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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 OSTI2022

Local imaging of diamagnetism in proximity-coupled niobium nanoisland arrays on gold thin films.

In this work, we study the effect of engineered disorder on the local magnetic response of proximity-coupled superconducting island arrays by comparing scanning superconducting quantum interference device (SQUID) susceptibility measurements to a model in which we treat the system as a network of one-dimensional (1D) superconductor-normal-metal-superconductor Josephson junctions, each with a Josephson coupling energy E-J determined by the junction length or distance between islands. We find that the disordered arrays exhibit a spatially inhomogeneous diamagnetic response which, for low local applied magnetic fields, is well described by this junction network model, and we discuss these results as they relate to inhomogeneous 2D superconductors. Our model of the static magnetic response of the arrays does not fully capture the onset of nonlinearity and dissipation with increasing applied field, as these effects are associated with vortex motion due to the dynamic nature of the scanning SQUID susceptometry measurement. This work demonstrates a model 2D superconducting system with engineered disorder, and it highlights the impact of dissipation on the local magnetic properties of 2D superconductors and Josephson junction arrays.

Bishop-Van Horn, Logan↗
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

Mapping the three-dimensional fermiology of the triangular lattice magnet EuAg 4 Sb 2

In this paper, we report the temperature-field phase diagram as well as present a comprehensive study of the electronic structure and three-dimensional fermiology of the triangular-lattice magnet EuAg 4 ⁢Sb 2 , utilizing quantum oscillation measurements, angle-resolved photoemission spectroscopy, and first-principles calculations. The complex magnetic phase diagram of EuAg 4 ⁢Sb 2 highlights many transitions through nontrivial AFM states. Shubnikov-de Haas and de Haas-van Alphen oscillations were observed in the polarized ferromagnetic state of EuAg 4 ⁢Sb 2 , revealing three pairs of distinct spin-split frequency branches with small effective masses. A comparison of the angle-dependent oscillation data with first-principles calculations in the ferromagnetic state and angle-resolved photoemission spectra shows good agreement, identifying tubular hole pockets and hourglass-shaped hole pockets at the Brillouin zone center, as well as diamond-shaped electron pockets at the zone boundary. As the temperature increases, the frequency branches of the tiny hourglass pockets evolve into a more cylindrical shape, while the larger pockets remain unchanged. This highlights that variations in exchange splitting, driven by changes in the magnetic moment, primarily impact the small Fermi pockets without significantly altering the overall band structure. As a result, this is consistent with first-principles calculations, which show minimal changes near the Fermi level across ferromagnetic and simple antiferromagnetic states or under varying on-site Coulomb repulsion.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Informing nuclear physics via machine learning methods with differential and integral experiments

Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Structure of even-even Sr isotopes with 50 ≤ N ≤ 58 neutrons

Excited levels in Sr 90 , Sr 92 , Sr 94 , and Sr 96 nuclei were reinvestigated using high-statistics multiple- γ coincidence data from neutron-induced fission of U 235 and spontaneous fission of Cf 252 , measured using Exogam at Institut Laue Langevin and Gammasphere arrays, respectively. The experimental goal was the search for new excited levels and firm spin-parity assignments to known levels. A total of 23 new levels with 30 new or corrected decays and 39 new or improved spin-parity assignments were obtained in the four nuclei. Negative-parity structures on top of 3 - excitation were firmly identified and extended to higher spins. New positive-parity structures in Sr 94 and Sr 96 were observed with 3 + excitations characteristic of γ collectivity. The 277.7-keV, E 2 decay from the 1507.0-keV level to the second 0 + level in Sr 96 , found in this paper, completes the coexisting deformed band in this nucleus. To learn about the microscopic structure of levels in the Sr 88 - 96 nuclei, we performed large-scale shell-model calculations. The calculations compared to the experiment, helped the discussion of the evolution of collectivity in strontium isotopes, highlighting the important role of various single-particle excitations in phase transitions and shape coexistence in the region. The special role of the neutron 9 / 2 + [ 404 ] extruder as a catalyst of the deformation change in the region is highlighted.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

