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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Modification of cell wall polysaccharide guides cell division in Streptococcus mutans

In ovoid-shaped, Gram-positive bacteria, MapZ guides FtsZ-ring positioning at cell equators. The cell wall of the ovococcus Streptococcus mutans contains peptidoglycan decorated with serotype c carbohydrates (SCCs). In the present study, we identify the major cell separation autolysin AtlA as an SCC-binding protein. AtlA binding to SCC is attenuated by the glycerol phosphate (GroP) modification. Using fluorescently labeled AtlA constructs, we mapped SCC distribution on the streptococcal surface, revealing enrichment of GroP-deficient immature SCCs at the cell poles and equators. The immature SCCs co-localize with MapZ at the equatorial rings throughout the cell cycle. In GroP-deficient mutants, AtlA is mislocalized, resulting in dysregulated cellular autolysis. These mutants display morphological abnormalities associated with MapZ mislocalization, leading to FtsZ-ring misplacement. Altogether, our data support a model in which maturation of a cell wall polysaccharide provides the molecular cues for the recruitment of cell division machinery, ensuring proper daughter cell separation and FtsZ-ring positioning.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Identification of new marker genes from plant single‐cell RNA‐seq data using interpretable machine learning methods

Summary An essential step in the analysis of single‐cell RNA sequencing data is to classify cells into specific cell types using marker genes. In this study, we have developed a machine learning pipeline called single‐cell predictive marker (SPmarker) to identify novel cell‐type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning models to select marker genes. We have demonstrated that our method can: assign cell types based on cells that were labelled using published methods; project cell types identified by trajectory analysis from one data set to other data sets; and assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, the new marker genes have more orthologous genes identifiable in the corresponding rice single‐cell clusters. The new root hair marker genes also include 172 genes with orthologs expressed in root hair cells in five non‐ Arabidopsis species, which expands the number of marker genes for this cell type by 35–154%. Our results represent a new approach to identifying cell‐type marker genes from scRNA‐seq data and pave the way for cross‐species mapping of scRNA‐seq data in plants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Mushroom body input connections form independently of sensory activity in Drosophila melanogaster

Associative brain centers, such as the insect mushroom body, need to represent sensory information in an efficient manner. In Drosophila melanogaster, the Kenyon cells of the mushroom body integrate inputs from a random set of olfactory projection neurons, but some projection neurons—namely those activated by a few ethologically meaningful odors—connect to Kenyon cells more frequently than others. This biased and random connectivity pattern is conceivably advantageous, as it enables the mushroom body to represent a large number of odors as unique activity patterns while prioritizing the representation of a few specific odors. How this connectivity pattern is established remains largely unknown. Here, we test whether the mechanisms patterning the connections between Kenyon cells and projection neurons depend on sensory activity or whether they are hardwired. We mapped a large number of mushroom body input connections in partially anosmic flies—flies lacking the obligate odorant co-receptor Orco—and in wild-type flies. Statistical analyses of these datasets reveal that the random and biased connectivity pattern observed between Kenyon cells and projection neurons forms normally in the absence of most olfactory sensory activity. Finally, this finding supports the idea that even comparatively subtle, population-level patterns of neuronal connectivity can be encoded by fixed genetic programs and are likely to be the result of evolved prioritization of ecologically and ethologically salient stimuli.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Super-moiré spin textures in twisted two-dimensional antiferromagnets

Stacking two-dimensional layered materials offers a platform to engineer electronic and magnetic states. In general, the resulting states—such as moiré magnetism—have a periodicity at the length scale of the moiré unit cell. Here we study magnetic order in twisted double-bilayer chromium triiodide by means of scanning nitrogen-vacancy microscopy. We observe long-range magnetic textures extending beyond the single moiré unit cell, which we dub a super-moiré magnetic state. At small twist angles, the size of the spontaneous magnetic texture increases with twist angle, opposite to the underlying moiré wavelength. The spin-texture size reaches a maximum of about 300 nm in 1.1° twisted devices, an order of magnitude larger than the underlying moiré wavelength, and vanishes at twist angles above 2°. The obtained magnetic field maps suggest the formation of antiferromagnetic Néel-type skyrmions spanning multiple moiré cells. The twist-angle-dependent study, combined with large-scale atomistic Monte Carlo simulations, suggests that the magnetic competition between the Dzyaloshinskii–Moriya interaction, magnetic anisotropy and exchange interactions—which all depend on the relative rotation of the layers—produces the topological textures that emerge in the super-moiré spin order.

