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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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244 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Pinning ångström-size solid ionic channels for rare-earth element separation

High-purity rare-earth elements are essential for modern technologies, yet current solvent extraction processes are energy-intensive and environmentally harmful because of inadequate selectivity and ligand toxicity. Although combining size exclusion and binding affinity can improve lanthanide separation, the role of long-range confinement remains underexplored. Here we report lanthanide separation in aqueous systems using extremely confined manganese oxide solid ionic channels with optimized layer spacing. Different lanthanides induce distinct solid-state phase transformations in manganese oxide, creating a strong driving force for separation. Two lanthanide groups, differing by ~1.4 Å in spacing, were identified and confirmed to be stable by density functional theory. The narrower confinement of heavier Group II lanthanides improves cross-group separation by increasing the dehydration barrier for lighter Group I lanthanides without inducing strong binding. Here, we further developed a strategy to pin the confinement dimensions and enhance same-group separation, increasing enrichment factors for La–Nd and La–Pr pairs from 1.6 ± 0.1 and 1.5 ± 0.1 to 5.4 ± 0.1 and 4.2 ± 0.1, respectively.

Chemical engineering↗
DOE OSTI2024

Surface phase diagrams from nested sampling

From nested sampling, we compute the partition function and, from that, the phase diagram of gas adsorbates, including their anharmonic and configurational degrees of freedom, on flat and stepped surfaces of the Lennard-Jones solid.

Chemistry↗
DOE OSTI2026

Galaxy Size and Rotation Curve Diversity in ΛCDM with Baryons

The observed rotation curves of dwarf galaxies exhibit significant diversity at fixed halo mass, challenging galaxy formation within the cold dark matter (CDM) model. Previous cosmological galaxy formation simulations with baryonic physics fail to reproduce the full diversity of rotation curves, suggesting that there is a flaw in baryonic feedback models, observational bias, or that an alternative to CDM must be invoked. In this work, we use the Marvelous Massive Dwarf zoom-in simulations, a suite of high-resolution dwarf simulations with M 200 ∼ 10 10 –10 11 M ⊙ and M * ∼ 10 7 –10 9 M ⊙ , designed to target the mass range where the galaxy rotation curve diversity is maximized, i.e., between and 100 km s −1 . We add to this a set of low-mass galaxies from the Marvel Dwarf Zoom Volumes to extend the galaxy mass range to lower values. Our fiducial star formation and feedback models produce simulated dwarfs with a broader range of rotation curve shapes, similar to observations. These simulations both create dark matter cores via baryonic feedback, reproducing the slower-rising rotation curves, while also allowing for compact galaxies and steeply rising rotation curves. Our simulated dwarfs also reproduce the observed size–M * relation, including scatter, producing both extended and compact dwarfs for the first time in simulated field dwarfs. However, the slowly rising and high baryon mass fraction, as well as the steeply rising and low baryon mass fraction, remain missing. We explore star formation and feedback models and conclude that previous simulations may have had feedback that was too strong to produce compact dwarfs.

Cruz, Akaxia [Flatiron Institute, New York, NY (Un↗
DOE OSTI2025

A quantitative imaging framework for lithium morphology: Linking deposition uniformity to cycle stability in lithium metal batteries

Characterizing the morphology of lithium (Li) is crucial for developing long-lasting lithium metal batteries. It is well established that more uniform Li deposition correlates with better cell performance. Li morphology is often characterized through qualitative analysis of scanning electron microscopy (SEM) images; however, there are no widely accepted metrics to quantitatively describe deposition uniformity. Here, we propose a framework to quantify uniformity through SEM image analysis via the index of dispersion (ID) metric, which is defined and presented in the context of Li metal batteries. We also explore experimental impacts of sampling protocols onIDmeasurements. Our results demonstrate that theIDmetric is highly sensitive to variations in deposition uniformity, including the coexistence and uniformity of multiple morphologies, uniformity within a single morphology, and particle size distribution uniformity. Furthermore, it is demonstrated that uniformity, as measured by theID, can be related to the average potential of Li||Li symmetric cells over cycling. Higher capacity cycling leads to more pronounced changes in bothIDand average cell potential. Local minima/maxima are found consistently in bothIDand average cell potential immediately before cells short-circuit, which we suggest may indicate a collapse of the microstructure prior to failure. We put forward this framework as a more robust approach to quantify Li deposition uniformity, advancing the development of Li metal batteries that are safer and longer lasting.

