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At least 271 records · Page 15

Quantum phase transitions in a model Hamiltonian exhibiting entangled simultaneous fermion-pair and exciton condensations

Quantum states of a novel Bose-Einstein condensate, in which both fermion-pair and exciton condensations are simultaneously present, have recently been realized theoretically in a model Hamiltonian system. Here, in this study, we identify quantum phase transitions in that model between fermion-pair and exciton condensations based on a geometric analysis of the convex set of ground-state two-particle reduced density matrices (2-RDMs). The 2-RDM set provides a finite representation of the infinite parameter space of Hamiltonians that readily reveals a fermion-pair condensate phase and two distinct exciton condensate phases, as well as the emergence of first- and second-order phase transitions as the particle number of the system is increased. The set, furthermore, shows that the fermion-exciton condensate (FEC) lies along the second-order phase transition between the exciton and fermion-pair condensate phases. The detailed information about the exciton and fermion-pair phases, the forces behind these phases, as well as their associated transitions provides additional insight into the formation of the FEC condensate, which we anticipate will prove useful in its experimental realization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Propagation of acoustic modes in the transitional ionosphere

Continuum theory is unsatisfactory for describing wave propagation in the transitional ionosphere, since the mean free path is of the same order as the characteristic length (i.e., Knudsen number in this region is of the order of unity). Therefore a transition model in which isotropic electrons behave as a fluid while the ions are governed by the kinetic equation modified by ion-electron collision effects is proposed to study acoustic wave propagation in the upper atmosphere in the altitude region from 500 to 2000 km. The results show that the dissipation of acoustic waves by electrons is through the viscous and thermal conduction effects, and the dissipation of acoustic waves by ions is through Landau damping. Comparisons of the characteristics of acoustic mode propagation and wave dissipation mechanisms in the collision-dominated, transitional from collisional to collisionless, and collisionless media are also discussed.

Hung, R. J.↗

Free-stream turbulence and concave curvature effects on heated, transitional boundary layers

An experimental investigation of the transition process on flat-plate and concave curved-wall boundary layers for various free-stream turbulence levels was performed. Results show that for transition of a flat-plate, the two forms of boundary layer behavior, identified as laminar-like and turbulent-like, cannot be thought of as separate Blasius and fully-turbulent profiles, respectively. Thus, simple transition models in which the desired quantity is assumed to be an average, weighted on intermittency, of the theoretical laminar and fully turbulent values is not expected to be successful. Deviation of the flow identified as laminar-like from theoretical laminar behavior is shown to be due to recovery after the passage of a turbulent spot, while deviation of the flow identified as turbulent-like from the full-turbulent values is thought to be due to incomplete establishment of the fully-turbulent power spectral distribution. Turbulent Prandtl numbers for the transitional flow, computed from measured shear stress, turbulent heat flux and mean velocity and temperature profiles, were less than unity. For the curved-wall case with low free-stream turbulence intensity, the existence of Gortler vortices on the concave wall within both laminar and turbulent flows was established using liquid crystal visualization and spanwise velocity and temperature traverses. Transition was found to occur via a vortex breakdown mode. The vortex wavelength was quite irregular in both the laminar and turbulent flows, but the vortices were stable in time and space. The upwash was found to be more unstable, with higher levels of u' and u'v', and lower skin friction coefficients and shape factors. Turbulent Prandtl numbers, measured using a triple-wire probe, were found to be near unity for all post-transitional profiles, indicating no gross violation of Reynolds analogy. No evidence of streamwise vortices was seen in the high turbulence intensity case.

Kim, J.↗

DriveSense: A Noise-Resilient Framework for Driving Mode Identification

Accurate drive mode classification is essential for enhancing the reliability and predictive maintenance of heavy-duty electric trucks. This study proposes a novel fuzzy logic-based framework, DriveSense, for real-time drive mode classification, addressing key challenges such as sensor noise, transitional behaviors, and computational efficiency. The proposed approach integrates a two-stage filtering pipeline, combining adaptive outlier removal and a dynamic Kalman filter to enhance data quality. A fuzzy inference system with smoothened trapezoidal membership functions is then applied to classify driving modes into standstill, constant speed, acceleration, and deceleration while mitigating the effects of noise and edge cases. Performance evaluation using real-world and simulated drive cycles demonstrates significant improvements in classification accuracy (up to 97.8%), F1-score (up to 0.97), and robustness against noise, while reducing false positives. Comparative analysis against baseline models, demonstrates DriveSense’s superior accuracy and generalizability across diverse driving patterns. The framework’s lightweight and interpretable fuzzy inference engine operates with low computational latency, ensuring compatibility with real-time embedded systems typical of heavy-duty electric trucks. Moreover, DriveSense models transitional behaviors through overlapping fuzzy sets and adaptive borderline classification logic, enabling smooth identification of subtle shifts such as rolling stops or gradual deceleration. These results highlight DriveSense’s potential to enhance predictive maintenance strategies, reduce downtime, and support scalable, fleet-wide diagnostics.

