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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Atomic‐Scale Surface Imaging of Bulk Epitaxial CsPbBr 3 Perovskite Single Crystals on Mica Using Light Assisted Scanning Tunneling Microscopy at Low‐Temperature (80 K)

Epitaxial single-crystalline CsPbBr 3 perovskite films on mica, prepared ex situ, are explored using a low-temperature scanning tunneling microscope (STM) by probing the unoccupied electronic states of their surface in ultra-high vacuum (UHV) at 80 K. Light-assisted STM measurements under a broadband illumination with visible light were employed to enhance and stabilize surface conductivity. STM imaging across the surface of macroscopic bulk CsPbBr 3 films reveals large flat terraces characterized by a specific type of surface reconstruction, consisting of parallel rows of U-shaped atomic nanostructures. These structures are spaced by 12 Å and exhibit an internal feature size of 5.1 Å. Density functional theory (DFT) calculations reproduce the experimental observations and reveal a competition between different orthorhombic CsPbBr 3 (110) surface reconstructions: a Cs-rich structure, identified as the most energetically stable, and three alternative Pb–Br-rich reconstructions, which are slightly higher in energy yet remain consistent with the STM data. Additional analyses that explicitly account for the mica substrate exclude the cubic CsPbBr 3 phase and other orthorhombic surface orientations, while showing that variations in the mica surface termination do not alter the preferred CsPbBr 3 (110) reconstruction. In conclusion, this combined approach thereby confirms our assignment and resolves previous STM interpretations of CsPbBr 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Microscopic scattering approach to in-gap states: Cr adatoms on superconducting 𝛽−Bi 2 ⁢Pd

We develop a microscopic scattering formalism to describe Yu-Shiba-Rusinov (YSR) states due to a single Cr adatom on the Bi-terminated surface of 𝛽−Bi 2 ⁢Pd, by combining ab initio Wannier functions with a real-space Green's function approach in the Bogoliubov–de Gennes formalism. Our framework reproduces key scanning tunneling spectroscopy features, including a single particle-hole asymmetric YSR peak and isotropic 𝑑⁢𝐼/𝑑⁢𝑉 maps around the impurity. Decomposing the YSR states reveals contributions from four nearly degenerate 𝐶 4⁢𝑣 representations, with energy broadening masking their individual signatures. Spin-orbit coupling induces partial spin polarization, while the spatial asymmetry between particle and hole components arises from Cr 𝑑−Bi 𝑝 hybridization. These results highlight the importance of realistic band structures and microscopic modeling for interpreting STM data and provide a foundation for studying impurity chains hosting topological excitations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2003

Three-dimensional visual guidance improves the accuracy of calculating right ventricular volume with two-dimensional echocardiography

Three-dimensional guidance programs have been shown to increase the reproducibility of 2-dimensional (2D) left ventricular volume calculations, but these systems have not been tested in 2D measurements of the right ventricle. Using magnetic fields to identify the probe location, we developed a new 3-dimensional guidance system that displays the line of intersection, the plane of intersection, and the numeric angle of intersection between the current image plane and previously saved scout views. When used by both an experienced and an inexperienced sonographer, this guidance system increases the accuracy of the 2D right ventricular volume measurements using a monoplane pyramidal model. Furthermore, a reconstruction of the right ventricle, with a computed volume similar to the calculated 2D volume, can be displayed quickly by tracing a few anatomic structures on 2D scans.

Non-NASA Center↗
DOE OSTI2021

Nanoscale properties of lead halide perovskites by scanning tunneling microscopy

Since the introduction of lead halide perovskites, tremendous progress has been made regarding their stability, reproducibility and durability. However, one of the issues that remains is related to the interfacial atomic structure arrangement and structure-property relationship under optical and electrical stimuli. In this critical review, we highlight the recent progress using scanning tunneling microscopy (STM) to understand the nanoscale properties and dynamic processes occurring in these halide perovskite materials. STM is known to be a very challenging technique, which is reflected by the low number of relevant publications in the last years. These initial reports mirror the unique potential of STM to give Ångstrom-scale insight into the (opto)-electronic properties, morphology and underlying electronic structure and provide a path toward harnessing the full potential of these materials. However, care must be taken to understand the effects of the perturbations caused by STM and tailor the measurement conditions accordingly.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Satellite-Dominated Sulfur L 2,3 X-ray Emission of Alkaline Earth Metal Sulfides

