distributed quantum sensors. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Novel Probes Project: Tests of gravity on astrophysical scales

The Novel Probes Project, an initiative to advance the field of astrophysical tests of the dark sector by creating a forum that connects observers and theorists, is introduced. This review focuses on tests of gravity and is intended to be of use primarily to observers, as well as theorists with an interest in the development of experimental tests. It is twinned with a separate upcoming review on dark matter self-interactions. The review focuses on astrophysical tests of gravity in the weak-field regime, ranging from stars to quasilinear cosmological scales. This regime is complementary to both strong-field tests of gravity and background and linear probes in cosmology. In particular, the nonlinear screening mechanisms that are an integral part of viable modified-gravity models lead to characteristic signatures, specifically on astrophysical scales. The potential of these probes is not limited by cosmic variance but comes with the challenge of building robust theoretical models of the nonlinear dynamics of stars, galaxies, and large-scale structure. The groundwork is laid for a thorough exploration of the weak-field, nonlinear regime, with an eye to using the current and next generation of observations for tests of gravity. The scene is set by showing how gravitational theories beyond general relativity are expected to behave, focusing primarily on screening mechanisms. Analytic and numerical techniques for exploring the relevant astrophysical regime are described, as are the pertinent observational signals. With these in hand a range of astrophysical tests of gravity are presented, and prospects for future measurements and theoretical developments are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Toward a fully coherent tender and hard X-ray free-electron laser via cascaded EEHG in fourth-generation synchrotron light sources

Free-electron-laser-based beamlines utilize fully coherent laser pulses with extremely narrow bandwidth allowing direct use of X-rays without monochromators. This could be very beneficial for all users of current and future fourth-generation diffraction-limited synchrotron light sources (DL-SLSs) who need narrowband full-coherence high-brightness X-ray pulses. Based on our previous finding, i.e. that separating the two stages of echo-enabled harmonic generation (EEHG) with a few extra bending-magnet sections provides an effective way to increase the momentum compaction of chicane 1, one can simultaneously achieve adequate prebunching at extremely high harmonics as well as keep the energy modulation to the ideal minimum. This could open the door for cascaded EEHG, toward fully coherent tender and hard X-ray wavelengths. Built on our compact design of a twin-pulse seeding electron beam with an adjustable delay and timing jitter at the level of a few femtoseconds, a cascaded EEHG can be implemented, which includes two EEHG beamlines, where the radiation pulse generated by the first beamline with harmonic $h$ 1 could be used as the input seed laser pulse to the second beamline with harmonic $h$ 2 . Hence, the second radiator could potentially reach very high harmonics [$h$ = $h$ 1 (20)$h$ 2 (25–100)] from 500 to 2000, corresponding to tender and hard X-ray wavelengths. It is demonstrated that the cascaded EEHG scheme is compatible with almost any current or planned fourth-generation DL-SLS, with significant benefits for space-limited storage rings in particular. The main advantage is that this scheme requires almost no change of the storage-ring lattice and is fully compatible with other beamlines. Current proposals for rings with much longer straight sections would add self-amplified spontaneous emission as another viable option for storage-ring-based free-electron lasers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

SpeckleNN: a unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature. Classifying SPI scattering patterns, or `speckles', to extract single-hits that are needed for real-time vetoing and three-dimensional reconstruction poses a challenge for high-data-rate facilities like the European XFEL and LCLS-II-HE. Here, we introduce SpeckleNN, a unified embedding model for real-time speckle pattern classification with limited labeled examples that can scale linearly with dataset size. Trained with twin neural networks, SpeckleNN maps speckle patterns to a unified embedding vector space, where similarity is measured by Euclidean distance. We highlight its few-shot classification capability on new never-seen samples and its robust performance despite having only tens of labels per classification category even in the presence of substantial missing detector areas. Without the need for excessive manual labeling or even a full detector image, our classification method offers a great solution for real-time high-throughput SPI experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The incommensurately modulated structures of low-temperature labradorite feldspars: a single-crystal X-ray and neutron diffraction study