Kumar, Praveen [Oak Ridge National Laboratory (ORN↗

Tailoring light-induced charge transfer and intersystem crossing in FeCO using time-dependent spin–orbit configuration interaction

Real-time (RT) electronic structure methods provide a natural framework for describing light–matter interactions in arbitrary time-dependent electromagnetic fields (EMF). Optically induced excited state transitions are of particular interest, which require tuned EMF to drive population transfer to and from the specific state(s) of interest. Intersystem crossing, or spin-flip, may be driven through shaped EMF or laser pulses. These transitions can result in long-lived “spin-trapped” excited states, which are especially useful for materials requiring charge separation or protracted excited state lifetimes. Time-dependent configuration interaction (TDCI) is unique among RT methods in that it may be implemented in a basis of eigenstates, allowing for rapid propagation of the time-dependent Schrödinger equation. The recent spin–orbit TDCI (TD-SOCI) enables a real-time description of spin-flip dynamics in an arbitrary EMF and, therefore, provides an ideal framework for rational pulse design. The present study explores the mechanism of multiple spin-flip pathways for a model transition metal complex, FeCO, using shaped pulses designed to drive controlled intersystem crossing and charge transfer. These results show that extremely tunable excited state dynamics can be achieved by considering the dipole transition matrix elements between the states of interest.

Chemistry↗

Outer atmospheres of cool stars. XIV - A model for the chromosphere and transition region of Beta Ceti (G9.5 III)

In the present chromospheric and transition region model for Beta Ceti, which is consistent with IUE spectra of the Mg II, C II, and C IV resonance lines, the Mg II h and k lines are treated in partial redistribution and the C II and C IV lines in complete redistribution. Computed line fluxes are presented for a range of models to show the range of permitted temperature structures. A comparison of the Beta Ceti model to models previously computed in a similar way for other stars shows a trend of decreasing chromospheric pressures and increasing geometric scales as single stars evolve across the transition region boundary. The present analysis also suggests that transition region pressures drastically decrease and geometric scales rapidly increase as single giant stars evolve to the right, toward the boudnary. Beta Ceti's exceptional X-ray brightness is discussed.

Eriksson, K.↗

Utilizing Direct Numerical Simulations of Transition and Turbulence in Design Optimization

Design optimization methods that use the Reynolds-averaged Navier-Stokes equations with the associated turbulence and transition models, or other model-based forms of the governing equations, may result in aerodynamic designs with actual performance levels that are noticeably different from the expected values because of the complexity of modeling turbulence/transition accurately in certain flows. Flow phenomena such as wake-blade interaction and trailing edge vortex shedding in turbines and compressors (examples of such flows) may require a computational approach that is free of transition/turbulence models, such as direct numerical simulations (DNS), for the underlying physics to be computed accurately. Here we explore the possibility of utilizing DNS data in designing a turbine blade section. The ultimate objective is to substantially reduce differences between predicted performance metrics and those obtained in reality. The redesign of a typical low-pressure turbine blade section with the goal of reducing total pressure loss in the row is provided as an example. The basic ideas presented here are of course just as applicable elsewhere in aerodynamic shape optimization as long as the computational costs are not excessive.