The sulfur L 2,3 X-ray emission spectra of the alkaline earth metal sulfides BeS, MgS, CaS, SrS, and BaS are investigated and compared with spectra calculations based on density functional theory. Very distinct spectral shapes are found for the different compounds. With decreasing electronegativity of the cation, that is, increasing ionic bonding character, the upper valence band width and its relative spectral intensity decrease. These general trends are qualitatively reproduced by the spectra calculations, which give quite an accurate description of the spectral shapes in the upper valence band region. On the low energy side of the sulfur 3s → 2p transition dominating the spectra, we find strong satellites caused by "semi-Auger" decays involving configuration interaction. These satellites, previously believed to be energetically forbidden for sulfur L 2,3 emission and only observed for the L 2,3 emission of Cl to Cr, increase in intensity as the bonding character becomes more ionic and dominate the spectra for SrS and BaS. The intensities, energies, and widths of the satellites vary strongly between the investigated compounds, giving a very specific spectral fingerprint that can be used for speciation analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Oxygen–Chlorine Chemisorption Scaling for Seawater Electrolysis on Transition Metals: The Role of Redox

To clarify what controls species oxidation selectivity in seawater electrolysis, density functional theory (DFT) is used to identify chemisorption enthalpy trends and scaling relations for the simplest relevant adsorbates (O, Cl, and H) on relevant surfaces of 3d transition metals, as well as Pd and Pt, in face-centered-cubic and, if different, their ground-state crystal structures. Approximations are tested for electron exchange-correlation (XC) and van der Waals interactions to assess their ability to reproduce experimental adsorption enthalpies of H and O on Pt(111). The vdW-uncorrected generalized gradient approximation to XC of Perdew, Burke, and Ernzerhof (PBE) agrees most closely with experiments. Using DFT-PBE thereafter, it is determined that the O chemisorption enthalpy on this wide range of transition-metal surfaces is proportional to the sum of first and second atomic ionization energies, akin to a Born–Haber cycle for a redox reaction, indicating that metal redox activity controls O chemisorption strength. Then it is shown that the O and Cl chemisorption enthalpies are strongly correlated, suggesting that the transition metals considered will oxidize unselectively water and Cl – . This strong correlation appears also for crystal reduction potentials of binary oxides and chlorides, indicating a fundamental challenge for future seawater electrode materials design.

08 HYDROGEN↗
DOE OSTI2020

Dynamics for El Niño-La Niña asymmetry constrain equatorial-Pacific warming pattern

The El Niño-Southern Oscillation (ENSO) results from the instability of and also modulates the strength of the tropical-Pacific cold tongue. While climate models reproduce observed ENSO amplitude relatively well, the majority still simulates its asymmetry between warm (El Niño) and cold (La Niña) phases very poorly. The causes of this major deficiency and consequences thereof are so far not well understood. Analysing both reanalyses and climate models, we here show that simulated ENSO asymmetry is largely proportional to subsurface nonlinear dynamical heating (NDH) along the equatorial Pacific thermocline. Most climate models suffer from too-weak NDH and too-weak linear dynamical ocean-atmosphere coupling. Nevertheless, a sizeable subset (about 1/3) having relatively realistic NDH shows that El Niño-likeness of the equatorial-Pacific warming pattern is linearly related to ENSO amplitude change in response to greenhouse warming. Therefore, better simulating the dynamics of ENSO asymmetry potentially reduces uncertainty in future projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Phase Identification in Synchrotron X-ray Diffraction Patterns of Ti–6Al–4V Using Computer Vision and Deep Learning

X-ray diffraction patterns contain information about the atomistic structure and microstructure (defect population) of materials, extracting detailed information from diffraction patterns is complex, demanding and relies on prior knowledge. Here, we hypothesize that deep-learning techniques can help to perform an effective and accurate analysis with high throughput rates. To demonstrate this concept, we applied a novel deep learning framework to determine the evolution of the β-phase volume fraction in a Ti–6Al–4V alloy during heat-treatment from video sequences of 2D diffraction patterns recorded in transmission and with highly monochromatic radiation in a synchrotron beamline. In particular, we studied the impact of network design on prediction reliability and computational performance. Networks of different architectures were trained using 3008 experimental 2D patterns. A well-tuned model was found to reproduce the phase fractions of another experimental data set, consisting of 1100 diffraction patterns, with a mean-square error as small as 2.6 x 10 -4 . The average prediction error of β-phase volume fraction was within 1.6 x 10 -2 (in each diffraction pattern) of the values obtained by conventional methods. Our work demonstrates that convolutional neural networks can evaluate high energy X-ray diffraction patterns with a remarkable level of reliability. Furthermore, it demonstrates the significance of network design on the reliability of predictions and computational performance. The most complex models do not necessarily result in highest accuracy and may even fail to learn from the data.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Accuracy of XAS theory for unraveling structural changes of adsorbates: CO on Ni(100)