DESI 2024: Constraints on physics-focused aspects of dark energy using DESI DR1 BAO data

Baryon acoustic oscillation data from the first year of the Dark Energy Spectroscopic Instrument (DESI) provide near percent-level precision of cosmic distances in seven bins over the redshift range z=0.1–4.2. Here, this paper is the follow-up to the original DESI BAO cosmology paper [A. G. Adame et al. (DESI Collaboration), arXiv:2404.03002], which considered the conventional w 0 w a cold dark matter (CDM) model. We use the novel DESI data, together with other cosmic probes, to constrain the background expansion history using some well-motivated physical classes of dark energy. In particular, we explore three physics-focused behaviors of dark energy from the equation of state and energy density perspectives: the thawing class (matching many simple quintessence potentials), emergent class (where dark energy comes into being recently, as in phase transition models), and mirage class [where phenomenologically the distance to cosmic microwave background (CMB) last scattering is close to that from a cosmological constant Λ despite dark energy dynamics]. All three classes fit the data at least as well as Λ ⁢CDM, and indeed can improve on it by Δ⁢χ 2 ≈ –5 to –17 for the combination of DESI BAO with CMB and supernova data while having one more parameter. The mirage class does essentially as well as w 0 ⁢w a CDM and exhibits moderate to strong Bayesian evidence preference with respect to Λ⁢ CDM. These classes of dynamical behaviors highlight worthwhile avenues for further exploration into the nature of dark energy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Cation and anion topotactic transformations in cobaltite thin films leading to Ruddlesden-Popper phases.

Topotactic transformations involve structural changes between related crystal structures due to a loss or gain of material while retaining a crystallographic relationship. The perovskite oxide La0.7Sr0.3CoO3 (LSCO) is an ideal system for investigating phase transformations due to its high oxygen vacancy conductivity, relatively low oxygen vacancy formation energy, and strong coupling of the magnetic and electronic properties to the oxygen stoichiometry. While the transition between cobaltite perovskite and brownmillerite (BM) phases has been widely reported, further reduction beyond the BM phase lacks systematic studies. In this paper, we study the evolution of the physical properties of LSCO thin films upon exposure to highly reducing environments. We observe the rarely reported crystalline Ruddlesden-Popper phase, which involves the loss of both oxygen anions and cobalt cations upon annealing where the cobalt is found as isolated Co ions or Co nanoparticles. First-principles calculations confirm that the concurrent loss of oxygen and cobalt ions is thermodynamically possible through an intermediary BM phase. The strong correlation of the magnetic and electronic properties to the crystal structure highlights the potential of utilizing ion migration as a basis for emerging applications such as neuromorphic computing.

Chiu, I-Ting↗
DOE OSTI2023

Accuracy of DFT computed oxygen-vacancy formation energies and high-throughput search of solar thermochemical water-splitting compounds

The enthalpy change involved in metal oxide reduction is a key quantity in various processes related to energy conversion and storage, and is of particular interest for computational prediction. Often this prediction involves the simulation of a high temperature reduction process with a 0K methodology like density functional theory (DFT), and it is not infrequent for the high temperature and 0K stable crystal structures to differ. This introduces a conundrum with regards to the choice of crystal structure to utilize in the computation, with approaches in the literature varying and experimental validation remaining scarce. In this work we address both the crystal structure conundrum and the experimental validation, and then apply the insights we gain to guide a high-throughput search for new materials for solar thermochemical water-splitting applications. By computing the DFT+U oxygen vacancy formation energy (ΔE vf ) of a selection of ABO 3 compounds and comparing different crystal structures for each composition, we highlight the issues that arise when the structure utilized in the computation is dynamically unstable at 0K, namely the presence of an artificial lowering of ΔE vf , and the lack of convergence of ΔE vf with cell size. We solve these limitations by identifying and employing a suitable surrogate dynamically stable structure. We then validate the predictive power of our calculations against appositely generated experimental measurements of reduction enthalpy for a series of Hubbard U values, finding an accuracy ranging between 0.2-0.6 eV/O. In light of such conclusions, we revise and expand a previous a high-throughput DFT study on ABO 3 perovskite oxides. As a result, we provide a list of candidate STCH materials, highlight trends with redox-active cation and structural distortion, and identify Mn 4+ , Mn 3+ and Co 3+ as the most promising redox-active cations.