Direct numerical simulations of transition and tur↗

Applying AI tools to operational space environmental analysis

The U.S. Air Force and National Oceanic Atmospheric Agency (NOAA) space environmental operations centers are facing increasingly complex challenges meeting the needs of their growing user community. These centers provide current space environmental information and short term forecasts of geomagnetic activity. Recent advances in modeling and data access have provided sophisticated tools for making accurate and timely forecasts, but have introduced new problems associated with handling and analyzing large quantities of complex data. AI (Artificial Intelligence) techniques have been considered as potential solutions to some of these problems. Fielding AI systems has proven more difficult than expected, in part because of operational constraints. Using systems which have been demonstrated successfully in the operational environment will provide a basis for a useful data fusion and analysis capability. Our approach uses a general purpose AI system already in operational use within the military intelligence community, called the Temporal Analysis System (TAS). TAS is an operational suite of tools supporting data processing, data visualization, historical analysis, situation assessment and predictive analysis. TAS includes expert system tools to analyze incoming events for indications of particular situations and predicts future activity. The expert system operates on a knowledge base of temporal patterns encoded using a knowledge representation called Temporal Transition Models (TTM's) and an event database maintained by the other TAS tools. The system also includes a robust knowledge acquisition and maintenance tool for creating TTM's using a graphical specification language. The ability to manipulate TTM's in a graphical format gives non-computer specialists an intuitive way of accessing and editing the knowledge base. To support space environmental analyses, we used TAS's ability to define domain specific event analysis abstractions. The prototype system defines events covering reports of natural phenomena such as solar flares, bursts, geomagnetic storms, and five others pertinent to space environmental analysis. With our preliminary event definitions we experimented with TAS's support for temporal pattern analysis using X-ray flare and geomagnetic storm forecasts as case studies. We are currently working on a framework for integrating advanced graphics and space environmental models into this analytical environment.

Krajnak, Mike↗

The Effect of Trailing Edge Grid Resolution in Large-Eddy Simulations

Ceramic Matrix Composite (CMC) with environmental barrier coating can tolerate significantly higher temperatures compared with the conventional metal alloy blades and thus can help achieve higher thermal efficiency in gas turbine engines. Due to the complex fabrication process of CMC blades, larger blade trailing edge thicknesses and larger leading-edge radii of curvature are expected. These features significantly alter aerodynamic performance especially near the trailing edge and thus the loss profile. In previous studies, the authors used the large eddy simulation (LES) as well as the Reynolds Averaged Navier-Stokes (RANS) coupled with an intermittency function-based transition model to simulate an aerodynamics performance of three different CMC blades and compared the predictions against the data acquired at NASA Glenn Transonic Turbine Blade Cascade Rig. Although we were able to successfully predict different characteristics of aerodynamic performance among three different blades (e.g., pressure loading and integrated losses), LES consistently predicted a small recirculation bubble at the end of the suction side. This was not inconsistent with the physics of the flow, but the pressure loading, locally, near the trailing edge, and as a result, the measured wake profiles did not match the experimental data. To delve further into these issues, a new LES grid with a much finer mesh near the trailing edge was generated where the spanwise extent of the grid was increased by 50%. An LES simulation for the CMC blade with the largest trailing edge thicknesses at the high-freestream turbulence (Tu=13%) condition showed that using such a mesh is necessary for LES to accurately capture the transition phenomena on the suction side. The resulting total pressure coefficient profile and the shift of the wake profile were greatly improved.

CMC↗

The Effect of Trailing Edge Grid Resolution in Large-Eddy Simulations

Ceramic Matrix Composite (CMC) with environmental barrier coating can tolerate significantly higher temperatures compared with the conventional metal alloy blades and thus can help achieve higher thermal efficiency in gas turbine engines. Due to the complex fabrication process of CMC blades, larger blade trailing edge thicknesses and larger leading-edge radii of curvature are expected. These features significantly alter aerodynamic performance especially near the trailing edge and thus the loss profile. In previous studies, the authors used the large eddy simulation (LES) as well as the Reynolds Averaged Navier-Stokes (RANS) coupled with an intermittency function-based transition model to simulate an aerodynamics performance of three different CMC blades and compared the predictions against the data acquired at NASA Glenn Transonic Turbine Blade Cascade Rig. Although we were able to successfully predict different characteristics of aerodynamic performance among three different blades (e.g., pressure loading and integrated losses), LES consistently predicted a small recirculation bubble at the end of the suction side. This was not inconsistent with the physics of the flow, but the pressure loading, locally, near the trailing edge, and as a result, the measured wake profiles did not match the experimental data. To delve further into these issues, a new LES grid with a much finer mesh near the trailing edge was generated where the spanwise extent of the grid was increased by 50%. An LES simulation for the CMC blade with the largest trailing edge thicknesses at the high-freestream turbulence (Tu=13%) condition showed that using such a mesh is necessary for LES to accurately capture the transition phenomena on the suction side. The resulting total pressure coefficient profile and the shift of the wake profile were greatly improved.