Studying surface reactions using ultrafast optical pump and X-ray probe experiments relies on accurate calculations of X-ray spectra of adsorbates for correct identification of the spectral signatures and their dynamical evolution. We show that experimental XAS can be well reproduced for the different binding sites in a static prototype system CO/Ni(100) at a standard DFT (GGA) level of theory, using a plane-wave basis and pseudopotentials. This validates its utility in analyzing ultrafast X-ray probe experiments. The accuracy of computed relative core level binding energies is about 0.2 eV, representing a lower limit for which spectral features can be resolved with this method. We also show that the commonly used Z +1 approximation gives very good core binding energy shifts overall. However, we find a discrepancy for CO adsorbed in the hollow site, which we assign to the significantly stronger hybridization in hollow bonding than in on-top.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Easy-plane spin Hall nano-oscillators as spiking neurons for neuromorphic computing

Here we show analytically using a macrospin approximation that easy-plane spin Hall nano-oscillators excited by a spin current polarized perpendicularly to the easy plane have phase dynamics analogous to that of Josephson junctions. Similarly to Josephson junctions, they can reproduce the spiking behavior of biological neurons that is appropriate for neuromorphic computing. To take advantage of typical spin-orbit torques, we use a nanoconstriction geometry, in which the magnetostatic interaction and magnetocrystalline anisotropy are tuned to create an easy plane that includes the interface normal direction. We perform micromagnetic simulations of such oscillators realized in this geometry and show that the easy-plane spiking dynamics is preserved in this experimentally feasible architecture. Finally we simulate two elementary neural network blocks that implement operations essential for neuromorphic computing. First, we show that output spikes energies from two neurons can be summed and injected into a following layer neuron and second, we demonstrate that outputs can be multiplied by synaptic weights implemented by locally modifying the anisotropy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Data for Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process- Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process- based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data- constrained representation of the sterile triploid Miscanthus (IL clone) within the process- based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam- derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field- measured biomass. Building on the calibrated operating state, parameter- response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post- calibration GPP R2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

Carbon↗
DOE OSTI2021

Recommended reporting items for epidemic forecasting and prediction research: The EPIFORGE 2020 guidelines

Background: The importance of infectious disease epidemic forecasting and prediction research is underscored by decades of communicable disease outbreaks, including COVID-19. Unlike other fields of medical research, such as clinical trials and systematic reviews, no reporting guidelines exist for reporting epidemic forecasting and prediction research despite their utility. We therefore developed the EPIFORGE checklist, a guideline for standardized reporting of epidemic forecasting research. Methods and findings: We developed this checklist using a best-practice process for development of reporting guidelines, involving a Delphi process and broad consultation with an international panel of infectious disease modelers and model end users. The objectives of these guidelines are to improve the consistency, reproducibility, comparability, and quality of epidemic forecasting reporting. The guidelines are not designed to advise scientists on how to perform epidemic forecasting and prediction research, but rather to serve as a standard for reporting critical methodological details of such studies. Conclusions: These guidelines have been submitted to the EQUATOR network, in addition to hosting by other dedicated webpages to facilitate feedback and journal endorsement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Estimation of the radiation budget during MOSAiC based on ground-based and satellite remote sensing observations

An accurate representation of the radiation budget is essential for investigating the impact of clouds on the climate system, especially in the Arctic, an environment highly sensitive to complex and rapid environmental changes. In this study, we analyse a unique dataset of observations from the central Arctic made during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in conjunction with state-of-the-art satellite products from CERES (Clouds and the Earth's Radiant Energy System) to investigate the radiative effect of clouds and radiative closure at the surface and the top of the atmosphere (TOA). We perform a series of radiative transfer simulations using derived cloud macro- and microphysical properties as inputs to the simulations for the entire MOSAiC period, comparing our results to collocated satellite products and ice-floe observations. The radiative closure biases were generally within the instrumental uncertainty, indicating that the simulations are sufficiently accurate to reproduce the radiation budget during MOSAiC. Comparisons of the simulated radiation budget relative to CERES show similar values in the terrestrial flux but relatively large differences in the solar flux, which are attributed to a lower surface albedo and a possible underestimation of atmospheric opacity by CERES. While the simulation results were consistent with the observations, more detailed analyses reveal an overestimation of simulated cloud opacity for cases involving geometrically thick ice clouds. In the annual mean, we found that, during the MOSAiC expedition, the presence of clouds leads to a loss of 5.2 W m −2 of the atmosphere–surface system to space, while the surface gains 25.0 W m −2 and the atmosphere is cooled by 30.2 W m −2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Demonstration of the Reproducibility Challenges in the Sintering Behavior of Lithium‐Stuffed Garnets in Scaling up Synthesis