08 HYDROGEN↗
DOE OSTI2024

Direct observation of entangled electronic-nuclear wave packets

We present momentum resolved covariance measurements of entangled electronic-nuclear wave packets created and probed with octave spanning phaselocked ultrafast pulses. We launch vibrational wave packets on multiple electronic states via multiphoton absorption, and probe these wave packets via strong field double ionization using a second phaselocked pulse. Momentum resolved covariance mapping of the fragment ions highlights the nuclear motion, while measurements of the yield as a function of the relative phase between pump and probe pulses highlight the electronic coherence. The combined measurements allow us to directly visualize the entanglement between the electronic and nuclear degrees of freedom and follow the evolution of the complete wavefunction. Published by the American Physical Society 2024

Moğol, Gönenç↗
DOE OSTI2026

Isotopic discrepancy in microscopic fusion of 16 O + 40,48 Ca

We present a detailed comparison of fusion in 16 O + 40,48 Ca within a fully microscopic time-dependent Hartree-Fock framework over sub-, near-, and above-barrier energies. While 16 O + 40 Ca fusion cross sections are reproduced within the available experimental energy range, calculations for the neutron-rich 16 O + 48 Ca system systematically overestimate the measured near-barrier cross sections. The discrepancy persists across the tested energy density functionals, indicating that it is not tied to a particular parametrization. Analysis of the dynamical interaction potentials reveals an outward shift and softening of the barrier region at the lowest collision energies. These results are then compared to a frozen density description where the barrier modifications are absent and the predicted cross sections are brought closer to experiment. Here, this demonstrates that the observed discrepancy is closely linked to dynamical surface rearrangement and isovector effects, and highlights the sensitivity of low-energy fusion to both the structure and dynamics of neutron-rich nuclei. This suggests that limitations in the isovector sector of conventional Skyrme EDFs in describing the structure of 48 Ca, as highlighted by CREX, are also manifested in the fusion dynamics of the 16 O + 48 Ca system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

SCOMAP-XD : atomistic deuterium contrast matching for small-angle neutron scattering in biology

The contrast-variation method in small-angle neutron scattering (SANS) is a uniquely powerful technique for determining the structure of individual components in biomolecular systems containing regions of different neutron scattering length density ρ . By altering the ρ of the target solute and the solvent through judicious incorporation of deuterium, the scattering of desired solute features can be highlighted. Most contrast-variation methods focus on highlighting specific bulk solute elements, but not on how the scattering at specific scattering vectors q , which are associated with specific structural distances, changes with contrast. Indeed, many systems exhibit q -dependent contrast effects. Here, a method is presented for calculating both bulk contrast-match points and q -dependent contrast using 3D models with explicit solute and solvent atoms and SASSENA , an explicit-atom SANS calculator. The method calculates the bulk contrast-match points within 2.4% solvent D 2 O accuracy for test protein–nucleic acid and lipid nanodisc systems. The method incorporates a general model for the incorporation of deuterium at non-exchangeable sites that was derived by performing mass spectrometry on green fluorescent protein. The method also decomposes the scattering profile into its component parts and identifies structural features that change with contrast. The method is readily applicable to a variety of systems, will expand the understanding of q -dependent contrast matching and will aid in the optimization of next-generation neutron scattering experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Survey on the Design, Detection, and Prevention of Pre-Silicon Hardware Trojans

The complexity of the semiconductor design lifecycle and globalized manufacturing process creates concern over the threat of deliberate malicious alterations, or hardware Trojans, being inserted into microelectronic designs. This has resulted in a significant corpus of hardware Trojan research including Trojan design and benchmarking efforts and development of corresponding metrics and detection and prevention techniques, over the last two decades. In this survey, we first highlight efforts in Trojan design and benchmarking, followed by a cataloging of seminal and recent works in Trojan detection and prevention and their accompanied metrics. Given the volume of literature in this field, this survey considers only pre-silicon techniques. We make this distinction between pre- and post-silicon to properly scope and provide appropriate context into the capabilities of existing hardware Trojan literature. Each major section (design, prevention, and detection) is accompanied by insights, and common pitfalls, which we highlight can be addressed by future research.

