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Results for “correlation energy”

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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Correlation-driven electronic reconstruction in FeTe 1−x Se x

Electronic correlation is of fundamental importance to high temperature superconductivity. While the low energy electronic states in cuprates are dominantly affected by correlation effects across the phase diagram, observation of correlation-driven changes in fermiology amongst the iron-based superconductors remains rare. Here we present experimental evidence for a correlation-driven reconstruction of the Fermi surface tuned independently by two orthogonal axes of temperature and Se/Te ratio in the iron chalcogenide family FeTe 1−x Se x . We demonstrate that this reconstruction is driven by the de-hybridization of a strongly renormalized d xy orbital with the remaining itinerant iron 3 d orbitals in the emergence of an orbital-selective Mott phase. Our observations are further supported by our theoretical calculations to be salient spectroscopic signatures of such a non-thermal evolution from a strongly correlated metallic phase into an orbital-selective Mott phase in d xy as Se concentration is reduced.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Highly-destabilized ligand field excited states of iron carbene complexes and their relation to charge transfer state lifetimes

Lifetimes of photoexcited charge transfer (CT) states in transition metal chromophores are influenced by low-lying ligand field (LF) excited states, especially for 3d metal complexes. To manipulate interactions between LF and CT states, it is important to be able to control LF excited state energies using tunable synthetic variables. In this report, we use Fe 2p3d L 3 -edge resonant inelastic X-ray scattering (RIXS) to measure LF excited state energies of three homoleptic iron chromophores coordinated by strong-field N-heterocyclic carbenes (NHCs). We investigate the effect of oxidation state and ligand scaffold on LF energies and covalency parameters. A cyclometalated bis(NHC) ligand affords both high LF excited state energies (and thus high 10 Dq) as well as high metal–ligand covalency compared to other iron complexes with very strong-field ligands. However, for the set of complexes investigated, we do not observe meaningful correlation between the LF excited state energies and the CT excited state lifetimes. These results illustrate that targeting long-lived CT excited states necessitates control of multiple molecular excited state properties, with destabilization of the LF excited state energies proving necessary, but insufficient, to control the CT excited state lifetime in Fe carbene complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Proton Number Cumulants and Correlation Functions from Hydrodynamics and the QCD Phase Diagram

We analyze the behavior of (net-)proton number cumulants in central collisions of heavy ions across a broad collision energy range by utilizing hydrodynamic simulations. The calculations incorporate essential non-critical contributions to proton fluctuations such as repulsive baryonic core and exact baryon-number conservation. The experimental data are consistent with non-critical physics at collision energies of √SNN ≥ 20 GeV. The data from the STAR and HADES collaborations at lower collision energies indicate an excess of (multi-)proton correlations over the non-critical reference. This observation is discussed in the context of different mechanisms, including the possibility of a critical point in the baryon-rich region of the QCD phase diagram.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Impacts of vacancy-induced polarization and distortion on diffusion in Solid Electrolyte Li 3 OCl

We report that Lithium-rich oxychloride antiperovskites are promising solid electrolytes for enabling next-generation batteries. Here, we report a comprehensive study varying Li + concentrations in Li 3 OCl using ab initio molecular dynamics simulations. The simulations accurately capture the complex interactions between Li + vacancies (V$^'_{Li}$), the dominant mobile species in Li 3 OCl. The V$^'_{Li}$ polarize and distort the host lattice, inducing additional non-vacancy-mediated diffusion mechanisms and correlated diffusion events that reduce the activation energy barrier at concentrations as low as 1.5% V$^'_{Li}$. Our analyses of discretized diffusion events in both space and time illustrate the critical interplay between correlated dynamics, polarization and local distortion in promoting ionic conductivity in Li 3 OCl.