Lithium-stuffed garnets, such as Li 7 La 3 Zr 2 O 12 (LLZO), are promising candidates for next-generation solid-state batteries because of their high room-temperature ionic conductivity and chemical stability against lithium metal anodes, which are crucial for achieving higher energy density. However, realizing LLZO's potential in practical devices requires synthesis methods that can be scaled reliably to large batch sizes for manufacturing. Herein, we investigate the sintering reproducibility of LLZO synthesized at larger scales using ultrasonic spray pyrolysis, a cost-effective and scalable synthesis route. Two 100 g batches of Al-doped LLZO are prepared and their sintering behavior is examined in detail. Both Al-LLZO batches contain over 90 wt.% cubic-phase LLZO, and both batches exhibit room temperature conductivities greater than 1 × 10 −4 S cm −1 at a relative density above 0.8. However, variations in secondary phases and subtle differences in Al content lead to significant differences in densification and microstructure. These results demonstrate that LLZO's sintering behavior is highly sensitive to small changes in secondary phases and Al content, creating reproducibility challenges when moving from laboratory- to manufacturing-scale synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Heterogeneous Multilayer Nanopores via Chemically Tuned Dielectric Breakdown for Single‐Molecule Sensing

Solid-state nanopores are powerful platforms for single-molecule sensing, yet their performance is often constrained by fabrication complexity, noise, and limited control over surface properties. Here we report a direct method to fabricate heterogeneous multilayer nanopores using chemically tuned controlled dielectric breakdown (CT-CDB). We integrate hBN, MoS 2 , or graphene atop a silicon nitride membrane to form five distinct bilayer and tri-layer architectures, with bare SiN x nanopore as a control. CT-CDB achieves pore formation reproducibly through material-stacks with high efficiency, good pore size control, and strong yield, validated by various characterizations. Transferrin protein translocation experiments, supported by simulations, reveal that multilayer configurations modulate protein conformations, ionic current blockade and dwell time distributions, reflecting combined effects of membrane type, interfacial chemistry, and local electric field gradients. A supervised machine learning framework is implemented to assist identifying multilayer structure effects embedded in signal signatures, with over 96% accuracy. This work presents a modular and scalable framework for functional nanopore engineering with complex structural integration, thereby expanding the potential of 2D materials in single-molecule sensing applications.

2D materials↗
DOE OSTI2022

Application-specific optimal model weighting of global climate models: A red tide example

Global climate models (GCMs) and Earth system models (ESMs) provide many climate services with environmental relevance. The High Resolution Model Inter-comparison Project (HighResMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) provides model runs of GCMs and ESMs to address regional phenomena. Developing a parsimonious ensemble of CMIP6 requires multiple ensemble methods such as independent-model subset selection, prescreening-based subset selection, and model weighting. The work presented here focuses on application-specific optimal model weighting, with prescreening-based subset selection. As such, independent ensemble members are categorized, selected, and weighted based on their ability to reproduce physically-interpretable features of interest that are problem-specific. We discuss the strengths and caveats of optimal model weighting using a case study of red tide prediction in the Gulf of Mexico along the West Florida Shelf. Red tide is a common name of specific harmful algal blooms that occur worldwide, causing adverse socioeconomic and environmental impacts. Our results indicate the importance of prescreening-based subset selection as optimal model weighting can underplay robust ensemble members by optimizing error cancellation. Prescreening-based subset selection also provides insights about the validity of the model weights. By illustrating the caveats of using non-representative models when optimal model weighting is used, the findings and discussion of this study are pertinent to many other climate services.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stochastic generation of electrolyzer anode catalyst layers

Here, we introduce a stochastic methodology to reproduce the complex pore structure observed in commercial iridium catalyst layers. This method preserves the α pore (pores smaller than 250 nm) and β pore (pores greater than or equal to 250 nm) regions of the catalyst layer. The morphology of the generated materials was validated by comparing the pore size distributions of generated materials against those obtained from commercial materials imaged using x-ray nano computed tomography. We further demonstrate that the pore size distributions of the generated materials are statistically indistinguishable from the imaged catalyst layers, indicating that the stochastic methodology is capable of accurately reproducing catalyst layer morphology. Pore network modelling was conducted on the generated catalyst materials to simulate single-phase permeability, electrical conductivity, and ionic conductivity, and these properties were found to be within experimentally measured ranges for electrolyzer catalyst layers. Additionally, simulations were performed on the generated materials with varying ionomer and iridium catalyst loadings. As the ionomer loading is added, proton conductivity increases exponentially, which demonstrates the importance of optimizing ionomer loading, considering that these effects will be exacerbated in the hydration and temperature conditions of operating electrolyzers. The stochastic material generation method presented in this work is a powerful tool for the development of novel low loading catalyst layers, where the effect of various structural parameters on electrolyzer performance characteristics can be explored.

36 MATERIALS SCIENCE↗