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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Manipulating Na/TM Ratio‐Driven Structural Heterogeneity of O3‐NaNi 1/3 Fe 1/3 Mn 1/3 O 2 Cathode for High‐Voltage Sodium‐Ion Batteries

The stability of O3-type NaNi 1/3 Fe 1/3 Mn 1/3 O 2 under high-voltage cycling is dictated by how synthesis encodes lattice strain and redox heterogeneity. Here, in this study, the role of Na:TM stoichiometry is systematically resolved by tuning the NaOH:precursor ratio during solid-state synthesis. The stoichiometric condition (Na:TM = 1.00) yields minimized microstrain, enabling uniform O3–P3 phase evolution and homogeneous multi-metal redox with preserved octahedral symmetry. In contrast, Na-excess compositions inherit disordered intermediates and heterogeneous distortion fields that trigger abrupt multiphase transitions and promote localized charge redistribution. In situ XRD captures the divergence in phase-transition pathways, TXM resolves particle-level redox heterogeneity, and XANES corroborates a stronger and more reversible Fe redox contribution at stoichiometry, shifting to diminished Fe participation and spatially inhomogeneous redox at higher Na content. These results establish Na:TM stoichiometry as a critical synthesis parameter controlling both structural coherence and redox stability. Electrochemically, the stoichiometric composition exhibits smooth voltage profiles with minimal polarization growth and retains nearly 80% of its initial capacity after 100 cycles even at an extended 4.2 V cutoff, whereas Na-excess compositions show significantly reduced initial coulombic efficiency and rapid voltage fade. Precise stoichiometric tuning provides a scalable route to defect-suppressed O3 frameworks, enabling structurally resilient, high-voltage sodium-layered cathodes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Rapid Coal-Ash Characterization using Geophysical Methods & Machine Learning

Coal combustion products (CCP) are challenging to delineate in heterogeneous field settings. Conventional methods (test pits, coring, and laboratory analyses) are labor-intensive, slow, invasive, and provide sparse spatial coverage. This study evaluates whether rapid non-invasive geophysical screening methods—induced polarization (IP), magnetic susceptibility, and nuclear magnetic resonance (NMR) —combined with surface colorimetry (RGB_24), can discriminate CCP-soil mixtures and provide reliable estimates of CCP content. Laboratory measurements were collected on five CCP-soil mixtures (series) and modeled using (i) a linear baseline, (ii) a calibrated non-linear (power-mean) model, and (iii) a machine-learning (ML) Random Forest approach, with validation via leave-one-series-out and site-specific tests. Across the five series, individual signals—particularly IP and magnetic susceptibility—were strongly predictive of ash content but were consistently outperformed by combined models. The pooled calibrated non-linear and ML models captured the observed non-linearity and achieved high accuracy and precision, improving on linear fits. Colorimetry showed the weakest direct relationship with ash content for the tested samples but improved performance when included in multi-signal models. At pre-selected 3.5% decision threshold, calibrated and ML approaches yielded near-perfect classification (Matthews correlation coefficient ˜ 1), suggesting strong practical operability for field screening. Additionally, field-analog tests highlighted the role of endmembers—accuracy declined without access to end-member measurements but was largely recovered by collecting a minimal labeled pair for local recalibration. With end members, accuracy remained high. Globally trained models performed well on three operational unknowns; however, series-specific refits provided the most accurate predictions. Overall, these results highlight the potential of combining rapid geophysics and minimal local calibration for improved coal-ash delineation.

Peshtani, Klaudio↗
DOE OSTI2021

Using Nanofiller Assemblies to Control the Crystallization Kinetics of High-Density Polyethylene

Polyethylene-grafted nanoparticles (NPs) are organized into a variety of assemblies in a polydisperse polyethylene melt by tailoring the graft density and molecular weights of the graft chains. Under these conditions we systematically vary NP assemble state and study is consequences on crystal nucleation and growth rates. We find that the nucleation rate is suppressed below that of the unfilled polymer for good NP spatial dispersion. However, poorer dispersion, which leads to the formation of NP assemblies, can accelerate nucleation likely by providing multiple heterogenous sites due to topographical features. We find that a key parameter, the chain overcrowding in the brush, can predict these nucleation trends – in this language, the most enhanced nucleation rate is found when the grafts are the most overcrowded, and hence the least interpenetrated with the matrix chains. This result is consistent with one other literature result which utilized short crystallizable polyethylene glycol grafts in short PEO matrices. The growth kinetics were retarded for all nanocomposites, their temperature dependences were essentially equal to that for the pure polymer (in the absence of NPs) – the NPs thus do not affect secondary nucleation, indicating that the transport of the matrix to the growth front is the rate determining step. Thus, evidently the increase in matrix viscosity, or reduction in growth rates, is directly determined by the agglomeration state of the NPs. These results are consistent with past works with bare silica NPs in PEO, and with silica NPs grafted with amorphous chains in a PEO matrix, suggesting that growth kinetics in these systems apparently follow “universal” behavior. Additionally, there are initial hints that the ratio of the effective surface area of the NP clusters per unit matrix volume provides a unified description of the NP induced confinement that slows growth kinetics. Furthermore, our work thus shows that there is an evolving understanding of the role of NPs on crystallization kinetics, in particular crystal growth where trends appear to be independent of the grafts ability to crystallize.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Crystal Orientation and Defect Mapping in Electron-Beam-Sensitive Zeolites with Near-Axis Transmission Kikuchi Diffraction

