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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Extending Imaging Volume in Soft X‐Ray Tomography

Soft X‐ray tomography offers rapid imaging of whole, single cells with a few tens of nanometers spatial resolution without fixation or labeling. Herein, this technique is limited to specimens about 10 μm thick, such that applications of soft X‐ray tomography of large human cells or multicellular specimens are not possible. A theoretical and experimental framework for soft X‐ray tomography that enables extension of imaging volumes to 18 μm‐thick specimens is developed. This approach, based on long depth of field and half‐acquisition tomography, is easily applicable to microscopes equipped with a full‐rotation specimen stage. This opens opportunities for imaging large human cells, such as those commonly seen in cancer research, as well as cell‐to‐cell interactions, where two or more cells occupy the same imaging volume.

Ekman, Axel↗
DOE OSTI2023

High–Yield Deterministic Focused Ion Beam Implantation of Quantum Defects Enabled by In Situ Photoluminescence Feedback

Focused ion beam implantation is ideally suited for placing defect centers in wide bandgap semiconductors with nanometer spatial resolution. However, the fact that only a few percent of implanted defects can be activated to become efficient single photon emitters prevents this powerful capability to reach its full potential in photonic/electronic integration of quantum defects. Here an industry adaptive scalable technique is demonstrated to deterministically create single defects in commercial grade silicon carbide by performing repeated low ion number implantation and in situ photoluminescence evaluation after each round of implantation. An array of 9 single defects in 13 targeted locations is successfully created—a ≈70% yield which is more than an order of magnitude higher than achieved in a typical single pass ion implantation. The remaining emitters exhibit non-classical photon emission statistics corresponding to the existence of at most two emitters. This approach can be further integrated with other advanced techniques such as in situ annealing and cryogenic operations to extend to other material platforms for various quantum information technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Review and Perspective on Cathodoluminescence Analysis of Halide Perovskites

Halide perovskite solar cells have achieved a certified efficiency of 25.2%, surpassing CdTe and CuInGaSe 2 , which have long been regarded as the most-efficient thin-film photovoltaic materials. As this exciting class of materials continues to mature, researchers will require characterization techniques capable of exposing the interplay among structure, chemistry, and optoelectronic properties to inform processing strategies and increase both device efficiencies and long-term stability. Cathodoluminescence microscopy is an ideal technique to provide such information due to the high spatial resolution and robust optical information acquired. Here, the current body of work related to cathodoluminescence analysis of halide perovskite materials for optoelectronic applications is surveyed. This review demonstrates how cathodoluminescence can monitor degradation due to environmental stressors, phase segregation resulting from material processing, and other halide perovskite-centric material issues. A persistent concern associated with e-beam-based analysis of halide perovskites is what effect the electron beam has on the material properties being probed. Addressing this, a detailed discussion is provided on the origin of the cathodoluminescence signal and a review of studies focused on revealing changes in the properties of halide perovskites resulting from e-beam excitation. Finally, a perspective on future opportunities to expand the role of cathodoluminescence analysis for halide perovskites is provided.

14 SOLAR ENERGY↗
DOE OSTI2021

Proton-Radiation Tolerant All-Perovskite Multijunction Solar Cells

Radiation-resistant but cost-efficient, flexible, and ultralight solar sheets with high specific power (W g -1 ) are the "holy grail" of the new space revolution, powering private space exploration, low-cost missions, and future habitats on Moon and Mars. Herein, this study investigates an all-perovskite tandem photovoltaic (PV) technology that uses an ultrathin active layer (1.56 micrometers) but offers high power conversion efficiency, and discusses its potential for high-specific-power applications. This study demonstrates that all-perovskite tandems possess a high tolerance to the harsh radiation environment in space. The tests under 68 MeV proton irradiation show negligible degradation (<6%) at a dose of 10 13 p + cm -2 where even commercially available radiation-hardened space PV degrade >22%. Using high spatial resolution photoluminescence (PL) microscopy, it is revealed that defect clusters in GaAs are responsible for the degradation of current space-PV. By contrast, negligible reduction in PL of the individual perovskite subcells even after the highest dose studied is observed. Studying the intensity-dependent PL of bare low-gap and high-gap perovskite absorbers, it is shown that the V OC , fill factor, and efficiency potentials remain identically high after irradiation. Radiation damage of all-perovskite tandems thus has a fundamentally different origin to traditional space PV.

