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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Making the most of your electrons: Challenges and opportunities in characterizing hybrid interfaces with STEM

Inspired by the unique architectures composed of hard and soft materials in natural and biological systems, synthetic hybrid structures and associated hard-soft interfaces have recently evoked significant interest. Soft matter is typically dominated by structural fluctuations even at room temperature, while hard matter is governed by rigid mechanical behavior. This dichotomy offers considerable opportunities to leverage the disparate properties offered by these components across a wide spectrum spanning from basic science to engineering insights with significant technological overtones. Such hybrid structures, which include polymer nanocomposites, DNA functionalized nanoparticle superlattices, and metal organic frameworks to name a few, have delivered promising insights into the technologically relevant applications such as catalysis, environmental remediation, optoelectronics, and medicine. The interfacial structure between the hard and soft phases demonstrates features across a variety of length scales and often strongly influence the functionality of hybrid systems. While scanning/transmission electron microscopy (S/TEM) has proven to be a valuable tool for acquiring intricate molecular and nanoscale details of these interfaces, the unusual nature of hybrid composites presents a suite of challenges that make assessing or establishing structure–property relationships especially difficult. There are additional considerations at all stages of sample analysis from preparing electron-transparent samples to obtaining sufficient contrast to resolve the interface between dissimilar materials given the dose sensitivity of soft materials. Here, we discuss each of these challenges and supplement a review of recent developments in the field with additional experimental investigations and simulations to present solutions for attaining a nano or molecular-level understanding of these interfaces. These solutions present a host of opportunities for investigating the role interfaces play in this unique class of functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Excitonic density wave and spin-valley superfluid in bilayer transition metal dichalcogenide

Artificial moiré superlattices in 2 d van der Waals heterostructures are a new venue for realizing and controlling correlated electronic phenomena. Recently, twisted bilayer WSe 2 emerged as a new robust moiré system hosting a correlated insulator at moiré half-filling over a range of twist angle. In this work, we present a theory of this insulating state as an excitonic density wave due to intervalley electron–hole pairing. We show that exciton condensation is strongly enhanced by a van Hove singularity near the Fermi level. Our theory explains the remarkable sensitivity of the insulating gap to the vertical electric field. In contrast, the gap is weakly reduced by a perpendicular magnetic field, with quadratic dependence at low field. The different responses to electric and magnetic field can be understood in terms of pair-breaking versus non-pair-breaking effects in a BCS analog of the system. We further predict superfluid spin transport in this electrical insulator, which can be detected by optical spin injection and spatial-temporal imaging.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO 2

Water availability plays a critical role in shaping terrestrial ecosystems, particularly in low- and mid-latitude regions. The sensitivity of vegetation growth to precipitation strongly regulates global vegetation dynamics and their responses to drought, yet sensitivity changes in response to climate change remain poorly understood. Here we use long-term satellite observations combined with a dynamic statistical learning approach to examine changes in the sensitivity of vegetation greenness to precipitation over the past four decades. We observe a robust increase in precipitation sensitivity (0.624% yr –1 ) for drylands, and a decrease (–0.618% yr –1 ) for wet regions. Using model simulations, we show that the contrasting trends between dry and wet regions are caused by elevated atmospheric CO 2 (eCO 2 ). eCO 2 universally decreases the precipitation sensitivity by reducing leaf-level transpiration, particularly in wet regions. However, in drylands, this leaf-level transpiration reduction is overridden at the canopy scale by a large proportional increase in leaf area. The increased sensitivity for global drylands implies a potential decrease in ecosystem stability and greater impacts of droughts in these vulnerable ecosystems under continued global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Silicon Photomultipliers Coupled to Scintillators With the Emission Maximum at 550 nm