25 ENERGY STORAGE↗
DOE OSTI2025

Energy, economic, and environmental tradeoffs at run-of-river hydropower facilities

Hydropower’s ability to quickly adapt to variability from wind and solar generation by fluctuation flow rates can allow the electricity grid to integrate more renewable capacity. However, these rapid flow fluctuations, required to meet variability needs, can negatively impact aquatic ecosystems. In this study, we quantified energy-economic-environment tradeoffs at five conventional hydropower facilities (i.e. hydropower produced ad a dam on a river channel) across the United States to identify a mix of operational regimes that can provide flexibility to support variable renewable energy integration and environmental protections. Model results show a range of ability to meet demand from 4.7% to 97.8% depending on which case study is considered. Additionally, when modeling the case study facilities on a range of RoR conditions, allowing a % of inflow as discharge, we found the range of 140–200% of inflow allowed as discharge lead to lowest environmental impact while meeting the highest amount of demand. Our sensitivity analysis results demonstrated the Richard-Baker Flashiness Index, used to measure flowrate changes, and Revenue, were negatively correlated with the percent of hydropower generation within the defined Regional Energy Deployment System balancing area (i.e. region in which energy demand and energy supply is balanced based on the Regional Energy Deployment System model) yet positively correlated to the variable renewable energy generation percentage in the defined balancing area. In conclusion, our results suggest hydropower operations can aid in increasing renewable energy generation while limiting environmental impacts when considering a holistic analysis of energy-economic-environment tradeoffs.

Economic impact↗
DOE OSTI2026

Hierarchical Reinforcement Learning of a Short-Range Bond-Order Potential for Silica: Analytic Embedding of Coordination with Classical Efficiency

Reinforcement learning (RL) has recently emerged as a data-efficient strategy to parametrize short-range interatomic potentials. Building on our past RL optimization of pairwise silica models, we extend the framework to a bond-order (Tersoff-type) potential that provides an analytic embedding of local coordination through a three-body term. A hierarchical RL workflow combining continuous-action Monte Carlo Tree Search and property-based rewards efficiently explores the 26-dimensional parameter space, sequentially optimizing lattice parameters, densities, angles, and cohesive energies of 21 silica polymorphs. The resulting models, Q-Tersoff and ML-Tersoff, reproduce the energetic ordering of low-energy phases and capture the angular correlations and amorphous structure factors of silica with improved fidelity over pairwise force fields, while remaining orders of magnitude faster than high-dimensional machine-learned potentials. Both models underperform for elastic constants and high-energy frameworks, delineating the limits of the current analytic form. The approach establishes a general and interpretable route to angle-aware, short-range potentials that bridge physics-based and machine-learned descriptions of silicate materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A non-perturbative pairwise-additive analysis of charge transfer contributions to intermolecular interaction energies

Energy decomposition analysis (EDA) based on absolutely localized molecular orbitals (ALMOs) decomposes the interaction energy between molecules into physically interpretable components like geometry distortion, frozen interactions, polarization, and charge transfer (CT, also sometimes called charge delocalization) interactions. In this work, a numerically exact scheme to decompose the CT interaction energy into pairwise additive terms is introduced for the ALMO-EDA using density functional theory. Unlike perturbative pairwise charge-decomposition analysis, the new approach does not break down for strongly interacting systems, or show significant exchange–correlation functional dependence in the decomposed energy components. Both the energy lowering and the charge flow associated with CT can be decomposed. Complementary occupied–virtual orbital pairs (COVPs) that capture the dominant donor and acceptor CT orbitals are obtained for the new decomposition. It is applied to systems with different types of interactions including DNA base-pairs, borane-ammonia adducts, and transition metal hexacarbonyls. While consistent with most existing understanding of the nature of CT in these systems, we report the results also reveal some new insights into the origin of trends in donor–acceptor interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Effects of shape/phase transition regions on neutron capture cross sections

Abstract A recent study found a new, purely empirical correlation between two-neutron separation energies and neutron capture cross sections in keV neutron energy regimes. In shape/phase transition regimes, such as that near A= 150, S $$_{2n}$$ 2 n values show an anomaly—a flattening of the normal near linear decrease with neutron number. This paper addresses two questions: (1) Using this new correlation, is this anomaly in S $$_{2n}$$ 2 n values sizeable enough to produce an observable effect in capture cross sections? and (2) Can the correlation be used to quantitatively reproduce the cross sections in the transition region? It is found that the answer to both questions is in the affirmative. Possible relations to the r -process are briefly discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Estimation of mean electron energy in helium surface ionization waves on dielectric substrates

