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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Characterization of Aquifer Poroelastic Response to Impulse and Oscillatory Well Pressure Using Distributed Acoustic Sensing

Abstract The storage of fluids in the subsurface is critical for a broad spectrum of applications including managed aquifer recharge, storage of liquefied carbon dioxide and hydrogen, geothermal heat extraction and exploitation of hydrocarbon. It is surprising then, that there has been relatively little measurement of the vertical distribution of poroelastic storage in geologic formations as compared with permeability. We present experiments in which fluid was injected into an important regional aquifer and the depth‐dependent strain response measured using fiber optic distributed acoustic sensing. The formation expansion and contraction in response to fluid injection were several 100 nanostrain. Strain, and the implied storage distribution, was highly localized in specific strata and demonstrated complex, hydromechanical behavior. This new window into fluid‐geomechanical coupling undermines some typically use models and observations currently in practice, but provides potential for complete representation and prediction of fluid storage in the subsurface.

58 GEOSCIENCES↗
DOE OSTI2024

Noncontact excitation of multi-GHz lithium niobate electromechanical resonators

Abstract The demand for high-performance electromechanical resonators is ever-growing across diverse applications, ranging from sensing and time-keeping to advanced communication devices. Among the electromechanical materials being explored, thin-film lithium niobate stands out due to its strong piezoelectric properties and low acoustic loss. However, in nearly all existing lithium niobate electromechanical devices, the configuration is such that the electrodes are in direct contact with the mechanical resonator. This configuration introduces an undesirable mass-loading effect, producing spurious modes and additional damping. Here, we present an electromechanical platform that mitigates this challenge by leveraging a flip-chip bonding technique to separate the electrodes from the mechanical resonator. By offloading the electrodes from the resonator, our approach yields a substantial increase in the quality factor of these resonators, paving the way for enhanced performance and reliability for their device applications.

Instruments & Instrumentation↗
DOE OSTI2022

Tuning of oscillation modes by controlling dimensionality of spin structures

Abstract Harmonic oscillation of spin structures is a physical phenomenon that offers great potential for applications in nanotechnologies such as nano-oscillators and bio-inspired computing. The effective tuning of oscillations over wide frequency ranges within a single ferromagnetic nanoelement is a prerequisite to realize oscillation-based nanodevices, but it has not been addressed experimentally or theoretically. Here, utilizing a vortex core structure, one of spin structures, we report a drastic change of oscillation modes over the frequency range from MHz to sub-GHz in a 100 nm-thick permalloy circular disk. Oscillation mode was found to considerably depend on the shape and dimension of the vortex core structure and various oscillation modes over a wide range of frequencies appeared with dimensional change in the vortex core structure. This work demonstrates that oscillation modes of the vortex core structure can be effectively tuned and opens a way to apply spin structures to oscillation-based technology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Defect-mediated ripening of core-shell nanostructures

Abstract Understanding nanostructure ripening mechanisms is desirable for gaining insight on the growth and potential applications of nanoscale materials. However, the atomic pathways of nanostructure ripening in solution have rarely been observed directly. Here, we report defect-mediated ripening of Cd-CdCl 2 core-shell nanoparticles (CSN) revealed by in-situ atomic resolution imaging with liquid cell transmission electron microscopy. We find that ripening is initiated by dissolution of the nanoparticle with an incomplete CdCl 2 shell, and that the areas of the Cd core that are exposed to the solution are etched first. The growth of the other nanoparticles is achieved by generating crack defects in the shell, followed by ion diffusion through the cracks. Subsequent healing of crack defects leads to a highly crystalline CSN. The formation and annihilation of crack defects in the CdCl 2 shell, accompanied by disordering and crystallization of the shell structure, mediate the ripening of Cd-CdCl 2 CSN in the solution.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Topology stabilized fluctuations in a magnetic nodal semimetal

Abstract The interplay between magnetism and electronic band topology enriches topological phases and has promising applications. However, the role of topology in magnetic fluctuations has been elusive. Here, we report evidence for topology stabilized magnetism above the magnetic transition temperature in magnetic Weyl semimetal candidate CeAlGe. Electrical transport, thermal transport, resonant elastic X-ray scattering, and dilatometry consistently indicate the presence of locally correlated magnetism within a narrow temperature window well above the thermodynamic magnetic transition temperature. The wavevector of this short-range order is consistent with the nesting condition of topological Weyl nodes, suggesting that it arises from the interaction between magnetic fluctuations and the emergent Weyl fermions. Effective field theory shows that this topology stabilized order is wavevector dependent and can be stabilized when the interband Weyl fermion scattering is dominant. Our work highlights the role of electronic band topology in stabilizing magnetic order even in the classically disordered regime.