A majority of the silicon photomultipliers (SiPMs) are sensitive to blue and near-ultraviolet (NUV) photons that are not optimized for scintillators with the emission maximum at wavelengths longer than 500 nm. The red–green–blue (RGB) SiPM is developed for the maximum photon detection efficiency (PDE) at 550 nm, which is a good match for some high-light-yield scintillators, such as CsI:Tl (CsI) and Gd 1.5 Y 1.5 Ga 2 Al 3 O 12 :Ce (GYGAG). Comparisons are made for the performance of these scintillators coupled to the RGB SiPM and a blue-sensitive SiPM. Because it takes tens of nanoseconds for the microcells to recharge after registering a photon hit, the linearity of these scintillation detectors was studied for high-energy gammas where numerous scintillation photons are generated. In addition, the energy resolution of the 662-keV gamma emitted by 137 Cs was measured for temperatures between –20 °C and 50 °C. The nonlinearity was observed above 1 MeV for all measurements, and however, it can be corrected by energy calibration using a third-degree polynomial. For CsI, the energy resolution is better with the blue-sensitive SiPM because of the lower dark count rate (DCR). In contrast, GYGAG coupled to the RGB SiPM has a better energy resolution for temperatures below 30 °C because of the well-matched emission spectrum and PDE distribution. Nevertheless, the advantage disappears for temperatures above 30 °C due to the higher DCR. It would be useful to further develop the RGB SiPM with a lower DCR and higher operating temperatures.

42 ENGINEERING↗
DOE OSTI2026

Fast and Accurate Intersections on a Sphere

We introduce a fast, high-precision algorithm for calculating intersections between great circle arcs and lines of constant latitude on the unit sphere. We first propose a simplified intersection point formula with improved speed and numerical robustness over the ones traditionally implemented in geoscience software. We then show how algorithms based on the concept of error-free transformations (EFT) can be applied to evaluate this formula within a relative error bound that is on the order of machine precision. Here, we demonstrate that, with a vectorized and parallelized implementation, this enhanced accuracy is achieved with no compute time overhead compared to a direct calculation in hardware floating point, making our algorithm suitable for performance-sensitive applications like regridding of high-resolution climate data. In contrast, evaluating our formula using high-precision data types like quadruple precision and arbitrary precision, or using the robust intersection computation routines from the Computational Geometry Algorithms Library, leads to significant computational overhead, especially since these alternatives inhibit vectorization. More generally, our work demonstrates how EFT techniques can be combined and extended to implement nontrivial geometric calculations with high accuracy and speed.

Environmental sciences↗
DOE OSTI2023

Revealing the Mechanism Behind Sudden Capacity Loss in Lithium Metal Batteries

Rechargeable Li-metal batteries (LMBs) are attractive energy storage candidates for electric vehicles (EVs) because they offer higher energy density than batteries built with intercalation electrodes. However, one of the main barriers to the commercial deployment of LMBs has been their relatively short cycle life. Re-designing the electrolyte system shows promise in achieving acceptable cycle life, but even so, the resulting cells display a challenging end-of-life (EOL) behavior: a sudden capacity loss. Herein, we report a new method for analyzing voltage profiles during cycling to distinguish between the capacity loss originating from the loss of cathode capacity vs growth in cell resistance. Further, this analysis reveals that sudden capacity loss was preceded by acceleration in the rate of growth of cell resistance, and cycling of multiple cells showed that this phenomenon is sensitive to the initial quantity of electrolyte in the cells. In contrast, the cathode capacity degraded at a constant rate independent of the electrolyte quantity. Combining this evidence with post-analysis of harvested electrolyte and electrodes, we conclude that neither the loss of active lithium nor the loss of active cathode material was the primary source of sudden capacity loss; instead, consumption and decomposition of electrolyte causes the drastic capacity loss at EOL.