Porous materials are vital in catalysis, energy conversion, and environmental remediation. Understanding structural heterogeneity in zeolites is key to linking synthesis, framework intergrowths, and catalytic performance, yet current methods for phase identification and spatial mapping lack sufficient resolution or throughput. We present a high-throughput approach using near-axis transmission Kikuchi diffraction in a scanning electron microscope, achieving high phase and spatial resolution for electron-beam-sensitive zeolites, including ZSM-5 and, for the first time, Zeolite A. Here, this method enables direct visualization of intergrowth features that critically affect catalytic and adsorption behavior, bridging the gap between ensemble-averaged X-ray diffraction and high-resolution but low-throughput transmission electron microscopy. Combining nanoscale mapping with statistical sampling is highly suited for machine-learning pipelines guiding new structure function understanding and could be extended to other beam-sensitive porous materials such as metal–organic or covalent–organic frameworks.

crystallography↗
DOE OSTI2022

Neutron diffusion calculation in heterogeneous geometry based on local/global iteration using proper orthogonal decomposition

This study newly proposes a heterogeneous core calculation method based on local/global iteration using proper orthogonal decomposition (POD). By using the singular value decomposition (SVD) and the low-rank approximation, appropriate POD bases for expanding the neutron flux can be obtained from snapshot data of the neutron flux obtained by fine mesh calculations. By projection using the POD bases, the dimension of the target equation (e.g., discretized neutron diffusion equation) can be dramatically reduced. In the proposed method, POD is effectively applied to each single assembly calculation (local calculation). Furthermore, using the local/global iteration, the effective neutron multiplication factor and the neutron flux distribution in the whole core geometry can be obtained by combining the numerical results of the local calculation for each fuel assembly and the global calculation for the whole core. As a feasibility study, the proposed method is applied to a one-dimensional heterogeneous core analysis, and the accuracy is investigated by changing the total number of POD bases. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Geology and elevation shape bacterial assembly in Antarctic endolithic communities

Ice free areas of continental Antarctica are among the coldest and driest environments on Earth, and yet, they support surprisingly diverse and highly adapted microbial communities. Endolithic growth is one of the key adaptations to such extreme environments and often represents the dominant life-form. Despite growing scientific interest, little is known of the mechanisms that influence the assembly of endolithic microbiomes across these harsh environments. Here, we used metagenomics to examine the diversity and assembly of endolithic bacterial communities across Antarctica within different rock types and over a large elevation range. While granite supported richer and more heterogeneous communities than sandstone, elevation had no apparent effect on taxonomic richness, regardless of rock type. Conversely, elevation was clearly associated with turnover in community composition, with the deterministic process of variable selection driving microbial assembly along the elevation gradient. The turnover associated with elevation was modulated by geology, whereby for a given elevation difference, turnover was consistently larger between communities inhabiting different rock types. Overall, selection imposed by elevation and geology appeared stronger than turnover related to other spatially-structured environmental drivers. Our findings indicate that at the cold-arid limit of life on Earth, geology and elevation are key determinants of endolithic bacterial heterogeneity. This also suggests that warming temperatures may threaten the persistence of such extreme-adapted organisms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Uniformity and volume-representativity of consecutive submillimetre wafers of shale for SANS and USANS investigations