Wong, King Cho [Univ. of Stuttgart (Germany)] (ORC↗
DOE OSTI2021

Charge order textures induced by non-linear couplings in a half-doped manganite

Abstract The self-organization of strongly interacting electrons into superlattice structures underlies the properties of many quantum materials. How these electrons arrange within the superlattice dictates what symmetries are broken and what ground states are stabilized. Here we show that cryogenic scanning transmission electron microscopy (cryo-STEM) enables direct mapping of local symmetries and order at the intra-unit-cell level in the model charge-ordered system Nd 1/2 Sr 1/2 MnO 3 . In addition to imaging the prototypical site-centered charge order, we discover the nanoscale coexistence of an exotic intermediate state which mixes site and bond order and breaks inversion symmetry. We further show that nonlinear coupling of distinct lattice modes controls the selection between competing ground states. The results demonstrate the importance of lattice coupling for understanding and manipulating the character of electronic self-organization and that cryo-STEM can reveal local order in strongly correlated systems at the atomic scale.

42 ENGINEERING↗
DOE OSTI2025

Deep learning of structural morphology imaged by scanning X-ray diffraction microscopy

Scanning X-ray nanodiffraction microscopy is a powerful technique for spatially resolving nanoscale structural morphologies by diffraction contrast. One of the critical challenges in experimental nanodiffraction data analysis is posed by the convergence angle of nanoscale focusing optics which creates simultaneous dependency of the far-field scattering data on three independent components of the local strain tensor-corresponding to dilation and two potential rigid body rotations of the unit cell. All three components are in principle resolvable through a spatially mapped sample tilt series; however, traditional data analysis is computationally expensive and prone to artifacts. In this study, we implement NanobeamNN, a convolutional neural network specifically tailored to the analysis of scanning probe X-ray microscopy data. NanobeamNN learns lattice strain and rotation angles from simulated diffraction of a focused X-ray nanobeam by an epitaxial thin film and can directly make reasonable predictions on experimental data without the need for additional fine-tuning. We demonstrate that this approach represents a significant advancement in computational speed over conventional methods, as well as a potential improvement in accuracy over the current standard.

Luo, Aileen [Cornell Univ., Ithaca, NY (United Sta↗
DOE OSTI2020

Quantitative temporally and spatially resolved X-ray fluorescence microprobe characterization of the manganese dissolution-deposition mechanism in aqueous Zn/α-MnO 2 batteries

Rechargeable aqueous Zn/α-MnO 2 batteries are a possible alternative to lithium ion batteries for scalable stationary energy storage applications due to their low cost, safety and environmentally benign components. A critical need for advancement of this battery system is a full understanding of the electrochemical reaction mechanisms, which remain unclear. In this report, operando , spatiotemporal resolved synchrotron X-ray fluorescence mapping measurements on a custom aqueous Zn/α-MnO 2 cell provided direct evidence of a Mn dissolution-deposition faradaic mechanism that governs the electrochemistry. Simultaneous visualization and quantification of the Mn distribution in the electrolyte revealed the formation of aqueous Mn species during discharge and depletion on charge. The findings are supported by ex situ transmission electron microscopy (TEM), X-ray diffraction, Mn K-edge X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) measurements. The elucidated mechanism is fundamentally different from the previously proposed Zn 2+ insertion or conversion reactions. These findings provide a foundation for developing dissolution- deposition chemistries suitable for scalable stationary energy storage with aqueous electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2024