Abstract The determination of basic plasma parameters in atmospheric pressure discharges is critical to advancing their use in applications. Atmospheric pressure plasma jets have found use in the fields of medicine, agriculture, material modification and others. Atmospheric pressure plasma jets often generate plasma surface ionization waves (SIW) which interact with and propagate over surfaces. Electrical diagnostics are challenging in SIW due to high collision frequencies and small scale of the plasma discharge. This work employs a passive optical emission line ratio technique to estimate the mean electron energy in SIW over planar dielectric substrates. The method uses an intensity ratio of two helium triplet lines: He( 3 3 S ) at 706.5 nm and He( 3 3 D ) at 587.56 nm. A collisional-radiative model is used to correlate line ratio to mean electron energy and determine dependencies on electron density and He/air gas mixture. Mean electron energies ranging from 3–8 eV are determined in He/air mixtures and are found to remain constant as the surface wave propagates radially. This work provides a 2D, time-resolved, mean electron energy diagnostic for surface ionization wave propagation and validation of numerical modeling in atmospheric pressure systems with spatially varying He/air gas mixtures. The model in question is designed for use with any He line ratio in the n = 3 excitation level.

Morsell, Joshua (ORCID:0000000331073002)↗
DOE OSTI2026

DESI DR2 Baryon Acoustic Oscillations from the Lyman Alpha Forest Multipoles

We present an alternative measurement of the Baryon Acoustic Oscillation (BAO) using the Legendre multipole representation of the Ly$α$ forest correlation functions from the second data release (DR2) of the Dark Energy Spectroscopic Instrument survey. Compressing the auto- and cross-correlation functions into Legendre multipoles yields a positive-definite covariance matrix without any smoothing -- unlike the baseline DR2 analysis -- thanks to a significantly reduced data vector size. We introduce the statistical corrections required to debias the finite-sample covariance matrix estimate and demonstrate that monopole and quadrupole terms for both auto- and cross-correlations can be used even when the correlation functions are distorted by continuum errors and contaminated by metals. This formalism has slightly diminished the constraining power of the BAO scale, while considerably weakening constraints on nuisance parameters. We measure the isotropic BAO scale with $0.93\%$ precision at $z_\mathrm{eff}=2.35$, the Hubble parameter $H(z_\mathrm{eff})=(239.5\pm3.4)~(147.09~\mathrm{Mpc}/r_d) ~\mathrm{km~s}^{-1}~\text{Mpc}^{-1}$, and the transverse comoving distance $D_M(z_\mathrm{eff})=(5.80 \pm 0.10)~(r_d/147.09~\mathrm{Mpc})$~Gpc for a given value of the sound horizon ($r_d$). Our BAO results are entirely consistent with the baseline DR2 analysis.

Karaçaylı, Naim Göksel [Chicago U., KICP; Ohio Sta↗
DOE OSTI2021

Cosmological constraints from unWISE and Planck CMB lensing tomography

A number of recent, low-redshift, lensing measurements hint at a universe in which the amplitude of lensing is lower than that predicted from the ΛCDM model fit to the data of the Planck CMB mission. Here we use the auto- and cross-correlation signal of unWISE galaxies and Planck CMB lensing maps to infer cosmological parameters at low redshift. In particular, we consider three unWISE samples (denoted as "blue", "green" and "red") at median redshifts z ~ 0.6, 1.1 and 1.5, which fully cover the Dark Energy dominated era. Our cross-correlation measurements, with combined significance S/N ~ 80, are used to infer the amplitude of low-redshift fluctuations, σ 8 ; the fraction of matter in the Universe, Ω m ; and the combination S 8 ≡ σ 8 (Ω m /0.3) 0.5 to which these low-redshift lensing measurements are most sensitive. The combination of blue, green and red samples gives a value S m = 0.784 ± 0.015, that is fully consistent with other low-redshift lensing measurements and in 2.4σ tension with the CMB predictions from Planck. Finally, this is noteworthy, because CMB lensing probes the same physics as previous galaxy lensing measurements, but with very different systematics, thus providing an excellent complement to previous measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

How Wrong Can the Operational AEP Uncertainty Estimate Be When We Ignore the Correlations Between the Uncertainty Components?