36 MATERIALS SCIENCE↗
DOE OSTI2024

All-optical phase conjugation using diffractive wavefront processing

Abstract Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with applications ranging from imaging to beam focusing. Here, we present a diffractive wavefront processor to approximate all-optical phase conjugation. Leveraging deep learning, a set of diffractive layers was optimized to all-optically process an arbitrary phase-aberrated input field, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated this wavefront processor by 3D-fabricating diffractive layers and performing OPC on phase distortions never seen during training. Employing terahertz radiation, our diffractive processor successfully performed OPC through a shallow volume that axially spans tens of wavelengths. We also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and multi-wavelength nature, this diffractive wavefront processor can be used for various applications, e.g., turbidity suppression and aberration correction across different spectral bands.

42 ENGINEERING↗
DOE OSTI2024

Mechanochemically responsive polymer enables shockwave visualization

Abstract Understanding the physical and chemical response of materials to impulsive deformation is crucial for applications ranging from soft robotic locomotion to space exploration to seismology. However, investigating material properties at extreme strain rates remains challenging due to temporal and spatial resolution limitations. Combining high-strain-rate testing with mechanochemistry encodes the molecular-level deformation within the material itself, thus enabling the direct quantification of the material response. Here, we demonstrate a mechanophore-functionalized block copolymer that self-reports energy dissipation mechanisms, such as bond rupture and acoustic wave dissipation, in response to high-strain-rate impacts. A microprojectile accelerated towards the polymer permanently deforms the material at a shallow depth. At intersonic velocities, the polymer reports significant subsurface energy absorption due to shockwave attenuation, a mechanism traditionally considered negligible compared to plasticity and not well explored in polymers. The acoustic wave velocity of the material is directly recovered from the mechanochemically-activated subsurface volume recorded in the material, which is validated by simulations, theory, and acoustic measurements. This integration of mechanochemistry with microballistic testing enables characterization of high-strain-rate mechanical properties and elucidates important insights applicable to nanomaterials, particle-reinforced composites, and biocompatible polymers.

Science & Technology - Other Topics↗
DOE OSTI2020

The role of faceting and elongation on the magnetic anisotropy of magnetite Fe3O4 nanocrystals

Abstract Fe 3 O 4 nanoparticles are one of the most promising candidates for biomedical applications such as magnetic hyperthermia and theranostics due to their bio-compatibility, structural stability and good magnetic properties. However, much is unknown about the nanoscale origins of the observed magnetic properties of particles due to the dominance of surface and finite size effects. Here we have developed an atomistic spin model of elongated magnetite nanocrystals to specifically address the role of faceting and elongation on the magnetic shape anisotropy. We find that for faceted particles simple analytical formulae overestimate the magnetic shape anisotropy and that the underlying cubic anisotropy makes a significant contribution to the energy barrier for moderately elongated particles. Our results enable a better estimation of the effective magnetic anisotropy of highly crystalline magnetite nanoparticles and is a step towards quantitative prediction of the heating effects of magnetic nanoparticles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Long lifetime of bialkali photocathodes operating in high gradient superconducting radio frequency gun

Abstract High brightness, high charge electron beams are critical for a number of advanced accelerator applications. The initial emittance of the electron beam, which is determined by the mean transverse energy (MTE) and laser spot size, is one of the most important parameters determining the beam quality. The bialkali photocathodes illuminated by a visible laser have the advantages of high quantum efficiency (QE) and low MTE. Furthermore, Superconducting Radio Frequency (SRF) guns can operate in the continuous wave (CW) mode at high accelerating gradients, e.g. with significant reduction of the laser spot size at the photocathode. Combining the bialkali photocathode with the SRF gun enables generation of high charge, high brightness, and possibly high average current electron beams. However, integrating the high QE semiconductor photocathode into the SRF guns has been challenging. In this article, we report on the development of bialkali photocathodes for successful operation in the SRF gun with months-long lifetime while delivering CW beams with nano-coulomb charge per bunch. This achievement opens a new era for high charge, high brightness CW electron beams.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems

Abstract A central challenge in the computational modeling and simulation of a multitude of science applications is to achieve robust and accurate closures for their coarse-grained representations due to underlying highly nonlinear multiscale interactions. These closure models are common in many nonlinear spatiotemporal systems to account for losses due to reduced order representations, including many transport phenomena in fluids. Previous data-driven closure modeling efforts have mostly focused on supervised learning approaches using high fidelity simulation data. On the other hand, reinforcement learning (RL) is a powerful yet relatively uncharted method in spatiotemporally extended systems. In this study, we put forth a modular dynamic closure modeling and discovery framework to stabilize the Galerkin projection based reduced order models that may arise in many nonlinear spatiotemporal dynamical systems with quadratic nonlinearity. However, a key element in creating a robust RL agent is to introduce a feasible reward function, which can be constituted of any difference metrics between the RL model and high fidelity simulation data. First, we introduce a multi-modal RL to discover mode-dependant closure policies that utilize the high fidelity data in rewarding our RL agent. We then formulate a variational multiscale RL (VMRL) approach to discover closure models without requiring access to the high fidelity data in designing the reward function. Specifically, our chief innovation is to leverage variational multiscale formalism to quantify the difference between modal interactions in Galerkin systems. Our results in simulating the viscous Burgers equation indicate that the proposed VMRL method leads to robust and accurate closure parameterizations, and it may potentially be used to discover scale-aware closure models for complex dynamical systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Evidence of decoupling of surface and bulk states in Dirac semimetal Cd 3 As 2

Abstract Dirac semimetals have attracted a great deal of current interests due to their potential applications in topological quantum computing, low-energy electronic devices, and single photon detection in the microwave frequency range. Herein are results from analyzing the low magnetic ( B ) field weak-antilocalization behaviors in a Dirac semimetal Cd 3 As 2 thin flake device. At high temperatures, the phase coherence length l ϕ first increases with decreasing temperature ( T ) and follows a power law dependence of l ϕ ∝ T −0.4 . Below ∼3 K, l ϕ tends to saturate to a value of ∼180 nm. Another fitting parameter α , which is associated with independent transport channels, displays a logarithmic temperature dependence for T > 3 K, but also tends to saturate below ∼3 K. The saturation value, ∼1.45, is very close to 1.5, indicating three independent electron transport channels, which we interpret as due to decoupling of both the top and bottom surfaces as well as the bulk. This result, to our knowledge, provides first evidence that the surfaces and bulk states can become decoupled in electronic transport in Dirac semimetal Cd 3 As 2 .

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

A study of mechanoelectrical transduction behavior in polyvinyl chloride (PVC) gel as smart sensors

Abstract Polyvinyl chloride (PVC) gels are soft electroactive polymers (EAPs) being researched for soft robotic applications. Sensing properties of these EAPs have not been investigated in detail in regard to fundamental mechanoelectrical transduction behavior, but this smart material has been shown to exhibit a detectable response to external stimuli. This study shows PVC gels to be an extremely sensitive material when undergoing mechanoelectrical transduction and explores some response dependencies and proposes a theoretical framework for mechanoelectrical transduction within the gel. The work presented here also uncovers a very interesting phenomena under extremely low compressive loads during the initial contact with the gel. This phenomenon is attributed to a surface tension creeping motion onto the loading surface with an accompanying polarity inversion in the sensing signal relative to fully loaded gels in compression. Experimental work on hysteresis was also completed showing very little memory in steady state mechanoelectrical response to repeated stepped loading cycles. This study demonstrates the mechanoelectric ability of PVC gels to perform in sensing experiments and acts as a fundamental framework to further broaden the applications of PVC gel sensors.

Instruments & Instrumentation↗
DOE OSTI2024

GALIC: hybrid multi-qubitwise pauli grouping for quantum computing measurement

Abstract Observable estimation is a core primitive in NISQ-era algorithms targeting quantum chemistry applications. To reduce the state preparation overhead required for accurate estimation, recent works have proposed various simultaneous measurement schemes to lower estimator variance. Two primary grouping schemes have been proposed: full commutativity (FC) and qubit-wise commutativity (QWC), with no compelling means of interpolation. In this work we propose a generalized framework for designing and analyzing context-aware hybrid FC/QWC commutativity relations. We use our framework to propose a noise-and-connectivity aware grouping strategy: Generalized backend-Aware pauLI Commutation (GALIC). We demonstrate how GALIC interpolates between FC and QWC, maintaining estimator accuracy in Hamiltonian estimation while lowering variance by an average of 20% compared to QWC. We also explore the design space of near-term quantum devices using the GALIC framework, specifically comparing device noise levels and connectivity. We find that error suppression has a more than 10 × larger impact on device-aware estimator variance than qubit connectivity with even larger correlation differences in estimator biases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Perspective: multi-dimensional coherent spectroscopy of perovskite nanocrystals

Abstract Recently, colloidal perovskite nanocrystals (PNCs) have emerged as an exciting material platform for optoelectronic applications due to their combination of facile synthesis routes, quantum size effects, and exceptional optical properties among other favorable characteristics. Given the focus on their optoelectronic properties, spectroscopic characterization of PNCs is crucial to rational design of their structure and device implementation. In this Perspective, we discuss how multi-dimensional coherent spectroscopy (MDCS) can resolve exciton dynamics and circumvent inhomogeneous broadening to reveal underlying homogeneous spectral lineshapes. We highlight recent applications of MDCS to PNCs in the literature, and suggest compelling problems concerning their microscopic physics to be addressed by MDCS in the future.