Observation of Skewed Electromagnetic Wakefields in an Asymmetric Structure Driven by Flat Electron Bunches

Relativistic charged -particle beams that generate intense longitudinal fields in accelerating structures also inherently couple to transverse modes. The effects of this coupling may lead to beam breakup instability and thus must be countered to preserve beam quality in applications such as linear colliders. Beams with highly asymmetric transverse sizes (flat beams) have been shown to suppress the initial instability in slab -symmetric structures. However, as the coupling to transverse modes remains, this solution serves only to delay instability. In order to understand the hazards of transverse coupling in such a case, we describe here an experiment characterizing the transverse effects on a flat beam, traversing near a planar dielectric lined structure. Further, the measurements reveal the emergence of a previously unobserved skew-quadrupolelike interaction when the beam is canted transversely, which is not present when the flat beam travels parallel to the dielectric surface. We deploy a multipole field fitting algorithm to reconstruct the projected transverse wakefields from the data. We generate the effective kick vector map using a simple two -particle theoretical model, with particle -in -cell simulations used to provide further insight for realistic particle distributions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Modeling Present and Future Permafrost Distribution at Seward Peninsula, Alaska: Modeling Archive

This dataset contains results from two GIPL runs for RCP4.5 and RCP8.5 across the Seward Peninsula. The model was run on 500 m by 500 m resolution for the period 1901-2100. Meteo variables include forcing air temperature and precipitation as well as modeled maxim and average snow height. This dataset also includes ground temperature at 10 different depths for every grid cell, active layer depth and talik thickness. Auxillary variables include ecotype map and projected latitude and longitude. Ground temperature borehole data that is used for model calibration and validation of GIPL2 for Seward Peninsula 500 m resolution model runs for 1901-2100 time period. Dataset also includes calibrated model parameters for future use. The main purpose of this dataset is the reproducibility of research. Data were produced for regional permafrost distribution assessment for present and future, in addition, model parameters can be used for future model runs on adjacent territories. This dataset contains *.pdf, *.txt, *.csv, and *.nc. files. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Imaging Light‐Induced Migration of Dislocations in Halide Perovskites with 3D Nanoscale Strain Mapping

Abstract In recent years, halide perovskite materials have been used to make high‐performance solar cells and light‐emitting devices. However, material defects still limit device performance and stability. Here, synchrotron‐based Bragg coherent diffraction imaging is used to visualize nanoscale strain fields, such as those local to defects, in halide perovskite microcrystals. Significant strain heterogeneity within MAPbBr 3 (MA = CH 3 NH 3 + ) crystals is found in spite of their high optoelectronic quality, and both 〈100〉 and 〈110〉 edge dislocations are identified through analysis of their local strain fields. By imaging these defects and strain fields in situ under continuous illumination, dramatic light‐induced dislocation migration across hundreds of nanometers is uncovered. Further, by selectively studying crystals that are damaged by the X‐ray beam, large dislocation densities and increased nanoscale strains are correlated with material degradation and substantially altered optoelectronic properties assessed using photoluminescence microscopy measurements. These results demonstrate the dynamic nature of extended defects and strain in halide perovskites, which will have important consequences for device performance and operational stability.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Deep-ultraviolet ptychographic pocket-scope (DART): mesoscale lensless molecular imaging with label-free spectroscopic contrast