14 SOLAR ENERGY↗
DOE OSTI2020

Machine learning to predict biomass sorghum yields under future climate scenarios

Crop yield modeling is critical in the design of national strategies for agricultural production, particularly in the context of a changing climate. Forecasting yields of bioenergy crops at fine spatial resolutions can help to evaluate near-term and long-term pathways for scaling up bio-based fuel and chemical production, and for understanding the impacts of abiotic stressors such as severe droughts and temperature extremes on potential biomass supply. In this work we used a large dataset of 28,364 Sorghum bicolor yield samples (uniquely identified by county and year of observation), environmental variables, and multiple approaches to analyze historical trends in sorghum productivity across the USA. We selected the most accurate machine learning approach (a variation of the random forest approach) to predict future trends in sorghum yields under four greenhouse gas (GHG) emission scenarios and two irrigation regimes. We identified irrigation practices, vapor pressure deficit, and time (a proxy for technological improvement) as the most important predictors of sorghum productivity. Our results showed a decreasing trend of sorghum yields over future years (on average 2.7% from 2018 to 2099), with greater decline under a high GHG emissions scenario (3.8%) and in the absence of irrigation (4.6%). Geographically, we observed the steepest predicted declines in the Great Lakes (8.2%), Upper Midwest (7.5%), and Heartland (6.7%) regions. Our study demonstrates the use of machine learning to identify environmental controllers of sorghum biomass yield and predict yields with reasonable accuracy. These results can inform the development of more realistic biomass supply projections for bioenergy if sorghum production is scaled up. (c) 2020 Society of Chemical Industry and John Wiley & Sons, Ltd

09 BIOMASS FUELS↗
DOE OSTI2022

Estimation of pollen productivity and dispersal: How pollen assemblages in small lakes represent vegetation

Abstract Quantitative understanding of vegetation dynamics over timespans beyond a century remains limited. In this regard, the pollen‐based reconstruction of past vegetation enables unique research opportunities by quantifying changes in plant community compositions during hundreds to thousands of years. Critically, the methodological basis for most reconstruction approaches rests upon estimates of pollen productivity and dispersal. Previous studies, however, have reached contrasting conclusions concerning these estimates, which may be perceived to challenge the applicability and reliability of pollen‐based reconstruction. Here we show that conflicting estimates of pollen production and dispersal are, at least in part, artifacts of fixed assumptions of pollen dispersal and insufficient spatial resolution of vegetation data surrounding the pollen‐collecting lake. We implemented a Bayesian statistical model that related pollen assemblages in surface sediments of 33 small lakes (<2 ha) in the northeastern United States, with surrounding vegetation ranging from 10 1 to >10 5 m from the lake margin. Our analysis revealed three key insights. First, pollen productivity is largely conserved within taxa and across forest types. Second, when local (within a 1‐km radius) vegetation abundances are not considered, pollen‐source areas may be overestimated for some common taxa (Cupressaceae, Pinus , Quercus , and Tsuga ). Third, pollen dispersal mechanisms may differ between local and regional scales; this is missed by pollen‐dispersal models used in previous studies. These findings highlight the complex interactions between vegetation heterogeneity on the landscape and pollen dispersal. We suggest that, when estimating pollen productivity and dispersal, both detailed local and extended regional vegetation must be taken into account. Also, both deductive (mechanistic models) and inductive (statistical models) approaches are needed to better understand the emergent properties of pollen dispersal in heterogeneous landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An Optothermal Raman Model Accounting for Convection, Radiation, and Substrate Effects for Evaluation of the Thermal Conductivity of Two‐Dimensional Coatings

Thermal conductivity of two‐dimensional (2D) materials is important to characterize as this will govern thermal transport physics in the various thermal and energy applications benefitting from the unique properties of these materials. Here, analytical and numerical techniques are presented to determine the thermal conductivity and interfacial conductance of a 2D material coating using confocal micro‐Raman spectroscopy as a noncontact diagnostic. While several methods have been proposed for calculating the values of thermal conductivity, interfacial conductance, and spatial temperature profile, these models often do not consider effects of radiation, convection, and substrate resistance on the temperature and heat flux profiles. We present a model to calculate the thermal conductivity and interfacial conductance which accounts for convection, radiation, and substrate effects to characterize a variety of 2D material coatings, which is demonstrated using large area graphene transferred onto copper and nickel substrates. Convection and radiation effects are found to have a negligible effect on the temperature profile of supported coatings, while the substrate effects have a considerable effect and therefore impact the quantification of thermal conductivity and interfacial conductance in addition to limiting the spatial resolution of the technique. These findings will allow for more accurate and reproducible extraction of the thermal conductivity of graphene and other 2D material coatings when employing noncontact optothermal Raman spectroscopy methods.