42 ENGINEERING↗
DOE OSTI2026

Power Electronic Development Challenges for High Power Density Integrated Electric Drive Applications

The ever-increasing demand for compact, efficient, and high-performance traction drive systems for transportation applications has accelerated the development of integrated electric drives. In these systems, the electric machine and inverter are integrated within a single housing, offering significant advantages in electrical performance, volume, weight, cost, and overall system efficiency. Despite these benefits, such high levels of integration introduce a new set of challenges, particularly in power electronic design and component selection. This article presents an in-depth investigation of a highly integrated electric drive architecture with an internal stator-mounted inverter, highlighting key design considerations and trade-offs aimed exclusively at maximizing system power density.Based on a comprehensive review of the literature, the power density of a voltage-source-inverter-driven electric drive is primarily governed by the volumetric contributions of the power modules, heat sinks, and DC-link capacitors. Accordingly, this work focuses on the optimization of these three critical components to enhance the inverter's overall power density. The proposed design achieves a power density of 100 kW/L, demonstrating the effectiveness of the presented approach for next-generation integrated electric drive systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Exploring the Landscape of Distributed Graph Clustering on Leadership Supercomputers

The rapid growth of large-scale datasets in fields like biology and social networks has driven the need for advanced graph analytics techniques. Community detection, a fundamental task in graph analytics, identifies closely connected groups of nodes within a network, providing valuable insights across various disciplines. This study focuses on two classic community detection methods, the Louvain algorithm and Markov Clustering (MCL), and evaluates the performance of two prominent distributed community detection algorithms: HiPDPL-GPU, our prior implementation, and HipMCL. We conduct experiments on GPU-accelerated heterogeneous HPC systems, Summit and Frontier, to assess their performance under varying conditions. Our objective is to identify the strengths and weaknesses of these algorithms in terms of scalability, and quality of solutions. We evaluate these algorithms on a diverse set of 70+ networks spanning 13 domains, with sizes ranging up to 4.2 billion edges. Our results demonstrate that HiPDPL-GPU consistently outperforms HipMCL, especially for large-scale networks. HiPDPL-GPU achieves significantly faster runtimes (47x to 1439x), higher modularity scores, and improved scalability. These findings highlight HiPDPL-GPU as a promising solution for efficient and effective large-scale graph analytics in diverse application domains, and provide insights into the feasibility of using MCL-based approaches for certain application domains.

Community detection, graph algorithms↗
DOE OSTI2024

Frequency Stability Enhancement in a Fully Solar Power Grid: A Case Study on the Saudi Model

Recently, renewable energy sources (RES) such as solar photovoltaic (PV) have been recognized for their significant potential. Several studies have explored the issue of frequency stability with high RES penetration. A significant observation related to this issue is the decline in the weighted short circuit ratio (WSCR), which has the potential to adversely affect system stability. This research uniquely focuses on the gradual transition of the Saudi Electricity Company (SEC) system to a fully integrated solar PV grid, offering insight and methodology that can be adapted for other power systems. While a variety of mitigation methods are available, synchronous condensers (SC) were used in this study to stabilize grid frequency, and their implementation has been shown to improve the overall performance of the system. In response to the observed decline in WSCR, a comprehensive short circuit analysis was applied across all regions in the Saudi power grid model to evaluate the reduction in short circuit power and highlight areas requiring enhancement. Finally, scenarios illustrating frequency response with a gradual increase in SCR were analyzed, with the objective of establishing a stable, fully solar PV power system that is resilient to sudden power grid disturbances.

