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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impact of the Electronic Properties of Chalcogenide Ligands in their Complexation with Uranyl Nitrate Complexes

The idea of covalency being directly correlated with selectivity in f-element separations has gained attention over the years. However, “covalency” as a concept is still under debate as it is not an experimental nor quantum mechanical observable. Regardless, covalency along with ionicity are still the main concepts used to explain the nature of the chemical bond of coordination complexes. Another concept that has gained the attention in the separations community is the hard-soft acid-base (HSAB) theory, which favors soft-donor ligands having the potential to increase selectivity for actinides (An) over the lanthanides (Ln) due to their ability to engage more effectively f-electrons in covalent interactions. However, it has been shown that while using softer donor ligands in fact increased orbital mixing and covalency with the actinides, it compromises the strength of the interaction owing to a decrease in the metal-ligand electrostatic interactions.1 Herein, we study the electronic structure of different types of chalcogenide ligands (LE, E = O, S, Se), their interaction with the uranyl ion, and their complexation free energies. Surprisingly, contrary to the expected order of covalency, i.e. An–LSe > An–LS > An–LO, our results suggest that the degree of covalency and associated complexation free energies depend on the nature of the coordinating moiety rather than solely on the directly coordinated atom. 1) Sadhu, Biswajit, and Michael Dolg. Enhancing actinide (III) over lanthanide (III) selectivity through hard-by-soft donor substitution: exploitation and implication of near-degeneracy-driven covalency. Inorganic Chemistry, 2019, 58, 9738 – 9748.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Direct Study of Changes in Catalyst Structure-Kinetic Properties During Redox Transitions

The Temporal Analysis of Products (TAP) pulse response methodology is a transient technique that provides the time resolution needed to deconvolve reaction steps from the complex networks typical in industrial catalytic processes. Traditionally, TAP measurements observe gas phase dynamics at the reactor exit but lack direct measurements of changes in the catalyst itself. Recently, a new operando technique was developed that couples gas phase transients to dynamic changes in metal centers with the precise TAP methodology for nanomole titration. Using an industrial CrOx/Al2O3 catalyst used for propane dehydrogenation, we demonstrate the capabilities of this unique device to reveal key catalytic processes: 1) total propane oxidation not associated with chromia centers, 2) reduction of Cr6+ to Cr3+ correlated with selective product formation, and 3) subsequent carbon accumulation. By utilizing incremental pulsing in a diffusion-only transport regime, the spectrokinetic device allows us to resolve detailed changes in catalyst structure, composition, and kinetic function that are otherwise indistinguishable in conventional operando devices. The unification of the TAP methodology with time-resolved spectroscopic measurements offers new and unique insights into the complex kinetic phenomena regulated by solid catalyst surfaces.

03 - NATURAL GAS↗
DOE OSTI2024

Dynamical correlations leading to site and orbital selective Mott insulator transition in hydrogen doped SmNiO 3

Electron doping induces metal -to -insulator transition (MIT) in SmNiO 3 as realized by experiments. While earlier density functional theory (DFT) studies with static correlations fell short of explaining the recent MIT observations at lower hydrogen concentrations, we present a comprehensive computational investigation employing an advanced approach. We combine DFT with dynamical mean field theory (DFT + DMFT) to efficiently analyze the insulating behavior of hydrogen -doped SmNiO 3 . In contrast to previous theoretical works, our calculations predict an insulator transition occurring at a reduced doping level of H:Ni = 0.5:1. Specifically, while the DFT + U method reveals a gap opening between p-to-d orbitals, the DMFT approach highlights a gap opening between d-to-d orbitals. Our findings uncover a selective Mott transition in site and orbital characteristics, with the Ni ions proximate to the doped hydrogen exhibiting Mott -like traits. Notably, DMFT calculations highlight a pronounced dependence on Hund's parameter J, implying the presence of Hundness in the Mott insulator. Finally, this study underscores the necessity of accounting for dynamical correlations to accurately describe the electronic structure of strongly correlated electron-doped rare-earth nickelates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Impact of structural distortions on the correlated electronic structure of orbital-selective Mott insulating Na 3 ⁢Co 2 ⁢SbO 6 under strain

Na 3 Co 2 SbO 6 is a promising candidate to realize the Kitaev spin liquid phase since the large Kitaev spin exchange interaction is tunable via the change in electronic structure, such as the trigonal crystal field splitting (Δ TCF ). Here, in this study, we show that the uncorrelated electronic structure of Na 3 Co 2 SbO 6 is rather insensitive to the strain effect due to the low crystal symmetry accompanied by oxygen displacements and the presence of Sb s orbitals. Using density functional theory plus dynamical mean field theory, we find that the correlated electronic structure of Na 3 Co 2 SbO 6 is an orbital-selective Mott insulating state where the trigonal a 1g orbital is insulating due to the nearly full occupation, while other d orbitals behave as typical Mott insulators, resulting in the effective tunability of Δ TCF under the strain effect. The sign change of Δ TCF can occur as the in-plane tensile strain is applied, and the Kitaev spin liquid phase could possibly be realized due to the strongly suppressed Δ TCF under tensile strain. Our results show that the local Co-site symmetry and dynamical correlation effects will play an important role in engineering the novel magnetic phase in this and related materials.