2D coatings↗
DOE OSTI2023

Simulation studies of a full-ring, CZT SPECT system for whole-body imaging of 99m Tc and 177 Lu

Single photon emission computed tomography (SPECT) is an imaging modality that has demonstrated its utility in a number of clinical indications. Despite this progress, a high sensitivity, high spatial resolution, multi-tracer SPECT with a large field of view suitable for whole-body imaging of a broad range of radiotracers for theranostics is not available. With the goal of filling this technological gap, we have designed a cadmium zinc telluride (CZT) full-ring SPECT scanner instrumented with a broad-energy tungsten collimator. The final purpose is to provide a multi-tracer solution for brain and whole-body imaging. Our static SPECT does not rely on the dual- and the triple-head rotational SPECT standard paradigm, enabling a larger effective area in each scan to increase the sensitivity. We provide a demonstration of the performance of our design using a realistic model of our detector with simulated body-sized phantoms filled with 99m Tc and 177 Lu. Our SPECT design can resolve 7.9 mm rods for 99m Tc (140 keV) and 9.5 mm for 177 Lu (208 keV) in a hot-rod Derenzo phantom with a 3-min exposure and reach an image contrast of 78% for 99m Tc and 57% for 177 Lu using the NEMA IQ phantom with a 6-min exposure. Our modified scatter correction shows an improved contrast-recovery ratio compared to a standard correction. In this paper, we demonstrate the good performance of our design for whole-body imaging purposes. This adds to our previous demonstration of improved qualitative and quantitative 99m Tc imaging of brain perfusion and 123 I imaging of dopamine transport with respect to state-of-the-art NaI dual-head cameras. We show that our design provides similar IQ and contrast to the commercial full-ring SPECT VERITON for 99m Tc. Regarding 177 Lu imaging of the 208 keV emissions, our design provides similar contrast to that of other state-of-the-art SPECTs with a significant reduction in exposure. In conclusion, the high sensitivity and extended energy range up to 250 keV makes our SPECT design a promising alternative for clinical imaging and theranostics of emerging radionuclides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Small Signaling Peptides in Sorghum bicolor : Integrating Phylogeny and Gene Expression to Characterize Roles in Stem Development

Small signaling peptides (SSPs) are important regulators of plant growth, development, and responses to biotic and abiotic stress, yet their role in the C4 grass Sorghum bicolor is largely uncharacterized. To help fill this knowledge gap, 219 sorghum genes that encode SSPs were identified based on SSP sequences previously identified in Arabidopsis thaliana, Zea mays, Oryza sativa, Triticum aestivum , and Brachypodium distachyon . The 219 sorghum SSP-encoding genes were assigned to 19 gene families, analyzed for the presence of motifs, and aligned with genes that encode SSPs in other plants using phylogenetic analysis. Sorghum genes in 12 of the 19 SSP gene families had not been previously characterized. Expression of the 219 SSP-encoding genes in sorghum organs, during stem development, and in stem tissues and cell types revealed distinct spatial, temporal, and developmental patterns of expression. Genes associated with the SbCEP and SbRGF families were preferentially expressed in roots, whereas SbEPF genes were expressed in stem epidermal and pith parenchyma cells and panicles. The expression of genes during bioenergy sorghum stem growth and development was investigated because stems account for ~80% of harvested biomass and serve as conduits for water and nutrient transport between leaves and roots. During stem development, 28 SSP genes in several families ( CLE, EPF, CEP, GASS, PSY, ES, PSK, CAPE, POE ) were expressed at higher levels in zones of cell proliferation. For example, the TDIF homologs SbCLE41 and SbCLE42 were expressed at high levels in nascent stem nodes where they may regulate vascular bundle cambial activity and cell differentiation. A different set of 15 genes in the CIF, POE, CAPE, PSY, CEP, RALF , and CLE families were expressed at higher levels in zones of stem tissue differentiation highlighted by elevated expression of five SbRALFR s in the stem nodal plexus. Cell type–specific expression of many sorghum genes that encode SSPs was observed in fully elongated internodes indicating gene expression is regulated with high spatial resolution. Overall, the results provide a foundation of information for analysis of SSP function in sorghum that can be integrated with knowledge of sorghum gene regulatory networks to modulate traits important for production of sorghum crops.