(Ultra) Small Angle Neutron Scattering (SANS/USANS) is a non-destructive technique suitable for characterization of porous structures from nano- to micro-pore size (1 nm to 20 μm), which has been widely used to characterize accessible and inaccessible porosity in tight unconventional hydrocarbon reservoirs (e.g., shales). Here, in this study, SANS and USANS are used to examine the degree of nano- to micropore uniformity of the rock body on sub-millimetre to centimetre scale. This study presents a test of the hypothesis of volume representativity of pore structure information measured by SANS and USANS for shale wafers (0.22–1 mm) cut from six North American unconventional shale cores of different maturities (New Albany Shale and Marcellus Shale). Experimental reproducibility of USANS is further investigated for two wafers measured using various acquisition times. All samples show that fluctuations of the relative intensity generally decrease from the USANS Q-range (pore size from around 200 nm to 20 μm) to most of the SANS Q-range (pore size from around 5 nm to 700 nm), and peaks in the SANS large-Q region (for pores smaller than about 5 nm). There is a positive correlation between the spatial fluctuation of the relative SANS intensity and the scattering power of shales. In addition, the scattering intensity and its fluctuations is larger for the less mature shale cores. Shale is known to be highly heterogenous and the hypothesis of uniformity does not apply at sub-millimetre scale even for samples that appear homogeneous at visual inspection. This study presents an approach to minimise the variation through sample selection, data interpretation methodology and instrumental reproducibility tests. The best values of the microstructural spatial uniformity for the apparently homogeneous sections of a core (i.e., the SANS and USANS intensity variation) is less than ±10%.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

11-th order of accuracy for numerical solution of 3-D Poisson equation with irregular interfaces on unfitted Cartesian meshes

For the first time the optimal local truncation error method (OLTEM) with 125-point stencils and unfitted Cartesian meshes has been developed in the general 3-D case for the Poisson equation for heterogeneous materials with smooth irregular interfaces. The 125-point stencils equations that are similar to those for quadratic finite elements are used for OLTEM. The interface conditions for OLTEM are imposed as constraints at a small number of interface points and do not require the introduction of additional unknowns, i.e., the sparse structure of global discrete equations of OLTEM is the same for homogeneous and heterogeneous materials. The stencils coefficients of OLTEM are calculated by the minimization of the local truncation error of the stencil equations. These derivations include the use of the Poisson equation for the relationship between the different spatial derivatives. Such a procedure provides the maximum possible accuracy of the discrete equations of OLTEM. In contrast to known numerical techniques with quadratic elements and third order of accuracy on conforming and unfitted meshes, OLTEM with the 125-point stencils provides 11-th order of accuracy, i.e., an extremely large increase in accuracy by 8 orders for similar stencils. The numerical results show that OLTEM yields much more accurate results than high-order finite elements with much wider stencils. The increased numerical accuracy of OLTEM leads to an extremely large increase in computational efficiency. Additionally, a new post-processing procedure with the 125-point stencil has been developed for the calculation of the spatial derivatives of the primary function. The post-processing procedure includes the minimization of the local truncation error and the use of the Poisson equation. It is demonstrated that the use of the partial differential equation (PDE) for the 125-point stencils improves the accuracy of the spatial derivatives by 6 orders compared to post-processing without the use of PDE as in existing numerical techniques. At an accuracy of 0.1% for the spatial derivatives, OLTEM reduces the number of degrees of freedom by 900 - 4∙10 6 times compared to quadratic finite elements. The developed post-processing procedure can be easily extended to unstructured meshes and can be independently used with existing post-processing techniques (e.g., with finite elements).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

On a Unified Core Characterization Methodology to Support the Systematic Assessment of Rare Earth Elements and Critical Minerals Bearing Unconventional Carbon Ores and Sedimentary Strata

A significant gap exists in our understanding and ability to predict the spatial occurrence and extent of rare earth elements (REE) and certain critical minerals (CM) in sedimentary strata. This is largely due to a lack of existing, systematic, and well-distributed REE and CM samples and analyses in United States sedimentary basins. In addition, the type of sampling and characterization performed to date has generally lacked the resolution and approach required to constrain geologic and geographic heterogeneities typical of subsurface, mineral resources. Here, we describe a robust and systematic method for collecting core scale characterization data that can be applied to studies on the contextual and spatial attributes, the geologic history, and lithostratigraphy of sedimentary basins. The methods were developed using drilled cores from coal bearing sedimentary strata in the Powder River Basin, Wyoming (PRB). The goal of this effort is to create a unified core characterization methodology to guide systematic collection of key data to achieve a foundation of spatially and geologically constrained REEs and CMs. This guidance covers a range of measurement types and methods that are each useful either individually or in combination to support characterization and delineation of REE and CM occurrences. The methods herein, whether used in part or in full, establish a framework to guide consistent acquisition of geological, geochemical, and geospatial datasets that are key to assessing and validating REE and CM occurrences from geologic sources to support future exploration, assessment, and techno-economic related models and analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution manifold learning