Labradorite feldspars of the plagioclase solid solution series have been known for their complicated subsolidus phase relations and enigmatic incommensurately modulated structures. Characterized by the irrationally indexed e -reflections in the diffraction pattern, e -labradorite shows the largest variation in the incommensurate ordering states among the e -plagioclase structures. The strongly ordered low-temperature e -labradorite is one of the last missing pieces of the e -plagioclase puzzle. Nine plutonic and metamorphic labradorite feldspar samples from Canada, Ukraine, Minnesota (USA), Tanzania and Greenland with compositions ranging from An 52.5 to An 68 were studied with single-crystal X-ray diffraction. Two crystals from Labrador, Canada, and Duluth, MN, USA, with wide enough twin lamellae were analyzed with single-crystal neutron diffraction. The incommensurately modulated structures of e -plagioclase are refined for the first time with neutron diffraction data, which confirmed that the T—O distance modulation in the low-temperature e -plagioclase results from the Al–Si ordering in the framework. Detailed configurations of the M site are also observed in the structures refined from neutron diffraction data, which were not possible to see with X-ray diffraction data. The relation between the q -vectors and the mole% An composition is revealed for the entire compositional range of e -plagioclase, from An 25 to An 75 . The previously proposed two-trend relation depending on the cooling rate and phase transition path is confirmed. A new classification of e -plagioclase ( e α , e β and e γ ) is proposed based on the q -vector of the structure, which makes it an independent character from the presence/absence of density modulation. New parameters are proposed to quantify the ordering states of these complicated aperiodic structures of e -plagioclases, such as the difference between $\langle$T 1 o—O$\rangle$ and $\langle$T 1 m—O$\rangle$ at phase t = 0.2 or the normalized intensity of the (071\bar 1) reflection.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Crystal structures and comparisons of huntite aluminum borates RE Al 3 (BO 3 ) 4 ( RE = Tb, Dy and Ho)

Three huntite-type aluminoborates of stoichiometry RE Al 3 (BO 3 ) 4 ( RE = Tb, Dy and Ho), namely, terbium/dysprosium/holmium trialuminium tetrakis(borate), were synthesized by slow cooling within a K 2 Mo 3 O 10 flux with spontaneous crystallization. The crystal structures were determined using single-crystal X-ray diffraction (SC-XRD) data. The synthesized borates are isostructural to the huntite [CaMg 3 (CO 3 ) 4 ] structure and crystallized within the trigonal R 32 space group. The structural parameters were compared to literature data of other huntite RE Al 3 (BO 3 ) 4 crystals within the R 32 space group. All three borates fit well into the trends calculated from the literature data. The unit-cell parameters and volumes increase linearly with larger RE cations whereas the densities decrease. All of the crystals studied were refined as inversion twins.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Adaptive Generation of Training Data for ML Reduced Model Creation

Machine learning proxy models are often used to speed up or completely replace complex computational models. The greatly reduced and deterministic computational costs enable new use cases such as digital twin control systems and global optimization. The challenge of building these proxy models is generating the training data. A naive uniform sampling of the input space can result in a non-uniform sampling of the output space of a model. This can cause gaps in the training data coverage that can miss finer scale details resulting in poor accuracy. While larger and larger data sets could eventually fill in these gaps, the computational burden of full-scale simulation codes can make this prohibitive. In this paper, we present an adaptive data generation method that utilizes uncertainty estimation to identify regions where training data should be augmented. By targeting data generation to areas of need, representative data sets can be generated efficiently. The effectiveness of this method will be demonstrated on a simple one-dimensional function and a complex multidimensional physics model.