Liu, Albert (ORCID:0000000167183719)↗
DOE OSTI2024

Implicit quantile networks for emulation in jet physics

Abstract The ability to model and sample from conditional densities is important in many physics applications. Implicit quantile networks (IQN) have been successfully applied to this task in domains outside physics. In this work, we illustrate the potential of IQNs as components of emulators using the simulation of jets as an example. Specifically, we use an IQN to map jets described by their 4-momenta at the generation level to jets at the event reconstruction level. The conditional densities emulated by our model closely match those generated by Delphes , while also enabling faster jet simulation.

Kronheim, Braden (ORCID:0000000307040972)↗
DOE OSTI2024

Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems

The emerging class of high velocity and high volume data analytic workflows comprise interwoven data ingestion, organization, and processing stages, with ingestion and organization steps often contributing comparable or even higher computational costs than actual processing steps. Since complex workflows consist of a variety of phases that view and use data differently, being able to construct efficient, scalable, distributed data structures (arrays, vectors, sets, maps, and multi-maps) is essential and requires custom methods to extend and shrink containers, analyze and position data, and, maintain globallyconsistent meta-data. In this paper, we propose a novel datastructure access paradigm based on the concept of Accessors. At a high level, accessors are customizable callable objects that can modify the behavior of insert, read, update, and delete operations for distributed containers while preserving atomicity guarantees. Accessors provide a very clean and natural way to implement a variety of programming patterns, e.g., conditional insertion/deletion and cascading computations, which would be otherwise hard (or even impossible) to express in parallel and distributed settings without using locks. We demonstrate the practicality and usefulness of our approach with two representative use cases and study the performance of these applications on a distributed High-Performance Computing system. Our analysis highlights that our proposed abstraction allows for an effective overlapping and concurrent execution of different workflow steps (e.g., data ingestion and analysis), which in a conventional analytics pipeline would execute sequentially, contributing cumulatively to the overall latency.

Castellana, Vito G. [BATTELLE (PACIFIC NW LAB)] (O↗
DOE OSTI2023

Experimental and Numerical Investigation of Flow Boiling in Additive Manufactured Foam Structures With Vapor Pathways

Abstract The unique properties of metal foams make them potential candidates for a range of applications, including microsystem thermal management. Using additive manufacturing to create foam-type structures can improve upon prior thermal solutions by eliminating thermal interface materials and allowing for customization/local control of parameters. In the present investigation, flow boiling in additive-manufactured metal foams is investigated both experimentally and numerically. Two test samples, one with uniform structure and the other with pathways for vapor removal, are compared both experimentally and numerically. A conjugate computational fluid dynamics and heat transfer (CFD-HT) model utilizing a three-dimensional volume of fluid (VOF) model with accompanying evaporation/condensation model provided in-depth visualization of the boiling flow phenomena. The experiments generated the thermohydraulic performance over a range of heat fluxes, demonstrating that the sample incorporating dedicated vapor pathways performed better in both pressure and heat transfer performance metrics compared to the uniform foam. Additionally, negative system-level effects (i.e., hydraulic oscillations) were shown to be abated using the vapor removal structures. The numerical model yielded further insight into the factors contributing to the improved performance. Results indicated the pathways functioned as vapor removal channels, allowing the generated vapor to vent from the foam structure into the lanes. Further computational investigations demonstrated changes in flow regimes, where the addition of vapor channels caused the flow to change from churn to annular. Bubble behavior unique to the vapor pathway structure was studied, showing stagnant regions that eject vapor into the channel.

Engineering↗
DOE OSTI2026

BoBa

BoBa is a C++ software library for working with large matrices, tensors, and tensor decompositions. The library provides tools for dense matrix and tensor operations, tensor decompositions, and tensor decomposition methods that support modern CPU and GPU architectures. It includes portable abstractions for linear algebra, tensor algebra, and multidimensional computation. BoBa is intended for scientific computing applications that involve large multidimensional data sets or high dimensional mathematical models. Its capabilities support tasks such as data compression, linear algebra, efficient numerical computation, and the development of scalable algorithms for heterogeneous hardware. Tutorials, tests, and example applications are included to help users learn and apply the library.

Yao, Jin [Lawrence Livermore National Laboratory (↗