Science & Technology - Other Topics↗
DOE OSTI2024

Elastic Modulus Measurement at High Temperatures for Miniature Ceramic Samples Using Laser Micro-Machining and Thermal Mechanical Analyzer

In this paper, we demonstrate a method of measuring the flexural elastic modulus of ceramics at an intermediate (~millimeter) scale at high temperatures. We used a picosecond laser to precisely cut microbeams from the location of interest in a bulk ceramic. They had a cross-section of approximately 100 μm × 300 μm and a length of ~1 cm. They were then tested in a thermal mechanical analyzer at room temperature, 500 °C, 800 °C, and 1100 °C using the four-point flexural testing method. We compared the elastic moduli of high-purity Al2O3 and AlN measured by our method with the reported values in the literature and found that the difference was less than 5% for both materials. This paper provides a new and accurate method of characterizing the high-temperature elastic modulus of miniature samples extracted from representative/selected areas of bulk materials.

Chemistry↗
DOE OSTI2026

Analysis of an irradiated uranium sample for source attribution without chemical separation using microplasma ionization and ultrahigh resolution mass spectrometry

The use of element isotope ratios has great potential in not only determining the reactor type used to produce plutonium (Pu) but also in determining the burnup and the time since irradiation. While a powerful nuclear forensic technique, determining element isotope ratios is complicated by severe isobaric interferences when performed on typical inductively coupled plasma mass spectrometers. Such analyses require extensive chemical separations prior to analysis to alleviate the inter-elemental isobars. Ultrahigh mass resolution spectrometry provides a potential alternative, greatly reducing the complexity of sample preparation and turnaround times for these critical measurements. To demonstrate the power of the approach, a sample of irradiated, depleted uranium was analyzed with the liquid sampling—atmospheric pressure glow discharge ion source coupled to an Orbitrap mass spectrometer. The Orbitrap is augmented with an external data acquisition system, Spectroswiss’s FTMS-Booster X2T, allowing collection of extended ion transients, providing higher mass resolution. In using this approach, the 150 Sm/ 149 Sm and 152 Sm/ 149 Sm isotope ratios were found to be within 20% of predicted values without any chemical separations and without mass bias corrections. In addition, the 240 Pu/ 239 Pu isotope ratio was determined, free from the 238 UH + interferences common to the ICP-MS platforms, while at the same time allowing for the determination of U isotopic signatures. While these demonstrative results are from a single sample, the advantages of the microplasma/ultrahigh mass resolution approach to intra-element isotope ratio determinations are clear.

Fuel burnup↗
DOE OSTI2024

A comparison of compact, presumably young with extended, evolved radio active galactic nuclei