Abstract Accurately identifying the local structural heterogeneity of complex, disordered amorphous materials such as amorphous silicon is crucial for accelerating technology development. However, short-range atomic ordering quantification and nanoscale spatial resolution over a large area on a-Si have remained major challenges and practically unexplored. We resolve phonon vibrational modes of a-Si at a lateral resolution of <60 nm by tip-enhanced Raman spectroscopy. To project the high dimensional TERS imaging to a two-dimensional manifold space and categorize amorphous silicon structure, we developed a multiresolution manifold learning algorithm. It allows for quantifying average Si-Si distortion angle and the strain free energy at nanoscale without a human-specified physical threshold. The multiresolution feature of the multiresolution manifold learning allows for distilling local defects of ultra-low abundance (< 0.3%), presenting a new Raman mode at finer resolution grids. This work promises a general paradigm of resolving nanoscale structural heterogeneity and updating domain knowledge for highly disordered materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Amino mapping: possibility to visualize amino-N compounds in the rhizosphere of Zea Mays L.

Abstract Understanding N uptake by plants, the N cycle, and their relationship to soil heterogeneity has generated a great deal of interest in the distribution of amino-N compounds in soil. Visualization of the spatial distribution of amino-N in soil can provide insights into the role of labile N in plant-microbial mechanisms of N acquisition and plant N uptake, but until now, it has remained technically challenging. Here, we describe a novel technique to visualize the amino-N distribution at the root-soil interface. The technique is based on time-lapse amino mapping (TLAM) using membranes saturated with the fluorogenic OPAME reagent (O-phthalaldehyde and β-mercaptoethanol). OPAME in the membrane reacts with organic compounds containing a NH 2 functional group at the membrane-soil interface, generating a fluorescent product visible under UV light and detectable by a digital camera. The TLAM amino-mapping technique was applied to visualize and quantify the concentration of amino-N compounds in the rhizosphere of maize (Zea MaysL.). A ten times greater amino-N concentration was detected in the rhizosphere compared to non-rhizosphere soil. The high content of amino-N was mainly associated with the root tips and was 3 times larger than the average amino-N content at seminal roots. The amino-N rhizosphere was 2 times broader around the root tips than around other parts of the roots. We concluded that TLAM is a promising approach for monitoring the fate of labile N in soils. However, the technique needs to be standardized for different soil types, plant species, and climate conditions to allow wider application.

Agriculture↗
DOE OSTI2022

Fatigue crack growth resistance of a mesoscale composite microstructure Haynes 282 fabricated via electron beam melting additive manufacturing

Materials synthesis via additive manufacturing gives unprecedented control over the solidified microstructure. While a number of studies have demonstrated the ability to produce spatially varying microstructures, little work exists to understand the behavior of such “composite” materials. In this work, we utilized electron beam melting to process Ni-based superalloy Haynes 282 and produce compact tension samples with a spatially varying mesoscale structure. Fatigue crack growth experiments reveal that the crack growth rate is dependent on the degree of microstructural heterogeneity. This work demonstrates that the crack growth resistance can be tailored within a component using electron beam melting additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Global droughts connected by linkages between drought hubs

Abstract Quantifying the spatial and interconnected structure of regional to continental scale droughts is one of the unsolved global hydrology problems, which is important for understanding the looming risk of mega-scale droughts and the resulting water and food scarcity and their cascading impact on the worldwide economy. Using a Complex Network analysis, this study explores the topological characteristics of global drought events based on the self-calibrated Palmer Drought Severity Index. Event Synchronization is used to measure the strength of association between the onset of droughts at different spatial locations within the time lag of 1-3 months. The network coefficients derived from the synchronization network indicate a highly heterogeneous connectivity structure underlying global drought events. Drought hotspot regions such as Southern Europe, Northeast Brazil, Australia, and Northwest USA behave as drought hubs that synchronize regionally and with other hubs at inter-continental or even inter-hemispheric scale. This observed affinity among drought hubs is equivalent to the ‘rich-club phenomenon’ in Network Theory, where ‘rich’ nodes (here, drought hubs) are tightly interconnected to form a club, implicating the possibility of simultaneous large-scale droughts over multiple continents.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Advanced multi-modal mass spectrometry imaging reveals functional differences of placental villous compartments at microscale resolution