Cianciosa, Mark↗
DOE OSTI2022

Charaterization of Emerging Computing Architectures for Dynamic Simulation of Future Power Grids with Large-Scale Power Electronics

The increasing penetration of power electronics in power grids significantly raises the computing requirements in a real-time (and/or fast) simulation of the power grid. The real-time simulation is an enabler for evaluating controllers, protection systems, new equipment, and twinning. In this paper, emerging computing architectures such as tensor processing units (TPU), neural/neuromorphic processing units (NPU), and quantum processing units (QPU) are introduced and characterized for the real-time (and/or fast) simulation of power electronics-dominated power grids. The metrics and the process to characterize emerging computing architectures to perform real-time (and/or fast) simulations of future power grids with power electronics are discussed. Three of the emerging computing units are characterized based on these metrics and the process developed. This characterization will enable identification and comparison of emerging computing architectures that can perform real-time (and/or fast) simulation of future power grids.

Choi, Jongchan↗
DOE OSTI2022

Demand Driven Energy Management for PIPO Auxiliary Power Supply Architecture

In this paper, a demand driven energy management (DDEM) technique is implemented on modular parallel input parallel output DC/DC auxiliary power supply (APS) structure. In this method, modules are brought in/out of the operation making them operate under high loading conditions, avoiding low efficiency under light load. Such a method finds its application in power conservative systems with variable load. Implementation of DDEM and the energy saved is shown using APS comprised of two 15W commercially off-the-shelf DC-DC modules, with 100–1000 VDC input and 24 V output voltage. Along with the DDEM, the lifetime of the power stage devices is controlled minimizing their junction temperature swing through control of cooling system. This control method uses digital twin as interface to virtualize the power devices loading operation/ health condition. Accordingly, no extra sensor or closed loop control required to measure the junction temperature of the devices or feedback the losses to the cooling flow.

Azadeh, Yalda↗
DOE OSTI2022

Enabling Autonomous Electron Microscopy for Networked Computation and Steering

Advanced electron microscopy workflows require an ecosystem of microscope instruments and computing systems possibly located at different sites to conduct remotely steered and automated experiments. Current workflow executions involve manual operations for steering and measurement tasks, which are typically performed from control workstations co-located with microscopes; consequently, their operational tempo and effectiveness are limited. We propose an approach based on separate data and control channels for such an ecosystem of Scanning Transmission Electron Microscopes (STEM) and computing systems, for which no general solutions presently exist, unlike the neutron and light source instruments. We demonstrate automated measurement transfers and remote steering of Nion STEM physical instruments over site networks. We propose a Virtual Infrastructure Twin (VIT) of this ecosystem, which is used to develop and test our steering software modules without requiring access to the physical instrument infrastructure. Additionally, we develop a VIT for a multiple laboratory scenario, which illustrates the applicability of this approach to ecosystems connected over wide-area networks, for the development and testing of software modules and their later field deployment.

Al Najjar, Anees↗
DOE OSTI2025

Network Slicing for Federated Learning in Operational Technology Environment

Industrial Control Systems (ICS) and Supervisory Control and Data Acquisition (SCADA) environments are essential to modern infrastructure, facing challenges in ensuring low-latency, high-throughput communication while mitigating cyber threats. This paper presents a framework integrating Federated Learning (FL) and network slicing with Quality of Service (QoS) to enable real-time monitoring without disrupting OT operations. Leveraging digital twin technology and Network Function Virtualization (NFV), the architecture supports predictive analytics and Industry 4.0 requirements. FL facilitates decentralized model training, preserving data privacy and scalability, though it introduces potential throughput constraints. Network slicing addresses this by creating dedicated virtualized segments optimized for performance and security. Advanced fault tolerance at the container and instance levels enhances system reliability. The proposed architecture ensures high throughput, low latency, and secure orchestration for real-time anomaly detection in OT networks. Performance evaluations validate its efficiency in throughput, deployment, and learning accuracy, providing a robust foundation for future ICS automation and data-driven decision-making.

Delgado, Brian G. Rodiles [University of Texas at ↗
DOE OSTI2025

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