Context.The triggering and evolution of active galactic nuclei (AGNs) and the interaction of the AGN with its host galaxy is an important topic in extragalactic astrophysics. Radio sources with peaked spectra (peaked spectrum sources, PSS) and compact symmetric objects (CSO) are powerful, compact, and presumably young AGNs and therefore particularly suitable to study aspects of the AGN-host connection. Aims.We use a statistical approach to investigate properties of a PSS-CSO sample that are related to host galaxies and could potentially shed light on the link between host galaxies and AGNs. The main goal is to compare the PSS-CSO sample with a matching comparison sample of extended sources (ECS) to see if the two have significant differences. Methods.We analysed composite spectra, diagnostic line diagrams, multi-band spectral energy distributions (MBSEDs), star formation (SF) indicators, morphologies, and cluster environments for a sample of 121 PSSs and CSOs for which spectra are available from the Sloan Digital Sky Survey (SDSS). The statistical results were compared with those of the ECS sample, where we generally considered the two subsamples of quasi-stellar objects (QSOs) and radio galaxies separately. The analysis is based on a large set of archival data in the spectral range from the ultraviolet to mid-infrared. Results.We find significant differences between the PSS-CSO and the ECS sample. In particular, we find that the ECS sample has a higher proportion of passive galaxies with a lower star formation activity. This applies to both sub-samples (QSOs or radio galaxies) as well as to the entire sample. The star formation rates of the PSS-CSO host galaxies with available data are typically in the range ∼0 to 5 ℳ ⊙ yr −1 , and the stellar masses are in the range 3 × 10 11 to 10 12 ℳ ⊙ . Secondly, in agreement with previous results, we find a remarkably high proportion of PSS-CSO host galaxies with merger signatures. The merger fraction of the PSS-CSO sample is 0.61 ± 0.07, which is significantly higher than that of the comparison sample (0.15 ± 0.06). We suggest that this difference can be explained by assuming that the majority of the PSSs and CSOs cannot evolve to extended radio sources and are therefore not represented in our comparison sample.

Astronomy & Astrophysics↗
DOE OSTI2024

Selective ion transport through hydrated micropores in polymer membranes

Abstract Ion-conducting polymer membranes are essential in many separation processes and electrochemical devices, including electrodialysis 1 , redox flow batteries 2 , fuel cells 3 and electrolysers 4,5 . Controlling ion transport and selectivity in these membranes largely hinges on the manipulation of pore size. Although membrane pore structures can be designed in the dry state 6 , they are redefined upon hydration owing to swelling in electrolyte solutions. Strategies to control pore hydration and a deeper understanding of pore structure evolution are vital for accurate pore size tuning. Here we report polymer membranes containing pendant groups of varying hydrophobicity, strategically positioned near charged groups to regulate their hydration capacity and pore swelling. Modulation of the hydrated micropore size (less than two nanometres) enables direct control over water and ion transport across broad length scales, as quantified by spectroscopic and computational methods. Ion selectivity improves in hydration-restrained pores created by more hydrophobic pendant groups. These highly interconnected ion transport channels, with tuned pore gate sizes, show higher ionic conductivity and orders-of-magnitude lower permeation rates of redox-active species compared with conventional membranes, enabling stable cycling of energy-dense aqueous organic redox flow batteries. This pore size tailoring approach provides a promising avenue to membranes with precisely controlled ionic and molecular transport functions.

Science & Technology - Other Topics↗
DOE OSTI2025

Electronic structure prediction of medium and high entropy alloys across composition space

We propose machine learning (ML) models to predict the electron density — the fundamental unknown of a material’s ground state — across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of descriptors and sampled compositions required for accurate prediction grows rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to the strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries while keeping descriptor-vector size nearly constant as alloy complexity increases. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

materials science↗
DOE OSTI2026

Identifying Strain Stacking Boundaries between Multiphase Domains in Atomically Thin Two-Dimensional Magnets

Stacking engineering of van der Waals materials is an important strategy to control the materials’ properties, such as electronic correlations, ferroelectricity, and layer-dependent two-dimensional magnetism. A timely testbed for the study of the latter is atomically thin chromium trihalides (CrX 3 , X = Cl, Br, I). Notably, by understanding the sliding mechanism between different stacking sequences, control of the stacking arrangement, and thus magnetic properties in CrX 3 , can be achieved. Such insight, however, is currently lacking. Here, in this study, advanced electron microscopy methods are used to identify multiple stacking sequences corresponding to different bulk phases in atomically thin CrX 3 (X = Cl and Br) down to bilayer thickness and with lateral domain sizes as small as tens of nanometers. Indications of nanometer scale transitions and interactions at the stacking boundaries are found, including a universally preferred sliding direction that is consistent with density functional theory calculations and the strain fields at lateral heterostructure boundaries. This study demonstrates the necessity to consider local stacking structures when interpreting averaged magnetic properties measured with macroscale probes. Additionally, the preferred sliding direction insight from this study provides a strategy to control stacking sequence in atomically thin CrX 3 samples during the exfoliation and sample fabrication process.