Calculations of wind farm annual energy production (AEP) on operational data are essential for a variety of financial transactions during the life of wind plants. The AEP estimate is associated with an uncertainty value, which is calculated by combining contributions connected to on-site measurements, long-term reference measurements, losses, regression, windiness adjustment, and wind resource interannual variability. Although very limited documentation on the topic exists, the conventional approach currently used by the wind energy community to assess the uncertainty connected to the operational AEP estimate assume that the different uncertainty components are uncorrelated and therefore calculates the overall uncertainty with a sum of squares approach. In this analysis, we contrast the traditional technique to estimate the overall AEP uncertainty by ignoring the correlation between its different components with a novel Monte Carlo based approach, which can instead take into account the correlation between different uncertainty categories. We consider monthly operational data from 472 wind farms from the Energy Information Administration (EIA) 923 database to assess the difference between the two approaches. Long-term wind speed data needed for the AEP assessment are taken from three reanalysis products: the Modern-Era Retrospective analysis for Research and Applications v2 (MERRA-2), the European Reanalysis Interim (ERA-interim), and the National Centers for Environmental Prediction v2 (NCEP-2). The results of the Monte Carlo approach show that three pairs of AEP uncertainty components do show a statistically significant correlation: the uncertainty connected with wind resource inter-annual variability is positively correlated with the one related to the windiness correction and negatively correlated with the one due to the regression, and the wind measurement uncertainty is positively correlated with the regression uncertainty. All these correlations, which are found between uncertainty components which are not only part of an operational analysis, but also of a wind resource assessment, are currently ignored in the conventional techniques used as industry standard. We further investigate the causes of these correlations, in terms of common dependencies of different uncertainty components on wind resource variability, number of data points, and quality of the regression between wind speed and energy production data. Next, we quantify the error in the current industry standard technique, in terms of the percentage difference in total uncertainty calculated with the two considered approaches, for all the analyzed wind farms. We find a mean absolute percentage difference of about 6%, with the largest differences being greater than 20%. The data clearly confirm that ignoring the actual correlation between the uncertainty components can lead to large errors in the assessment of the operational AEP uncertainty, and the proposed Monte Carlo approach should be preferred.

Monte Carlo↗
DOE OSTI2020

Doping evolution of the charge excitations and electron correlations in electron-doped superconducting La 2-x Ce x CuO 4

Electron correlations play a dominant role in the charge dynamics of the cuprates. We use resonant inelastic X-ray scattering (RIXS) to track the doping dependence of the collective charge excitations in electron doped La 2-x Ce x CuO 4 (LCCO). From the resonant energy dependence and the out-of-plane momentum dependence, the charge excitations are identified as three-dimensional (3D) plasmons, which reflect the nature of the electronic structure and Coulomb repulsion on both short and long lengthscales. With increasing electron doping, the plasmon excitations increase monotonically in energy, a consequence of the electron correlation effect on electron structure near the Fermi surface (FS). Importantly, the plasmon excitations evolve from a broad feature into a well-defined peak with much increased life time, revealing the evolution of the electrons from incoherent states to coherent quasi-particles near the FS. Such evolution marks the reduction of the short-range electronic correlation, and thus the softening of the Mottness of the system with increasing electron doping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Toward accelerating rare-earth metal extraction using equivariant neural networks

The separation of rare-earth metals, vital for numerous advanced technologies, is hampered by their similar chemical properties, making ligand discovery a significant challenge. Traditional experimental and quantum chemistry approaches for identifying effective ligands are often resource-intensive. We introduce a machine learning protocol based on an equivariant neural network, Allegro, for the rapid and accurate prediction of binding energies in rare-earth complexes. Key to this work is our newly curated dataset of rare-earth metal complexes—made publicly available to foster further research—systematically generated using the Architector program. This dataset distinctively features functionalized derivatives of proven rare-earth-chelating scaffolds, hydroxypyridinone (HOPO), catecholamide (CAM), and their thio-analogues, selected for their established efficacy in binding these elements. Trained on this valuable resource, our Allegro models demonstrate excellent performance, particularly when trained to directly predict DFT-level binding energies, yielding highly accurate results that closely correlate with theoretical calculations on a diverse test set. Furthermore, this strategy exhibited strong out-of-sample generalization, accurately predicting binding energies for an isomeric HOPO-derivative ligand not seen during training. By substantially reducing computational demands, this machine learning framework, alongside the provided dataset, represent powerful tools to accelerate the high-throughput screening and rational design of novel ligands for efficient rare-earth metal separation.