LES↗

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗

Nickel-rich Nickel Manganese Cobalt (NMC622) Cathode Lithiation Mechanism and Extended Cycling Effects Using Operando X-ray Absorption Spectroscopy

Ni-rich NMC materials are a particularly promising class of Li-ion cathodes for various applications. LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) offers a unique balance of thermal stability and energy density, thus attracting attention for electric vehicle implementation. However, upon extended cycling, capacity fade is prevalent due to structural degradation, which is a major drawback for layered oxide cathodes. Therefore, exploring the underlying phenomena that drive detrimental structural response can lead to future improvements. For the first time, operando X-ray absorption spectroscopy (XAS) was performed on NMC622 pouch cells at three different stages. An extensive description of the first cycle (de)lithiation mechanisms was achieved through X-ray absorption near-edge structure analyses and extended X-ray absorption fine structure modeling. Transition metal specific electrochemical participation and structural variation revealed that much of the delivered capacity and distortion is a result of Ni redox behavior, while the local structure of Co and Mn are impacted due to their interdependencies. Key mechanistic components were identified, as the local structural variation from redox processes and Ni 3+ Jahn–Teller distortion were decoupled. Further, operando XAS was used to investigate the structural response of NMC622 to extended cycling and was supported by X-ray diffraction, X-ray photoelectron spectroscopy, and electrochemical impedance spectroscopy analyses. In this work, reduced capacity was found in the cell after 100 cycles and is attributed to structural degradation and cathode–electrolyte interphase buildup from repeated Li (de)insertion processes, which limit the electrochemical reversibility of Ni and Co through increased polarization. These results expand the understanding of a Ni-rich NMC material under extended cycling, which is vital to the future design of electrode materials.

25 ENERGY STORAGE↗

Manipulating topological Hall-like signatures by interface engineering in epitaxial ruthenate/manganite heterostructures

Topologically protected non-trivial spin textures (e.g. skyrmions) give rise to a novel phenomenon called the topological Hall effect (THE) and have promising implications in future energy-efficient nanoelectronic and spintronic devices. Here, we have studied the Hall effect in SrRuO 3 /La 0.42 Ca 0.58 MnO 3 (SRO/LCMO) bilayers. Our investigation suggests that pure SRO has hard and soft magnetic characteristics but the anomalous Hall effect (AHE) in SRO is governed by the high coercivity phase. Here, we have shown that the proximity effect of a soft magnetic LCMO on SRO plays a critical role in interfacial magnetic coupling and transport properties in SRO. Upon reducing the SRO thickness in the bilayer, the proximity effect becomes the dominant feature, enhancing the magnitude and temperature range of THE-like signatures. The THE-like features in bilayers can be explained by a diffusive Berry phase transition model in the presence of an emergent magnetic state due to interface coupling. This work provides an alternative understanding of THE-like signatures and their manipulation in SRO-based heterostructures, bilayers and superlattices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Properties of 187 Ta Revealed through Isomeric Decay

Mass-separated 187 Ta114 in a high-spin isomeric state has been produced for the first time by multi-nucleon transfer reactions, employing an argon gas stopping cell and laser ionisation. Here, internal $γ$ rays revealed a $T$ 1/2 = 7.3±0.9 s isomer at 1778±1 keV, which decays through a rotational band with perturbations associated with the approach to a prolate-oblate shape transition. Model calculations show less influence from triaxiality compared to heavier elements in the same mass region. The isomer decay reduced $E$2 hindrance factor, $f$ $ν$ = 27±1, supports the interpretation that axial symmetry is approximately conserved.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

First Measurement of Missing Energy due to Nuclear Effects in Monoenergetic Neutrino Charged-Current Interactions