25 ENERGY STORAGE↗
DOE OSTI2021

Convection–Kelvin Wave Coupling in a Global Convection-Permitting Model

A convectively coupled equatorial Kelvin wave (CCKW) was observed over the equatorial Indian Ocean in early November 2011 during the DYNAMO field campaign. This study examines the structure of the CCKW event using two simulations made using the MPAS model: one with 3-km grid spacing without convective parameterization and another with a 15-km grid and parameterized convection. Both simulations qualitatively capture the observed structure of the CCKW, including its vertical tilt and progression of cloud/precipitation structures. The two simulations, however, differ substantially in the amplitude of the CCKW-associated precipitation. While the 3-km run realistically captures the observed modulation of precipitation by the CCKW, the 15-km simulation severely underestimates its magnitude. To understand the difference between the two MPAS simulations regarding wave–convection coupling within the CCKW, the relationship of precipitation with convective inhibition, saturation fraction, and surface turbulent fluxes is investigated. Results show that the 15-km simulation underestimates the magnitude of the CCKW precipitation peak in association with its unrealistically linear relationship between moisture and precipitation. Precipitation, both in observations and the 3-km run, is predominantly controlled by saturation fraction and this relationship is exponential. In contrast, the parameterized convection in the 15-km run is overly sensitive to convective inhibition and not sensitive enough to environmental moisture. The implications of these results on CCKW theories are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Comparison of Shadowgraphy and X-Ray Phase Contrast Methods for Characterizing a DT Ice Layer in an Inertial Confinement Fusion Target

Shadowgraphy and x-ray phase contrast (XPC) imaging are two techniques that are used for characterizing the deuterium-tritium ice layer in Inertial Confinement Fusion targets. Each technique has limitations that affect how accurately they can characterize small crystalline defects and measure the ice-thickness non-uniformities that may be only a few micrometers in height. The concern is that shadowgraphy may be overly sensitive to the shape and depth of defects in the surface and insufficiently sensitive to the shape of longer-wavelength roughness, while x-ray phase contrast may be too insensitive to defects in the ice surface. Multiple ice layers with different thicknesses (40 to 63 μm), thickness uniformities (peak-valley variations that range from <2- to 12 μm), and crystal defects were analyzed using shadowgraphy and x-ray phase contrast techniques. The results from each method agree when the ice layer is uniformly thick and the crystal lacks defects. That agreement worsens as the number of defects in the surface of the ice layer increases and the roughness that is determined from a shadowgram image of the target’s limb is greater than can be justified by the number of defects that are seen in the target’s front and rear surfaces. The XPC technique is considerably less sensitive to surface defects, in part due to the poorer dynamic range and image resolution compared to shadowgraphy. Localized regions of the ice layer that are thicker or thinner than the average thickness of the layer are reported by shadowgraphy to be smaller in height and footprint (by up to 30%) than by XPC. As a result, the two techniques report different ice layer thicknesses that can vary by up to 10%. Shadowgraphy results from two caustics that trace different paths through the target, and, in theory, image the same ice-vapor surface (but reflect from either the vapor or ice side of the interface) did not consistently characterize the size or shape of ice features to be the same magnitude. Here, the XPC technique provides the best assessment of low-mode (l < 7) roughness in the ice layer. Shadowgraphy results using the strongest caustic is best for detecting the presence of grooves in the ice, though not for quantifying the size of them. If multiple grooves are present it is best to discard and reform the ice layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Real-time X-ray phase-contrast imaging using SPINNet—a speckle-based phase-contrast imaging neural network

X-ray phase-contrast imaging has become indispensable for visualizing samples with low absorption contrast. In this regard, speckle-based techniques have shown significant advantages in spatial resolution, phase sensitivity, and implementation flexibility compared with traditional methods. However, the computational cost associated with data inversion has hindered their wider adoption. By exploiting the power of deep learning, we developed a speckle-based phase-contrast imaging neural network (SPINNet) that significantly improves the imaging quality and boosts the phase retrieval speed by at least 2 orders of magnitude compared to existing methods. To achieve this performance, we combined SPINNet with a coded-mask-based technique, an enhanced version of the speckle-based method. Using this scheme, we demonstrate the simultaneous reconstruction of absorption and phase images on the order of 100 ms, where a traditional correlation-based analysis would take several minutes even with a cluster. In addition to significant improvement in speed, our experimental results show that the imaging and phase retrieval quality of SPINNet outperform existing single-shot speckle-based methods. Furthermore, we successfully demonstrate SPINNet application in x-ray optics metrology and 3D x-ray phase-contrast tomography. Our result shows that SPINNet could enable many applications requiring high-resolution and fast data acquisition and processing, such as in situ and in operando 2D and 3D phase-contrast imaging and real-time at-wavelength metrology and wavefront sensing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Graph-based Reversible Evaluation and Tangents Library