bioenergy sorghum↗
DOE OSTI2022

Understanding Synthesis and Structural Variation of Nanomaterials Through In Situ/Operando XAS and SAXS

Nanostructured materials with high surface area and low coordinated atoms present distinct intrinsic properties from their bulk counterparts. However, nanomaterials' nucleation/growth mechanism during the synthesis process and the changes of the nanomaterials in the working state are still not thoroughly studied. As two indispensable methods, X-ray absorption spectroscopy (XAS) provides nanomaterials' electronic structure and coordination environment, while small-angle X-ray scattering (SAXS) offers structural properties and morphology information. Here, a combination of in situ/operando XAS and SAXS provides high temporal and spatial resolution to monitor the evolution of nanomaterials. This review gives a brief introduction to in situ/operando SAXS/XAS cells. In addition, the application of in situ/operando XAS and SAXS in preparing nanomaterials and studying changes of working nanomaterials are summarized.

25 ENERGY STORAGE↗
DOE OSTI2021

Imaging Secondary Electron Emission from a Single Atomic Layer

Graphene-based devices hold promise for a wide range of technological applications. Yet characterizing the structure and the electrical properties of a material that is only one atomic layer thick still poses technical challenges. Recent investigations indicate that secondary-electron electron-beam-induced current (SE-EBIC) imaging can reveal subtle details regarding electrical conductivity and electron transport with high spatial resolution. Here, it is shown that the SEEBIC imaging mode can be used to detect suspended single layers of graphene and distinguish between different numbers of layers. Pristine and contaminated areas of graphene are also compared to show that pristine graphene exhibits a substantially lower SE yield than contaminated regions. In conclusion, this SEEBIC imaging mode may provide valuable information for the engineering of surface coatings where SE yield is a priority.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Signal Origin of Electrochemical Strain Microscopy and Link to Local Chemical Distribution in Solid State Electrolytes

Electrochemical strain microscopy (ESM) is a distinguished method to characterize Li-ion mobility in energy materials with extremely high spatial resolution. The exact origin of the cantilever deflection when the technique is applied on solid state electrolytes (SSEs) is currently discussed in the literature. Under-standing local properties and influences on ion mobility in SSEs is of utmost importance to improve such materials for next generation batteries. Here, the exact signal formation process of ESM when applied on sodium super ionic conductor (NASICON)-type SSE containing Na- and Li-ions is investigated. Changes in the dielectric properties, which are linked to the local chemical composition, are found to be responsible for the observed contrast in the deflection of the cantilever instead of a physical volume change as a result of Vegard´s Law. The cantilever response is strongly reduced in areas of high sodium content which is attributed to a reduction of the tip-sample capacitance in comparison to areas with high lithium content. This is the first time a direct link between electrostatic forces in contact mode and local chemical information is demonstrated on SSEs. Furthermore, the results open up new possibilities in information gain since dielectric proper-ties are sensitive to subtle changes in local chemical composition.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Imaging Bias‐Driven Domain Wall Motion With Scanning Oscillator Piezoresponse Force Microscopy

Understanding ferroelectric domain wall dynamics at the nanoscale across a broad range of timescales requires measuring domain wall position under different applied electric fields. The success of piezoresponse force microscopy (PFM) as a tool to apply local electric fields at different positions and imaging their changing position, together with the information obtained from associated switching spectroscopies has fueled numerous studies of the dynamics of ferroelectric domains to determine the impact of intrinsic parameters such as crystalline order, defects and pinning centers, as well as boundary conditions such as environment. However, the investigation of sub-coercive reversible domain wall vibrational modes requires the development of new tools that enable visualizing domain wall motion under varying applied fields with high temporal and spatial resolution while also accounting for spurious electrostatic effects. Here, scanning oscillator piezoresponse force microscopy extends the investigation of domain wall dynamics to new regimes, providing direct visualization of domain wall position as a function of an external electric field that varies in time and location. In conclusion, this enables studying the energetics of field-driven ferroelectric domain wall motion, which is shown to obey a thermally activated flow regime in the millisecond timescale.