The mesoscale characterization of biological specimens has traditionally required compromises between resolution, field-of-view, depth-of-field, and molecular specificity, with most approaches relying on external labels. Here we present the Deep-ultrAviolet ptychogRaphic pockeT-scope (DART), a handheld platform that transforms label-free molecular imaging through intrinsic deep-ultraviolet spectroscopic contrast. By leveraging biomolecules’ natural absorption fingerprints and combining them with lensless ptychographic microscopy, DART resolves down to 308-nm linewidths across centimeter-scale areas while maintaining millimeter-scale depth-of-field. The system’s virtual error-bin methodology effectively eliminates artifacts from limited temporal coherence and other optical imperfections, enabling high-fidelity molecular imaging without lenses. Through differential spectroscopic imaging at deep-ultraviolet wavelengths, DART quantitatively maps nucleic acid and protein distributions with femtogram sensitivity, providing an intrinsic basis for explainable virtual staining. We demonstrate DART’s capabilities through imaging of tissue sections, cytopathology specimens, blood cells, and neural populations, revealing detailed molecular contrast without external labels. The combination of high-resolution molecular mapping and broad mesoscale imaging in a portable platform opens new possibilities from rapid clinical diagnostics, tissue analysis, to biological characterization in space exploration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Nanoscale Superconducting States in the Fe-Based Filamentary Superconductor of Pr-Doped CaFe 2 As 2

The low-temperature scanning tunneling microscope and spectroscopy (STM/STS) are used to visualize superconducting states in the cleaved single crystal of 9% praseodymium-doped CaFe 2 As 2 (Pr-Ca122) with Tc ≈ 30 K. The spectroscopy shows strong spatial variations in the density of states (DOS), and the superconducting map constructed from spectroscopy discloses a localized superconducting phase, as small as a single unit cell. The comparison of the spectra taken at 4.2 K and 22 K (below vs. close to the bulk superconducting transition temperature) from the exact same area confirms the superconducting behavior. Nanoscale superconducting states have been found near Pr dopants, which can be identified using dI/dV conductance maps at +300 mV. There is no correlation of the local superconductivity to the surface reconstruction domain and surface defects, which reflects its intrinsic bulk behavior. We, therefore, suggest that the local strain of Pr dopants is competing with defects induced local magnetic moments; this competition is responsible for the local superconducting states observed in this Fe-based filamentary superconductor.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Exploring cycling induced crystallographic change in NMC with X-ray diffraction computed tomography

This study presents the application of X-ray diffraction computed tomography for the first time to analyze the crystal dimensions of LiNi 0.33 Mn 0.33 Co 0.33 O 2 electrodes cycled to 4.2 and 4.7 V in full cells with graphite as negative electrodes at 1 μm spatial resolution to determine the change in unit cell dimensions as a result of electrochemical cycling. The nature of the technique permits the spatial localization of the diffraction information in 3D and mapping of heterogeneities from the electrode to the particle level. An overall decrease of 0.4% and 0.6% was observed for the unit cell volume after 100 cycles for the electrodes cycled to 4.2 and 4.7 V. Additionally, focused ion beam-scanning electron microscope cross-sections indicate extensive particle cracking as a function of upper cut-off voltage, further confirming that severe cycling stresses exacerbate degradation. Finally, the technique facilitates the detection of parts of the electrode that have inhomogeneous lattice parameters that deviate from the bulk of the sample, further highlighting the effectiveness of the technique as a diagnostic tool, bridging the gap between crystal structure and electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2026

Improving protonic ceramic electrochemical cell performance via a dual-phase reaction-sintered bilayer electrolyte

Protonic ceramic electrochemical cells (PCCs) are promising energy conversion devices, but their fabrication remains challenging. In particular, the typical electrolytes for PCCs such as BaCe 0.7 Zr 0.1 Y 0.1 Yb 0.1 O 3−δ (7111) and BaCe 0.4 Zr 0.4 Y 0.1 Yb 0.1 O 3−δ (4411) suffer from intrinsic barium evaporation issues during high-temperature sintering. This tendency towards barium loss, combined with their highly refractory nature, leads to a tradeoff between sinterability and chemical stability. To address this tradeoff, we propose a bilayer electrolyte combining layers of 4411 and 7111 materials that is designed to enhance sinterability and conductivity through dual-phase reactive sintering. Our findings demonstrate that the bilayer structure exhibits shrinkage behavior closely matched to that of the fuel electrode substrate, with a higher shrinkage compared to a single-layer 4411 electrolyte. Utilizing this bilayer electrolyte structure, our PCCs achieve a peak power density of 637 mW∙cm −2 in fuel-cell mode and a current density of 1060 mA∙cm −2 at 1.3 V in electrolysis mode at 600 °C. Our PCCs demonstrate high Faradaic efficiency of 83% at 1.3 V and 500 °C. Hybrid distribution of relaxation times (DRT) polarization mapping further reveals that the bilayer structure reduces Ohmic and polarization resistance in both fuel-cell and electrolysis modes.