GRETL is a C++ library for evaluation, re-evaluation and algorithmic differentiation of functional operations on an arbitrary computational graph with limited memory usage. Similar to popular machine learning frameworks in Python, like PyTorch and JAX, it tracks and stores both operations and output data as functions are evaluated. Once this composition of functions is built up, the entire chain of operations can be back propagated to compute sensitivities of the final result with respect to any number of inputs. In contrast to most machine learning applications, memory usage becomes the bottleneck for back propagation in many physics applications, especially for time-dependent PDEs. Dynamic check pointing becomes essential. An important distinguishing feature of GRETL is its ability to limit the maximum memory usage by automatically dynamic checkpointing the data output for each graph operation (see Wang, Moin, Iaccarino, 2009). During backpropagation, parts of the graph that are no longer in memory are automatically re-evaluated from upstream checkpointed states as needed for derivative sensitivity calculations (or more precisely, for vector-Jacobian products). GRETL is particularly beneficial for applications, such as coupled multi-physics, where deriving adjoint-based sensitivities and managing checkpoint memory across modules becomes onerous. Cases which can be readily handled by the GRETL library include: different time-integration algorithms per physics (e.g., coupled predictor-corrector algorithms, IMEX, etc.), sub-cycling, asynchronous integrators, state dependent timestep sizes, iterative solvers and coupling algorithms, controller algorithms, and more.

Tupek, MichaelR [Lawrence Livermore National Labor↗
DOE OSTI2021

Stochastic simulations of temporally and spatially variable Fe cycling within a floodplain aquifer

This data package contains model input and output files for local and global sensitivity analysis (SA) of a reactive transport model simulating redox cycling within a floodplain aquifer. The reaction network is implemented in CrunchFlow and focuses on spatially and temporally heterogeneous Fe cycling, though it contains several other species and redox pathways (37 aqueous species and 7 minerals in total). The package contains data from 600 Monte Carlo simulations (for global SA) and 104 one-at-a-time simulations (for local SA). It includes all input files required to run the CrunchFlow model, as well as limited model output – .csv files containing time series of primary species concentrations at 21 grid cells within the domain. These time series files contain the following species: H+, CO32-, SO42-, Cl-, Ca2+, Mg2+, Na+, K+, Fe(II), Fe(III), HS-, CH3COO-, O2(aq), S(aq), and Br-.These data were used to demonstrate the application of a novel form of global SA, distance-based generalized sensitivity analysis (DGSA) to a reactive transport model. The 2D model simulates the export of reduced species from pockets of fine-grained, organic-rich sediments embedded in a coarse sand aquifer. Stochastic simulations jointly varied 17 key model input parameters across several orders of magnitude, including the spatial variability of each parameter. DGSA on the model results reveal that the amplitude and variability of exported Fe(II) are most sensitive to the interaction between sand permeability and individual reaction rates. By contrast, the propagation of reducing conditions downgradient from the fine-grained lenses depends most heavily on the rate of dissolved organic carbon and sulfate release from the fines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Detection of uranium-photofission neutrons with a 4 He scintillation detector