Piezoresponse Force Microscopy↗
DOE OSTI2026

Capturing soil moisture and salinity changes in flooded coastal forests using electrical resistivity and induced polarization

Geophysical methods provide high-resolution spatial measurements of physical quantities sensitive to changes in soil moisture and salinity and can be used to monitor soil hydrological responses to flooding. However, extracting quantitative hydrological information from geophysical data remains challenging. In this study, we extended existing petrophysical models to estimate soil moisture and salinity from electrical measurements to address this challenge. We manipulated two hydrologically isolated 2000 m 2 experimental plots by simultaneously inundating them with 265 m 3 of either freshwater or estuarine water. Repeated electrical resistivity and induced polarization measurements were used to image the water and solute infiltration along two transects that are 100 and 42 m in length. Petrophysical models derived from laboratory multi-salinity electrical measurements were used to estimate changes in soil moisture and fluid salinity from field measurements of real and imaginary conductivity during the ecosystem-scale flooding experiment. The real conductivity increased by ∼100% in the freshwater plot and ∼570% in the saltwater plot. The change in imaginary conductivity in the freshwater plot was <1 mS/m, whereas that of the estuarine water plot was ∼5 mS/m. Real conductivity shows dependence on soil moisture content with a coefficient of determination (R 2 ) > 0.7, while the imaginary conductivity shows a dependence on soil salinity with R 2 > 0.6. The results validate the use of electrical resistivity for estimating changes in soil moisture content in response to flooding. Combining electrical resistivity imaging with induced polarization measurements provides the possibility to account for changes in pore fluid conductivity.

Adebayo, Moses B. [Univ. of Toledo, OH (United Sta↗
DOE OSTI2026

Neutron Grating Interferometry at the High Flux Isotope Reactor

Neutron imaging is a non-destructive probe that can spatially resolve bulk materials’ internal features/structures. Neutron imaging spatial resolution is driven by detector technology, i.e., pixel size, and is currently on the order of 10–20 µm. This limitation can be alleviated by the use of neutron grating interferometry – an advanced neutron imaging technique – that enables simultaneous access to three contrast mechanisms: attenuation, differential phase, and small-angle neutron scattering. Recently, a Talbot-Lau neutron grating interferometry has been implemented at the Multimodal Advanced Radiography Station at the High Flux Isotope Reactor. In this work, the design, setup and performance of the grating apparatus are presented.

Zhang, Yuxuan [ORNL] (ORCID:0000000200831408)↗
DOE OSTI2025

Reconstructing neutrinoless double beta decay event kinematics in a xenon gas detector with vertex tagging

If neutrinoless double beta decay is discovered, the next natural step would be understanding the lepton number violating physics responsible for it. Several alternatives exist beyond the exchange of light neutrinos. Some of these mechanisms can be distinguished by measuring phase-space observables, namely the opening angle cos θ among the two decay electrons, and the electron energy spectra, T 1 and T 2 . In this work, we study the statistical accuracy and precision in measuring these kinematic observables in a future xenon gas detector with the added capability to precisely locate the decay vertex. For realistic detector conditions (a gas pressure of 10 bar and spatial resolution of 4 mm), we find that the average $\overline{cos θ}$ and $\overline{T_1}$ values can be reconstructed with a precision of 0.19 and 110 keV, respectively, assuming that only 10 neutrinoless double beta decay events are detected.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Predicting Fracture Network Development in Crystalline Rocks

The geometric properties of fractures influence whether they propagate, arrest, or coalesce with other fractures. Thus, quantifying the relationship between fracture network characteristics may help predict fracture network development, and perhaps precursors to catastrophic failure. To constrain the relationship and predictability of fracture characteristics, we deform eight one centimeter tall rock cores under triaxial compression while acquiring in situ X-ray tomograms. The tomograms reveal precise measurements of the fracture network characteristics above the spatial resolution of 6.5 µm. We develop machine learning models to predict the value of each characteristic using the other characteristics, and excluding the macroscopic stress or strain imposed on the rock. The models predict fracture development more accurately in the experiments performed on granite and monzonite, than the experiments on marble. Fracture network development may be more predictable in these igneous rocks because their microstructure is more mechanically homogeneous than the marble, producing more systematic fracture development that is not strongly impeded by grain contacts and cleavage planes. The varying performance of the models suggest that fracture volume, length, and aperture are the most predictable of the characteristics, while fracture orientation is the least predictable. Orientation does not correlate with length, as suggested by the idea that the orientation evolves with increasing differential stress and thus fracture length. This difference between the observed and expected relationship between orientation and length highlights the influence of mechanical heterogeneities and local stress perturbations on fracture growth as fractures propagate, link, and coalesce.

58 GEOSCIENCES↗