Nguyen, Nam [Univ. of Illinois, Chicago, IL (Unite↗
DOE OSTI2022

Porous Organic Cages CC3 and CC2 as Adsorbents for the Separation of Carbon Dioxide from Nitrogen and Hydrogen

The selective capture of carbon dioxide over nitrogen and hydrogen is of great industrial interest in flue gas and hydrogen purification respectively. Microporous adsorbents are highly suitable materials to preferentially adsorb gases. Here, in particular, Porous organic cages (POCs) with tunable hierarchically ordered micropores, high surface area, and thermodynamic affinity for CO 2 make them appealing candidates for these applications. Herein, we demonstrate that two prototypical POCs denoted as CC3, and CC2 with limiting pore aperture of 3.6 Å can selectively separate CO 2 from N 2 , and H 2 . For CC3 adsorption selectivities as high as ~ 8 and ~20 for CO 2 /N 2 and CO 2 /H 2 respectively were observed. For CC2 adsorption selectivities as high as ~ 9 and ~35 for CO 2 /N 2 and CO 2 /H 2 respectively were observed. Interestingly, the adsorption selectivity of the studied gases correlated linearly with polarizability selectivity.

Carbon Dioxide↗
DOE OSTI2020

SAM Code Validation on Frictional Pressure Drop through Pebble Beds

The System Analysis Module (SAM) is currently under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for safety analyses of advanced non-light water reactors. This report presents a recent effort to validate the capability of SAM to predict the frictional pressure drop through pebble beds. Selected experimental data were used for code validation, including data from test facilities at Texas A&M University, Missouri University of Science and Technology, and North-West University of South Africa. SAM implements three empirical correlations to predict frictional pressure drop: the classical Ergun correlation; the KTA correlation, which is widely used in high-temperature gas-cooled reactor applications; and the Eisfeld and Schnitzlein correlation, which explicitly considers wall effect. Code validation was performed using all three correlations. For all selected experimental data, the KTA correlation shows the best performance and agrees very well with experimental measurement; the Eisfeld and Schnitzlein correlation, explicitly considering wall effects, shows acceptable accuracy, while there is no evidence that it is better than the KTA correlation; the Ergun correlation, however, over-predicts frictional pressure drop for most selected data points.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗
DOE OSTI2026

Emergent surface resonance from charge density wave symmetry breaking in TiSe 2

Surface confined electronic states provide a fertile ground for discovering emergent phenomena that have no counterpart in the bulk, offering new routes to manipulate correlations, symmetry breaking, and dimensionality at the atomic scale. Here, in this study, we show that charge density wave (CDW) symmetry breaking can yield surface states in 1⁢T−TiSe 2 . Micro–angle-resolved photoemission spectroscopy (µ-ARPES) resolves a sharp, two-dimensional surface resonant state (SRS) that emerges within the CDW reconstructed low energy spectrum. The SRS exhibits notable temperature dependence and its spectral weight collapses around ∼ 160 K, while CDW transition temperature 𝑇 CDW is commonly reported as ≈ 202 K. Slab DFT + 𝑈 calculations reproduce a surface localized resonance when CDW folding brings valence and conduction states into near degeneracy, suggesting a correlation tuned, surface selective origin. These results point to a form of correlation-tuned surface resonance in a layered CDW compound and suggest a framework for engineering low-dimensional quantum states in van der Waals materials via symmetry breaking and electronic structure tuning.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The effect of selection – a tale of cluster mass measurement bias induced by correlation and projection

ABSTRACT Cosmology analyses using galaxy clusters by the Dark Energy Survey have recently uncovered an issue of a previously unknown selection effect affecting weak-lensing mass estimates. In this letter, we use the Illustris-TNG simulation to demonstrate that selecting on galaxy counts induces a selection effect because of projection and correlation between different observables. We compute the weak-lensing-like projected mass estimations of dark matter haloes and examine their projected subhalo counts. In the two-dimensional (2D) projected space, haloes that are measured as more massive than truth have higher subhalo counts. Thus, projection along the line of sight creates cluster observables that are correlated with cluster mass measurement deviations, which in turn creates a mass measurement bias when the clusters are selected by this correlated observable. We demonstrate that the bias is predicted in a forward model using the observable-mass measurement correlation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Dirhodium complexes as electrocatalysts for CO 2 reduction to HCOOH: role of steric hindrance on selectivity