The placenta is a complex and heterogeneous organ that links the mother and fetus, playing a crucial role in nourishing and protecting the fetus throughout pregnancy. Integrative spatial multi-omics approaches can provide a systems-level understanding of molecular changes underlying the mechanisms leading to the histological variations of the placenta during healthy pregnancy and pregnancy complications. Herein, we advance our metabolome-informed proteome imaging (MIPI) workflow to include lipidomic imaging, while also expanding the molecular coverage of metabolomic imaging by incorporating on-tissue chemical derivatization (OTCD). The improved MIPI workflow advances biomedical investigations by leveraging state-of-the-art molecular imaging technologies. Lipidome imaging identifies molecular differences between two morphologically distinct compartments of a placental villous functional unit, syncytiotrophoblast (STB) and villous core. Next, our advanced metabolome imaging maps villous functional units with enriched metabolomic activities related to steroid and lipid metabolism, outlining distinct molecular distributions across morphologically different villous compartments. Complementary proteome imaging on these villous functional units reveals a plethora of fatty acid- and steroid-related enzymes uniquely distributed in STB and villous core compartments. Integration across our advanced MIPI imaging modalities enables the reconstruction of active biological pathways of molecular synthesis and maternal-fetal signaling across morphologically distinct placental villous compartments with micrometer-scale resolution.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes

As a leading mode of sea surface temperature (SST) variability over the North Atlantic in both observations and model simulations, the Atlantic Multidecadal Oscillation (AMO) can have a substantial influence on regional and global climate. By using Low-Frequency Component Analysis, we explore the uncertainties of the resulting AMO indices and the corresponding spatial patterns derived from three observational SST datasets. We found that the known coherent spatial pattern of the AMO at the basin scale over the North Atlantic appears in two out of the three datasets. Further analysis indicates that both the warming trend and the different techniques used to construct these observed gridded SSTs contribute to the AMO’s spatial coherence over the North Atlantic, especially during periods of sparse data sampling. The SST in the Extended Reconstructed SST dataset version 5 (ERSSTv5), changes from being systematically below the other datasets during the dense sampling periods on either side of the Second World War (WWII), to systematically above the other datasets during WWII, thereby introducing an artificial 10–20-year variability that affects the AMO’s spatial coherence. This coherence in the AMO’s spatial pattern is also affected by bias adjustment in ERSSTv5 at relative cool (i.e., non-summer) seasons, and by the heterogeneous North Atlantic warming pattern. The different AMO patterns can induce the different effects of wind, surface heat fluxes, and then drive ocean circulation and its heat transport convergence, especially for some seasons. For AMO indices, both the different detrending methods and different observational data result in uncertainty for the period 1935–1950. Such SST uncertainty is important to detect the relative role of the atmosphere and ocean in shaping the AMO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Single-cell and spatial omics in plants: from cellular atlases to regulatory mechanisms

Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic studies by enabling gene expression profiling at the resolution of individual cells within and across a broad range of tissue types, revealing cellular heterogeneity that is obscured in bulk tissue transcriptomes. Over the past decade, improvements in microfluidics and library preparation have drastically increased throughput, allowing tens of thousands of cells to be assayed in a single experiment. Although initially developed in animal systems, scRNA-seq has rapidly emerged as a powerful and widely adopted approach in plant biology. Beyond transcriptomics, the integration of single-cell data with chromatin accessibility, proteomics, metabolomics, and spatial omics is enabling a system-level understanding of plant gene regulation and cellular organization. Network-based analytical frameworks further support the reconstruction of gene regulatory networks and the interpretation of complex single-cell data. In this review, we summarize the current technological landscape of plant single-cell studies, discuss key experimental and analytical challenges, and review emerging strategies for validating single-cell discoveries. We also discuss future directions in applying single-cell technologies to woody perennials plants and bioenergy-relevant crops, emphasizing their potential to accelerate the discovery of cell type-specific regulatory mechanisms underlying growth, stress resilience, and biomass production.

Li, Miaomiao [ORNL] (ORCID:0000000321326168)↗
DOE OSTI2023

HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data

Abstract Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km 2 across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems.

Science & Technology - Other Topics↗
DOE OSTI2025

Impact of grassland fire dynamics on particulate emission factors

Understanding particulate emission factors in grassland fires is critical for improving air quality assessments and refining emissions inventories. This study explores the dynamic and heterogeneous nature of fire processes and their influence on particulate emissions. Traditional emission factor inventories often rely on static values, overlooking the spatially and temporally variable dynamics of fire behavior. Through field experiments conducted at Konza Prairie Biological Station measuring emissions with uncrewed aerial vehicles, and computational modeling using HIGRAD/FIRETEC, this research highlights the dependency of emission production on localized fire dynamics, including ignition patterns, fuel properties, and atmospheric conditions. The results demonstrate a need for fire dynamic considerations to accurately capture emissions variability.

09 BIOMASS FUELS↗