DFT calculations↗
DOE OSTI2026

October 2025 Semiannual Composite Salt Waste Processing Facility Decontaminated Salt Solution Toxicity Characteristic Leaching Procedure Results

The aqueous waste from the Salt Waste Processing Facility is sampled semiannually for transfers to the Saltstone Disposal Facility. Salt solution is treated at the Saltstone Production Facility and disposed of in the Saltstone Disposal Facility. Per request of customer, X-TTR-Z-00027, Revision 0, one Saltstone Processing Facility Decontaminated Salt Solution and Z area premix material for the October 2025 semiannual Toxicity Characteristic Leaching Procedure sample. The sample contained 60:40 (by weight) of slag and fly ash (referred to as the “Cement-Free grout sample”). Results from the technical report support Task 2: ‘Grout Leaching Analyses’ of the Task Technical Request prepared by Savannah River Mission Completion. At 51 days cured, the Saltstone sample was collected and shipped to a certified laboratory for analysis using the Toxicity Characteristic Leaching Procedure. The October 2025 Semiannual Cement-Free grout sample met 61 79.268.48 requirements for a non-hazardous waste form with respect to the Resource Conservation and Recovery Act metals and Underlying Hazardous Constituents and met the Saltstone Production Facility Waste Acceptance Criteria that was in effect at the time of the sample collection at the Salt Waste Processing Facility.

Hsieh, Madison [Savannah River National Laboratory↗
DOE OSTI2026

Dimensional Reduction for Sampled Priors and Application to Photometric Redshift Distributions

A typical Bayesian inference on the values of some parameters of interest q from some data D involves running a Markov Chain (MC) to sample from the posterior $p$($q$,$n$|$D$) $\propto$ $\mathcal{L}$($D$|$q$,$n$)$p$(q)$p$($n$), where n are some nuisance parameters with a separable prior. In some cases, the nuisance parameters are high-dimensional, and their prior p(n) is itself defined only by a set of samples that have been drawn from some other MC. The MC for the posterior will typically require evaluation of p(n) at arbitrary values of n, i.e., one needs to provide a density estimator over the full n space from the provided samples. But the high dimensionality of n hinders both the density estimation and the efficiency of the MC for the posterior. We describe a solution to this problem: a linear compression of the n space into a much lower-dimensional space u, which projects away directions in n space that cannot appreciably alter $\mathcal{L}$. The algorithm for doing so is a slight modification to principal components analysis, and is less restrictive on p(n) than other proposed solutions to this issue. We demonstrate this “mode projection” technique using the analysis of 2-point correlation functions of weak lensing fields and galaxy density in the Dark Energy Survey, where n is a binned representation of the redshift distribution n(z) of the galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ↗
DOE OSTI2026

Dark Energy Survey Year 6 results: Clustering redshifts and importance sampling of self-organized-maps 𝑛⁡(𝑧) realizations for 3 × 2 ⁢pt samples