Gupta, Ankur K. [Lawrence Berkeley National Labora↗
DOE OSTI2022

Probing two-path electron quantum interference in strong-field ionization with time-correlation filtering

We report attosecond dynamics in strong-field tunnel ionization are encoded in intricate holographic patterns in the photoelectron momentum distributions. These patterns show the interference between two or more superposed quantum electron trajectories, which are defined by their ionization times and subsequent evolution in the laser field. We determine the ionization time separation between interfering pairs of electron orbits by performing a differential Fourier analysis on the measured momentum spectrum. We identify electron holograms formed by trajectory pairs whose ionization times are separated by less than a single quarter cycle, between a quarter cycle and half cycle, between a half cycle and three fourths of a cycle, and a full cycle apart. We compare our experimental results to the predictions of the Coulomb quantum orbit strong-field approximation (CQSFA) with significant success. We also time-filter the CQSFA trajectory calculations to demonstrate the validity of the technique on spectra with known time correlations. As a general analysis technique, the filter can be applied to all energy- and angularly resolved data sets to recover time correlations between interfering electron pathways, providing an important tool to analyze any strong-field ionization spectra. Moreover, it is independent of theory and can be applied directly to experiments, without the need of a direct comparison with orbit-based theoretical methods.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Search for PeV Gamma-Ray Emission from the Southern Hemisphere with 5 Yr of Data from the IceCube Observatory

The measurement of diffuse PeV gamma-ray emission from the Galactic plane would provide information about the energy spectrum and propagation of Galactic cosmic rays, and the detection of a pointlike source of PeV gamma-rays would be strong evidence for a Galactic source capable of accelerating cosmic rays up to at least a few PeV. This paper presents several unbinned maximum-likelihood searches for PeV gamma-rays in the Southern Hemisphere using 5 yr of data from the IceTop air shower surface detector and the in-ice array of the IceCube Observatory. The combination of both detectors takes advantage of the low muon content and deep shower maximum of gamma-ray air showers and provides excellent sensitivity to gamma-rays between ~0.6 and 100 PeV. Our measurements of pointlike and diffuse Galactic emission of PeV gamma-rays are consistent with the background, so we constrain the angle-integrated diffuse gamma-ray flux from the Galactic plane at 2 PeV to 2.61 × 10 -19 cm -2 s -1 TeV -1 at 90% confidence, assuming an E -3 spectrum, and we estimate 90% upper limits on pointlike emission at 2 PeV between 10 -21 and 10 -20 cm -2 s -1 TeV -1 for an E -2 spectrum, depending on decl. Furthermore, we exclude unbroken power-law emission up to 2 PeV for several TeV gamma-ray sources observed by the High Energy Spectroscopic System and calculate upper limits on the energy cutoffs of these sources at 90% confidence. We also find no PeV gamma-rays correlated with neutrinos from IceCube's high-energy starting event sample. Lastly, these are currently the strongest constraints on PeV gamma-ray emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Dark matter and galaxy cross-correlations with the Cherenkov Telescope Array Observatory

The Cherenkov Telescope Array Observatory (CTAO) will be a ground-based Cherenkov telescope performing wide-sky surveys, ideal for anisotropy studies such as cross-correlations with tracers of the cosmic large-scale structure. Cross-correlations can shed light on high-energy γ -ray sources and potentially reveal exotic signals from particle dark matter. In this work, we investigate CTAO sensitivity to cross-correlation signals between γ -ray emission and galaxy distributions. We find that by using dense, low-redshift catalogs like 2 MASS, and for integration times around 50 hours, this technique achieves sensitivities to both annihilating and decaying dark matter signals that are competitive with those from dwarf galaxy and cluster analyses.

Pinetti, Elena [CCA, New York; Perimeter Inst. The↗
DOE OSTI2021

Role of Coulomb interaction in the phase formation of fcc Ce: Correlation matrix renormalization theory

The effect of electronic Coulomb interaction on the phase formation of fcc Ce lattice is investigated by full ab initio calculations without adjustable Coulomb U and J parameters using the Gutzwiller wavefunction-based correlation matrix renormalization theory (CMRT). Its total energy and pressure as a function of volume agree reasonably well with existing DFT+Gutzwiller calculations and experiments, indicating correct capture of electronic correlation and screening effects within the CMRT formalism. Here, a stable phase is found in line with the experimental α-Ce phase, and a lurking phase is identified supposedly linked with the experimental γ-Ce phase. A criterion based on the local 4f electron charge fluctuation is introduced to confirm the distinct electronic correlation natures of both phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