The use of photon active interrogation to detect special nuclear material has held significant theoretical promise, as the interrogating source particles, photons, are fundamentally different from one of the main signatures of special nuclear material: neutrons produced in nuclear fission. However, neutrons produced by photonuclear reactions in the accelerator target, collimator, and environment can obscure the fission neutron signal. These (γ, n) neutrons could be discriminated from fission neutrons by their energy spectrum, but common detectors sensitive to the neutron spectrum, like organic scintillators, are typically hampered by the intense photon background characteristic of photon-based active interrogation. In contrast, high-pressure 4 ⁢He-based scintillation detectors are well-suited to photon active interrogation, as they are similarly sensitive to fast neutrons and can measure their spectrum, but show little response to gamma rays. Here, in this work, a photon active interrogation system utilizing a 4 ⁢He scintillation detector and a 9 MeV linac-bremsstrahlung x-ray source was experimentally evaluated. The detector was shown to be capable of operating in intense gamma-ray environments and detecting photofission neutrons from 238 ⁢U when interrogated by this x-ray source. The photofission neutrons show clear spectral separation from (γ, n) neutrons produced in lead, a common shielding material.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Composition-Dependent Photoluminescence Properties and Anti-Counterfeiting Applications of A 2 AgX 3 (A = Rb, Cs; X = Cl, Br, I)

Copper(I) halides are emerging as attractive alternatives to lead halide perovskites for optical and electronic applications. However, blue-emitting all-inorganic copper(I) halides suffer from poor stability and lack of tunability of their photoluminescence (PL) properties. In this work, the preparation of silver(I) halides A 2 AgX 3 (A = Rb, Cs; X = Cl, Br, I) through solid-state synthesis is reported. In contrast to the Cu(I) analogs, A 2 AgX 3 are broad-band emitters sensitive to A and X site substitutions. First-principle calculations show that defect-bound excitons are responsible for the observed main PL peaks in Rb 2 AgX 3 and that self-trapped excitons (STEs) contribute to a minor PL peak in Rb 2 AgBr 3 . This is in sharp contrast to Rb 2 CuX 3 , in which the PL is dominated by the emission by STEs. Moreover, the replacement of Cu(I) with Ag(I) in A 2 AgX 3 significantly improves photostability and stability in the air under ambient conditions, which enables their consideration for practical applications. Thus, luminescent inks based on A 2 AgX 3 are prepared and successfully used in anti-counterfeiting applications. The excellent light emission properties, significantly improved stability, simple preparation method, and tunable light emission properties demonstrated by A 2 AgX 3 suggest that silver(I) halides may be attractive alternatives to toxic lead halide perovskites and unstable copper(I) halides for optical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalable multiphoton quantum metrology with neither pre- nor post-selected measurements

The quantum statistical fluctuations of electromagnetic fields establish a limit, known as the shot-noise limit, on the sensitivity of optical measurements performed with classical technologies. However, quantum technologies are not constrained by this shot-noise limit. In this regard, the possibility of using every photon produced by quantum sources of light to estimate small physical parameters, beyond the shot-noise limit, constitutes one of the main goals of quantum optics. Here, we experimentally demonstrate a scalable protocol for quantum-enhanced optical phase estimation across a broad range of phases, with neither pre- nor post-selected measurements. This is achieved through the efficient design of a source of spontaneous parametric downconversion in combination with photon-number-resolving detection. The robustness of two-mode squeezed vacuum states against loss allows us to outperform schemes based on N00N states, in which the loss of a single photon is enough to remove all phase information from a quantum state. In contrast to other schemes that rely on N00N states or conditional measurements, the sensitivity of our technique could be improved through the generation and detection of high-order photon pairs. This unique feature of our protocol makes it scalable. Furthermore, our work is important for quantum technologies that rely on multiphoton interference such as quantum imaging, boson sampling, and quantum networks.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Distinct Gas-Particle Partitioning and Viscosity Characteristics of Secondary Organic Aerosols Derived from α-Pinene versus Ocimene