This work is part of a series establishing the redshift framework for the 3 × 2 ⁢pt analysis of the Dark Energy Survey Year 6 (DES Y6). For DES Y6, photometric redshift distributions are estimated using self-organizing maps (SOMs), calibrated with spectroscopic and many-band photometric data. To overcome limitations from color-redshift degeneracies and incomplete spectroscopic coverage, we enhance this approach by incorporating clustering-based redshift constraints (clustering-z, or WZ) from angular cross-correlations with BOSS and eBOSS galaxies and eBOSS quasar samples. We define a WZ likelihood and apply importance sampling to a large ensemble of SOM-derived 𝑛⁡(𝑧) realizations, selecting those consistent with the clustering measurements to produce a posterior sample for each lens and source bin. The analysis uses angular scales corresponding to 1.5–5 Mpc to optimize signal-to-noise ratio while mitigating modeling uncertainties and marginalizes over redshift-dependent galaxy bias and other systematics informed by the N-body simulation CARDINAL . While a sparser spectroscopic reference sample limits WZ constraining power at 𝑧 >1.1, particularly for source bins, we demonstrate that combining SOM with WZ improves redshift accuracy and enhances the overall cosmological constraining power of DES Y6. As a result, we estimate an improvement in 𝑆 8 of approximately 10% for cosmic shear and 3 ×2⁢pt analysis, primarily due to the WZ calibration of the source samples.

Cosmological parameters↗
DOE OSTI2025

DESI 2024 II: sample definitions, characteristics, and two-point clustering statistics

We present the samples of galaxies and quasars used for DESI 2024 cosmological analyses, drawn from the DESI Data Release 1 (DR1). We describe the construction of largescale structure (LSS) catalogs from these samples, which include matched sets of synthetic reference ‘randoms’ and weights that account for variations in the observed density of the samples due to experimental design and varying instrument performance. We detail how we correct for variations in observational completeness, the input ‘target’ densities due to imaging systematics, and the ability to confidently measure redshifts from DESI spectra. We then summarize how remaining uncertainties in the corrections can be translated to systematic uncertainties for particular analyses. We describe the weights added to maximize the signalto-noise of DESI DR1 2-point clustering measurements. We detail measurement pipelines applied to the LSS catalogs that obtain 2-point clustering measurements in configuration and Fourier space. The resulting 2-point measurements depend on window functions and normalization constraints particular to each sample, and we present the corrections required to match models to the data. We compare the configuration- and Fourier-space 2-point clustering of the data samples to that recovered from simulations of DESI DR1 and find they are, generally, in statistical agreement to within 2% in the inferred real-space over-density field. The LSS catalogs, 2-point measurements, and their covariance matrices will be released publicly with DESI DR1.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Coercivity enhancement in hematite/permalloy heterostructures across the Morin transition

Interfacial effects between antiferromagnetic (AFM) and ferromagnetic (FM) materials have long been a center of magnetism studies. Aside from the exchange bias occurring at the AFM/FM interface, controlling the coercivity is another significant topic in magnetic recordings. The coercivity of FM materials is often determined through varying grain size, alloy composition, density of defects, etc., which is set during material growth and offers limited room for modification after growth. Hematite (α - Fe 2 O 3 ) is an AFM material that undergoes a temperature-controlled spin-flip transition, the so-called Morin transition. This transition gives an extra degree of freedom making hematite an intriguing component to study the exchange coupling when interfaced with an FM material. Here, in this work, changes in the magnetic properties of soft magnetic permalloy (Ni 81 Fe 19 , or Py) thin films grown on hematite were studied across the Morin transition. Surprisingly, these samples showed a remarkable change in coercivity during the Morin transition. We attribute this effect to the magnetic domain mixture of hematite during the Morin transition. Our findings present a novel method of controlling the coercivity of plain ferromagnetic thin films.

Antiferromagnet↗
DOE OSTI2026

Weak localization and universal conductance fluctuations in large-area twisted bilayer graphene

We study diffusive magnetotransport in highly 𝑝-doped large-area twisted bilayer graphene in 1∘, 7∘, 9∘, and 20∘ samples. All samples exhibit weak localization, from which we extract the phase coherence length and intervalley scattering lengths, and from that determine that dephasing is caused by electron-electron scattering and intervalley scattering is caused by point defects. We observe signatures of universal conductance fluctuations in the 9∘ sample, which has high mobility and is near the van Hove singularity. Further improvements in sample quality and applications to large-area moiré materials will open new avenues to observe quantum interference effects.

Talkington, Spenser [University of Pennsylvania]↗