14 SOLAR ENERGY↗
DOE OSTI2023

Towards Smart Grids Enhanced Situation Awareness: A Bi-Level Quasi-Static State Estimation Model

Smart Grid situational awareness is provided by Energy Management Systems. A core process of these systems is State Estimation. The great majority of state estimators model the Smart Grid through a set of nonlinear algebraic equations, named the measurement model. Problem formulation considers the Gauss solution. Several model improvements have been presented regarding the Gauss solution, aiming between others to provide measurement noise robustness to the state estimation process. While considerable effort has been focused on such developments, state estimation is still constrained by the implicit modelling error, and thus inevitably vulnerable to cyber-threats. In this work, a state estimation bi-level formal model is presented towards Smart Grids enhanced situational awareness considering the concepts of synthetic measurements and innovation. Comparative test results with the state-of-the-art on the IEEE 14-bus system are presented highlighting improved situational awareness to bad data. Easy-to-implement model, without hard-to-derive parameters, built-on the classic weighted least squares solution, highlight potential aspects for real-life implementation.

cyber security↗
DOE OSTI2021

Applying Utility's Advanced Grid Technologies to Improve Resiliency of a Critical Load

The US DOE Office of Electricity's Energy Storage Program's joint R&D work with the Cordova Electric Cooperative (CEC) has deployed several advanced grid technologies that are providing benefits today to Cordova Alaska's electricity users. Advanced grid technologies deployed through DoE co-funded R&D include a 1MW Battery Energy Storage System (BESS), and enhanced monitoring including Phasor Measurement Units (PMU's) to help better understand the operational impacts of the added BESS. This paper will highlight key accomplishments to-date in deploying and using advanced grid technologies, and then outline the next phase of work that will use these technologies to implement an operating scheme to reconfigure the utility's distribution system and utility resources including BESS to provide emergency back-up power to a critical load: the Cordova Community Medical Center (CCMC). This paper will include additional insights on the use of utility resources to support critical loads via case study examples by the National Rural Electric Cooperative Assoc. (NRECA).

BESS↗
DOE OSTI2024

Increasing Multilayer Ceramic Capacitor Lifetime With Bipolar Voltage Cycling

Enhancing the lifetime of multilayer ceramic capacitors (MLCCs) is critical in many aerospace, naval, or electrical grid applications, where device failure could lead to catastrophic consequences. The migration of oxygen vacancies from the ceramic to the electrode interface under constant bias is known to reduce the lifetime of oxide-based MLCCs. Bias cycling presents an opportunity to enhance MLCC lifetime by reducing oxygen vacancy migration. The ideal frequency range is expected to lie between frequencies low enough to avoid self-heating but high enough to avoid interfacial defect formation. However, the impact of low-frequency bipolar voltage cycling (BVC) on MLCC degradation mechanisms has not been well studied. This work investigates the impact of periodic BVC on the degradation of MLCCs through highly accelerated lifetime testing (HALT) on X7R capacitors. HALT tests were conducted at 255 °C and 60 V using different switching frequencies: 0 (dc), 0.1, 2.5, and 10 Hz. BVC was found to improve the lifetime of MLCCs compared to dc test conditions. MLCCs tested at 10-Hz BVC showed a 311% increase in average time to failure compared to the dc case. Impedance spectroscopy shows that BVC decreases the rate of resistance degradation within MLCCs, indicating that oxygen vacancy migration to the electrodes is mitigated. The impedance spectra taken on BVC samples highlight how grain boundaries play a vital role in trapping oxygen vacancies. Periodic cycling causes oxygen vacancies to become trapped at grain boundaries, resulting in oxygen vacancies taking longer to reach the electrode interface and thus increasing MLCC lifetime. This work highlights not only how BVC can be used to increase MLCC lifetime but also how periodically cycling MLCCs could increase lifetime in extreme environments, such as at elevated temperatures and electric fields.

Chuong, Kayla Y.↗