A series of Rh 2 (II,II) complexes were shown to electrocatalytically reduce CO 2 to HCOOH. Electrochemical and spectroelectrochemical studies reveal a correlation between catalytic selectivity and efficiency with the steric bulk at the axial sites afforded by the bridging ligands. Mechanistic studies point to the presence of a Rh 2 (II,I)–H hydride as a key intermediate in the catalytic cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Electronic Origin of T c in Bulk and Monolayer FeSe

FeSe is classed as a Hund’s metal, with a multiplicity of d bands near the Fermi level. Correlations in Hund’s metals mostly originate from the exchange parameter J, which can drive a strong orbital selectivity in the correlations. The Fe-chalcogens are the most strongly correlated of the Fe-based superconductors, with d xy the most correlated orbital. Yet little is understood whether and how such correlations directly affect the superconducting instability in Hund’s systems. By applying a recently developed ab initio theory, we show explicitly the connections between correlations in d xy and the superconducting critical temperature T c . Starting from the ab initio results as a reference, we consider various kinds of excursions in parameter space around the reference to determine what controls T c . We show small excursions in J can cause colossal changes in T c . Additionally we consider changes in hopping by varying the Fe-Se bond length in bulk, in the free standing monolayer M-FeSe, and M-FeSe on a SrTiO 3 substrate (M-FeSe/STO). The twin conditions of proximity of the dxy state to the Fermi energy, and the strength of J emerge as the primary criteria for incoherent spectral response and enhanced single- and two-particle scattering that in turn controls T c . Using c-RPA, we show further that FeSe in monolayer form (M-FeSe) provides a natural mechanism to enhance J. We explain why M-FeSe/STO has a high T c , whereas M-FeSe in isolation should not. Our study opens a paradigm for a unified understanding what controls Tc in bulk, layers, and interfaces of Hund’s metals by hole pocket and electron screening cloud engineering.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2010

Herschel-ATLAS: The Angular Correlation Function of Submillimetre Galaxies at High and Low Redshift

We present measurements of the angular correlation function of galaxies selected from the first field of the H-ATLAS survey. Careful removal of the background from galactic cirrus is essential, and currently dominates the uncertainty in our measurements. For our 250 micrometer-selected sample we detect no significant clustering, consistent with the expectation that the 250 pm-selected sources are mostly normal galaxies at z < or equal to 1. For our 350 micrometer and 500 micrometer-selected samples we detect relatively strong clustering with correlation amplitudes A of 0.2 and 1.2 at 1', but with relatively large uncertainties. For samples which preferentially select high redshift galaxies at z approx. 2-3 we detect significant strong clustering, leading to an estimate of r(0) approx. 7-11/h Mpc. The slope of our clustering measurements is very steep. delta approx. 2. The measurements are consistent with the idea that sub-mm sources consist of a low redshift population of normal galaxies and a high redshift population of highly clustered star-bursting galaxies.

Maddox, S. J.↗
NASA NTRS2022

Landslide Likelihood Prediction using Machine Learning Algorithms

The supply of electricity via power plants is criticalto the operation of many critical infrastructure systems in mod-ern society. Natural hazards can disrupt the power supply, causepower outages that can halt economic growth, and impede emer-gency response until power is restored. The proposed work aimsto predict the landslides likelihood in these critical infrastructurelocations in the Northeastern USA using integrated databases ofexplanatory variables and machine learning algorithms. First,data related to landslides are obtained and merged, includingtopographic, soil moisture, and precipitation-related data. Fiveregression algorithms, namely: Random Forest, Extreme Gradi-ent Boosting (XGBoost), K-Nearest Neighbor regression (KNN),Linear Support Vector Regressor (SVR), and Linear regression,are utilized to predict the landslide probability and evaluatedon the dataset. The accuracy of the models is assessed by usingstatistical metrics such as mean absolute error (MAE), meansquared error (MSE), and root mean squared error (RMSE).The study results show that Random Forest outperformed othermodels with the mutual information feature selection method.It achieved an MSE of 0.0011 with mutual information-basedfeature selection and an MSE of 0.00157 without feature selection.KNN regressor outperformed the other models with an MSEof 0.00139 with correlation-based information selection. Theproposed landslide identification model with Random Forestalgorithm shows outstanding robustness and great potential intackling the landslide likelihood prediction by employing MLalgorithms.