ceramic processing↗
DOE OSTI2023

Field studies of PERC and Al-BSF PV module performance loss using power and I-V timeseries

We have studied the degradation of both full-sized modules and minimodules with PERC and Al-BSF cell variations in fields while considering packaging strategies. We demonstrate the implementations of data-driven tools to analyze large numbers of modules and volumes of timeseries data to obtain the performance loss and degradation pathways. This data analysis pipeline enables quantitative comparison and ranking of module variations, as well as mapping and deeper understanding of degradation mechanisms. The best performing module is a half-cell PERC, which shows a performance loss rate ( PLR ) of −0.27 ± 0.12% per annum (%/ a ) after initial losses have stabilized. Minimodule studies showed inconsistent performance rankings due to significant power loss contributions via series resistance, however, recombination losses remained stable. Overall, PERC cell variations outperform or are not distinguishable from Al-BSF cell variations.

Curran, Alan J.↗
DOE OSTI2021

Spatiotemporal distribution of chemical signatures exhibited by Myxococcus xanthus in response to metabolic conditions

Myxococcus xanthus is a common soil bacterium with a complex life cycle, which is known for production of secondary metabolites. However, little is known about the effects of nutrient availability on M. xanthus metabolite production. In this study, we utilize confocal Raman microscopy (CRM) to examine the spatiotemporal distribution of chemical signatures secreted by M. xanthus and their response to varied nutrient availability. Here, ten distinct spectral features are observed by CRM from M. xanthus grown on nutrient-rich medium. However, when M. xanthus is constrained to grow under nutrient-limited conditions, by starving it of casitone, it develops fruiting bodies, and the accompanying Raman microspectra are dramatically altered. The reduced metabolic state engendered by the absence of casitone in the medium is associated with reduced, or completely eliminated, features at 1140 cm –1 , 1560 cm –1 , and 1648 cm –1 . In their place, a feature at 1537 cm –1 is observed, this feature being tentatively assigned to a transitional phase important for cellular adaptation to varying environmental conditions. In addition, correlating principal component analysis heat maps with optical images illustrates how fruiting bodies in the center co-exist with motile cells at the colony edge. While the metabolites responsible for these Raman features are not completely identified, three M. xanthus peaks at 1004, 1151, and 1510 cm –1 are consistent with the production of lycopene. Thus, a combination of CRM imaging and PCA enables the spatial mapping of spectral signatures of secreted factors from M. xanthus and their correlation with metabolic conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Additive manufacturing of ceramic materials for energy applications: Road map and opportunities

Among engineering materials, ceramics are indispensable in energy applications such as batteries, capacitors, solar cells, smart glass, fuel cells and electrolyzers, nuclear power plants, thermoelectrics, thermoionics, carbon capture and storage, control of harmful emission from combustion engines, piezoelectrics, turbines and heat exchangers, among others. Advances in additive manufacturing (AM) offer new opportunities to fabricate these devices in geometries unachievable previously and may provide higher efficiencies and performance, all at lower costs. This article reviews the state of the art in ceramic materials for various energy applications. The focus of the review is on material selections, processing, and opportunities for AM technologies in energy related ceramic materials manufacturing. The aim of the article is to provide a roadmap for stakeholders such as industry, academia and funding agencies on research and development in additive manufacturing of ceramic materials toward more efficient, cost-effective, and reliable energy systems.

36 MATERIALS SCIENCE↗