We present the first measurement of the missing energy due to nuclear effects in monoenergetic, muon neutrino charged-current interactions on carbon, originating from 𝐾 + → 𝜇 + ⁢𝜈 𝜇 decay at rest (𝐸 𝜈 𝜇 = 235.5 MeV), performed with the J-PARC Sterile Neutrino Search at the J-PARC Spallation Neutron Source liquid scintillator based experiment. Toward characterizing the neutrino interaction, ostensibly 𝜈 𝜇 ⁢𝑛 → 𝜇 − ⁢𝑝 or 𝜈 𝜇 ⁢ 12 C → 𝜇 − ⁢ 12 N, we define the missing energy as the energy transferred to the nucleus (𝜔) minus the kinetic energy of the outgoing proton(s), 𝐸 𝑚 ≡ 𝜔−∑ 𝑇 𝑝 , and relate this to visible energy in the detector, 𝐸 𝑚 = 𝐸 𝜈 𝜇 ⁡(235.5 MeV) − 𝑚 𝜇⁡ (105.7 MeV) + [𝑚 𝑛 − 𝑚 𝑝⁡ (1.3 MeV)] − 𝐸 vis . The missing energy, which is naively expected to be zero in the absence of nuclear effects (e.g., nucleon separation energy, Fermi momenta, and final-state interactions), is uniquely sensitive to many aspects of the interaction, and has previously been inaccessible with neutrinos. The shape-only, differential cross section measurement reported, based on a (77 ± 3)% pure double-coincidence kaon decay-at-rest signal (621 total events), provides detailed insight into neutrino-nucleus interactions, allowing even the nuclear orbital shell of the struck nucleon to be inferred. The measurement provides an important benchmark for models and event generators at hundreds of MeV neutrino energies, characterized by the difficult-to-model transition region between neutrino-nucleus and neutrino-nucleon scattering, and relevant for applications in nuclear physics, neutrino oscillation measurements, and Type-II supernova studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Mauka Energy FEVER Tool Dataset

Mauka Energy’s dataset, developed under the Forestry Electric Vehicle Energy Routing (FEVER) project and funded by the U.S. Department of Energy’s Small Business Innovation Research program, is a high-resolution geospatial resource designed to support energy modeling for electric log trucks in complex forestry environments. The dataset integrates detailed spatial and road network data to enable accurate simulation of vehicle performance across varied terrain. At its core, the dataset incorporates lidar-derived elevation models, road alignments, and surface classifications from Oregon State University’s McDonald-Dunn Research Forest. These data capture fine-scale variations in slope, curvature, and surface conditions across forest road systems, allowing for vehicle-level analysis of energy consumption and recovery. The dataset also includes data collected on the surrounding public and private road networks in Benton County, Oregon, used in real-world haul routes. These connecting segments provide critical context for modeling transitions between forest operations and regional transportation infrastructure, incorporating attributes such as grade profiles, elevation change, and speed constraints. This combined dataset underpins the development of Mauka Energy’s rolldown tool, which quantifies energy use and regenerative braking potential on downhill and variable-grade segments. By leveraging high-resolution terrain and road data, the FEVER project enables more accurate assessment of electric vehicle feasibility and performance in forestry applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advanced Fuel Cycle Cost Basis Report: Supporting Document 5 Considerations on Learning

Learning refers here to the increased experience associated to each new build of a given type of fuel cycle facility, which results generally in design improvements, increased construction and operational efficiencies and reduced mistakes, and therefore in reduced costs. These are important considerations, for example, when modeling transitions from first-of-a-kind (FOAK) to nth-of-a-kind (NOAK) nuclear facilities and deciding the magnitude of the cost reduction (if any) to be applied to each successive build. Different assumptions on learning can significantly affect the results of the economic analyses during transitions. Other competing electricity-generation technologies, such as wind and solar power for example, have demonstrated substantial cost reductions through learning during the last few decades.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Strategic Condition Framework for Energy Innovation

Building upon previous work in innovation, technology, and economic fields, we propose a conceptual framework to address the interplay dynamics of public policy and the value chains of clean energy technology innovation systems, by focusing on market structural and strategic conditions in relation to the rate and direction of knowledge diffusion within activity-based value chains. Our framework extends beyond socio-technical transition models by considering such nuances as: 1) the implications of geography, 2) the locus of knowledge types, 3) the dynamics of financial and knowledge flow, and 4) emphasizing the importance of both market structure and institutional conditions. At the firm level, we consider dynamics of interactions between suppliers and customers, innovation activities, the competitive environment, and the firm’s broader strategic relationship to governance activities and structures; we allow for the fact that each of these aspects of a firm’s identity may have a strategically relevant geographic dimension (e.g., service territories, locational concentration of input resources, etc.). We provide a proof-of-concept application of the U.S. utility-scale solar photovoltaic (PV) and onshore wind sectors, including their interactions with the U.S. power market, which we in present in a web-based information platform (Energy I-SPARK, ei-spark.lbl.gov).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