Vasundhara Acharya↗
DOE OSTI2025

Observation of Orbital-Selective Dual Modulations in an Anisotropic Antiferromagnetic Kagome Metal TbTi 3 ⁢Bi 4

Orbital selectivity is pivotal in dictating the phase diagrams of multiorbital systems, with prominent examples including the orbital-selective Mott phase and superconductivity. The intercalation of anisotropic layers represents an effective method for enhancing orbital selectivity and thereby shaping the low-energy physics of multiorbital systems. Despite its potential, related experimental studies, especially those elucidating the correlation between orbital selectivity and magnetism, remain limited. In this work, we systematically examine the interplay between orbital selectivity and magnetism in the newly discovered anisotropic kagome TbTi 3 ⁢Bi 4 single crystal, and report the coexistence of orbital-selective dual-band modulations (𝑞 1 ∼ 1/3⁢𝑎*, 𝑞 2 ∼ 0.28⁢𝑏*) within the antiferromagnetic (AFM) state. By combining soft x-ray and vacuum ultraviolet angle-resolved photoemission spectroscopy measurements, neutron powder diffraction, scanning tunneling microscopy, and density-functional-theory calculations, we identify these dual-band reconstructions as manifestations of the AFM order driven by a (approximately 1/3, 0.28, 0) nesting instability of the intercalated Tb 5⁢𝑑 𝑥⁢𝑧 orbitals. These orbital-selective modulations induce unusual momentum-dependent band folding and lead to the emergence of Dirac cones only at the $\bar{M}$ 1 point, signaling a topological phase transition in the AFM state. Importantly, the discovery of orbital-selective (approximately 1/3, 0.28, 0) AFM order offers crucial insights into the mechanism underlying the fractional magnetization plateau in this kagome AFM metal. Our findings not only underscore the essential role of both conducting and localized electrons in determining the magnetic orders of Ln⁢Ti 3 ⁢Bi 4 (Ln = lanthanide) kagome metals but also offer a pathway for manipulating magnetism through selective control of anisotropic electronic structures.

Zhang, Renjie [Shanghai Jiao Tong University (Chin↗
NASA NTRS1983

A correlation analysis of percent canopy closure versus TMS spectral response for selected forest sites in the San Juan National Forest, Colorado

The correlation of canopy closure with the signal response of individual thematic mapper simulator (TMS) bands for selected forest sites in the San Juan National Forest, Colorado was investigated. Ground truth consisted of a photointerpreted determination of percent canopy closure of 0 to 100 percent for 32 sites. The sites selected were situated on plateaus at an elevation of approximately 3 km with slope or = 10 percent. The predominant tree species were ponderosa pine and aspen. The mean TMS response per band per site was calculated from data acquired by aircraft during mid-September, 1981. A correlation analysis of TMS response vs. canopy closure resulted in the following correlation coefficients for bands 1 through 7, respectively: -0.757, -0.663, -0.666, -0.088, -0.797, -0.763. Two model regressions were applied to the TMS data set to create a map of predicted percent forest canopy closure for the study area. Results indicated percent predictive accuracies of 71, 74, and 57 for percent canopy closure classes of 0-25, 25-75, and 75-100, respectively.

Butera, M. K.↗
DOE OSTI2026

Hund's coupling governed orbital-selective superconductivity in Ba 1−𝑥 ⁢K 𝑥⁢ Fe 2 ⁢As 2

Understanding how strong electronic correlations shape superconductivity remains a central challenge in quantum materials. In multiorbital systems, correlations driven by Hund's coupling can differentiate the behavior of individual orbitals, producing the so-called Hund's metal state. How such orbital-selectivity also governs superconducting pairing, however, has remained largely unexplored experimentally. Here, in this study, we use high-resolution angle-resolved photoemission spectroscopy to systematically map the superconducting gap structure across the phase diagram of the representative iron-based superconductor Ba 1−x K x Fe 2 As 2 . We find that superconductivity evolves in a strongly orbital-dependent manner: the gap associated with the d xy orbital collapses beyond optimal doping while pairing on the d xz /d yz orbitals persists. This behavior mirrors the orbital-selective correlations observed in the normal state and reveals a direct connection between Hund's metal physics and the superconducting pairing landscape. Our results demonstrate that superconducting gaps themselves can serve as a sensitive probe of orbital-dependent correlations and suggest that Hund's coupling plays a central role in shaping pairing in multiorbital superconductors.

Corbae, Elena [SLAC National Accelerator Laborator↗