Secondary organic aerosols (SOA) have complex, multicomponent composition that controls particle viscosity and gas-particle partitioning, key factors to their atmospheric evolution. This study investigates the chemical composition, volatility and viscosity of SOA formed by ozonolysis of cyclic α-pinene (PSOA) and acyclic ocimene (OSOA) monoterpenes. Using Temperature-Programmed Desorption combined with Direct Analysis in Real-Time ionization and High-Resolution Mass Spectrometry, we determined the molecular composition and saturation mass concentration of individual SOA constituents. These data enabled gas-particle partitioning and viscosity estimates under varied atmospheric conditions. PSOA, composed of higher molecular weight and less oxidized species, shows higher condensability and viscosity under high total organic mass (tOM) loadings. Here, in contrast, OSOA, consisting of more oxidized, lower molecular weight species, exhibits greater sensitivity to tOM, with viscosity increasing significantly upon dilution. Poke-flow experiments support this trend, indicating that OSOA undergoes more dynamic compositional and phase changes during atmospheric aging. These observations reveal distinct dynamic trends in the atmospheric transformations and reactivity of SOA from cyclic and acyclic monoterpenes, with the latter showing greater compositional changes during aging that alter viscosity and diffusion. This highlights the importance of incorporating such dynamic transformations into atmospheric models to improve predictions of SOA atmospheric loadings, lifetimes, and impacts.

cyclic and acyclic monoterpenes↗
DOE OSTI2020

Flexoinduced ferroelectricity in low-dimensional transition metal dichalcogenides

We developed a Landau-type theory for the description of polar phenomena in low-dimensional transition metal dichalcogenides (TMDs), specifically exploring the flexoelectric origin of the polarization induced by a spontaneous bending and by inversion symmetry breaking due to the interactions with substrate. We consider the appearance of the spontaneous out-of-plane polarization due to the flexoelectric coupling with the strain gradient of the spontaneous surface rippling and surface-induced piezoelectricity. Additionally, performed calculations proved that the out-of-plane spontaneous polarization, originating from the flexoelectric effect in a rippled TMD, is bistable and reversible by a nonuniform electric field. In contrast, the spontaneous polarization induced by a misfit strain and symmetry-sensitive surface-induced piezoelectric coupling, cannot be reversed by an external electric field. Special attention is paid to the spectral analysis of the linear dielectric susceptibility and gain factor, which enhancement is critically important for the observation of the polar phenomena in low-dimensional TMDs by the surface-enhanced vibrational spectroscopy.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Examination of the sensitivity of quasifree reactions to details of the bound-state overlap functions

It is often stated that heavy-ion nucleon knockout reactions are mostly sensitive to the tails of the bound-state wave functions. In contrast, (p,2p) and (p,pn) reactions are known to access information on the full overlap functions within the nucleus. We analyze the oxygen isotopic chain and explore the differences between single-particle wave functions generated with potential models, used in the experimental analysis of knockout reactions, and ab initio computations from self-consistent Green's function theory. Contrary to common belief, we find that not only the tail of the overlap functions, but also their internal part is assessed in both reaction mechanisms, which are crucial to yield accurately determined spectroscopic information.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Low-energy Electron-track Imaging for a Liquid Argon Time-projection-chamber Telescope Concept Using Probabilistic Deep Learning

The GammaTPC is an MeV-scale single-phase liquid argon time-projection-chamber gamma-ray telescope concept with a novel dual-scale pixel-based charge-readout system. It promises to enable a significant improvement in sensitivity to MeV-scale gamma rays over previous telescopes. The novel pixel-based charge readout allows for imaging of the tracks of electrons scattered by Compton interactions of incident gamma rays. The two primary contributors to the accuracy of a Compton telescope in reconstructing an incident gamma-ray’s original direction are its energy and position resolution. In this work, we focus on using deep learning to optimize the reconstruction of the initial position and direction of electrons scattered in Compton interactions, including using probabilistic models to estimate predictive uncertainty. We show that the deep-learning models are able to predict locations of Compton scatters of MeV-scale gamma rays from simulated 500 μm pixel-based data to better than 1 mm rms error and are sensitive to the initial direction of the scattered electron. We compare and contrast different deep-learning uncertainty estimation algorithms for reconstruction applications. Additionally, we show that event-by-event estimates of the uncertainty of the locations of the Compton scatters can be used to select those events that were reconstructed most accurately, leading to improvement in locating the origin of gamma-ray sources on the sky.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