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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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At least 865 records · Page 48

Transmission Data-Driven User-Defined Model for Inverter-based and Conventional Power Plants

Recent events in Odessa [1], [2] have shed light on the complexities of integrating large Inverter-Based Resource (IBR) plants with the transmission system, prompting NERC to stress continuous performance monitoring by transmission operators. Challenges such as plant control updates, IBR model revisions, Phase-locked loop loss of synchronism, and protection events have been identified, underscoring the need for enhanced monitoring protocols by regulatory bodies. The recent FERC 901 order underscores the importance of accurate data exchange regarding IBRs for reliability studies. However, limited access to IBR plant-related data hampers effective decision-making for transmission operators (TOP). This paper proposes a method for constructing data-driven User-Defined dynamic Models (UDM) for power plants for validating multiple-event data using field measurements from interconnection bus locations. The problem is formulated as a power plant model identification problem and a multi-task learning approach under partial input observability assumptions is proposed in this work. This approach aims to predict aggregated responses of conventional and IBR power plants during various dynamic physical events which is useful for planning studies under diverse disturbance conditions. Ultimately, this methodology emphasizes the importance of plant visibility to operators in addressing power system challenges, facilitating improved planning and operational studies.

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗

Seeking Repeating Anthropogenic Seismic Sources: Implications for Seismic Velocity Monitoring at Fault Zones

Abstract Seismic velocities in rocks are highly sensitive to changes in permanent deformation and fluid content. The temporal variation of seismic velocity during the preparation phase of earthquakes has been well documented in laboratories but rarely observed in nature. It has been recently found that some anthropogenic, high‐frequency (>1 Hz) seismic sources are powerful enough to generate body waves that travel down to a few kilometers and can be used to monitor fault zones at seismogenic depth. Anthropogenic seismic sources typically have fixed spatial distribution and provide new perspectives for velocity monitoring. In this work, we propose a systematic workflow to seek such powerful seismic sources in a rapid and straightforward manner. We tackle the problem from a statistical point of view, considering that persistent, powerful seismic sources yield highly coherent correlation functions (CFs) between pairs of seismic sensors. The algorithm is tested in California and Japan. Multiple sites close to fault zones show high‐frequency CFs stable for an extended period of time. These findings have great potential for monitoring fault zones, including the San Jacinto Fault and the Ridgecrest area in Southern California, Napa in Northern California, and faults in central Japan. However, extra steps, such as beamforming or polarization analysis, are required to determine the dominant seismic sources and study the source characteristics, which are crucial to interpreting the velocity monitoring results. Train tremors identified by the present approach have been successfully used for seismic velocity monitoring of the San Jacinto Fault in previous studies.

58 GEOSCIENCES↗

Engineering microstructure to improve coercivity of bulk MnBi magnet

MnBi is a candidate material for high-temperature magnets because of its increasing coercivity with increasing temperatures up to 255 °C. However, most efforts in fabricating bulk MnBi magnets have run into the problem of preserving the coercivity (H cj) of its feedstock powders. About 70% of powder’s H cj would be lost during the densification process. Our micromagnetic modeling shows that the coercivity mechanism of the MnBi bulk magnet is controlled by nucleation of the reversal magnetization domains, and the large H cj loss that occurred during the powder consolidation process can be attributed to the inter-grain magnetic coupling. To attain a high H cj , the grains in the MnBi bulk magnet must be separated with a non-magnetic grain boundary phase (GBP). To validate this GBP hypothesis, we engineered MnBi bulk magnets with two different types of GBP. The first type of GBP was created in-situ by precipitating excessive Bi from the grains; the second type was created ex-situ by coating silicates on the feedstock powders before the consolidation. While both GBP work, the ex-situ approach resulted in a better H cj due to a more uniform GBP distribution. We report the H cj loss was reduced from 70% to 15%, and the (BH)max of a warm sintered bulk magnet reached 8.9 MGOe.

36 MATERIALS SCIENCE↗

A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery

Abstract Material properties share an intrinsic relationship with their structural attributes, making inverse design approaches crucial for discovering new materials with desired functionalities. Reinforcement Learning (RL) approaches are emerging as powerful inverse design tools, often functioning in discrete action spaces. This constrains their application in materials design problems, which involve continuous search spaces. Here, we introduce an RL-based framework CASTING (Continuous Action Space Tree Search for inverse design), that employs a decision tree-based Monte Carlo Tree Search (MCTS) algorithm with continuous space adaptation through modified policies and sampling. Using representative examples like Silver (Ag) for metals, Carbon (C) for covalent systems, and multicomponent systems such as graphane, boron nitride, and complex correlated oxides, we showcase its accuracy, convergence speed, and scalability in materials discovery and design. Furthermore, with the inverse design of super-hard Carbon phases, we demonstrate CASTING’s utility in discovering metastable phases tailored to user-defined target properties and preferences.

36 MATERIALS SCIENCE↗

Partitioning of Complex Fluids at Mineral Surfaces

This report summarizes the results obtained during the LDRD project entitled "Partitioning of Complex Fluids at Mineral Interfaces." This research addressed fundamental aspects of such interfaces, which are relevant to energy-water applications in the subsurface, including fossil energy extraction and carbon sequestration. This project directly addresses the problem of selectivity of complex fluid components at mineral-fluid interfaces, where complex fluids are defined as a mixture of hydrophobic and hydrophilic components: e.g., water, aqueous ions, polar/nonpolar organic compounds. Specifically, this project investigates how adsorption selectivity varies with surface properties and fluid composition. Both experimental and molecular modeling techniques were used to better understand trends in surface wettability on mineral surfaces. The experimental techniques spanned the macroscale (contact angle measurements) to the nanoscale (cryogenic electronic microscopy and vibrational spectroscopy). We focused on an anionic surfactant and a well-characterized mineral phase representative of clay phases present in oil- and gas-producing shale deposits. Collectively, the results consistently demonstrate that the presence of surfactant in the aqueous fluid significantly affects the mineral-fluid interfacial structure. Experimental and molecular modeling results reveal details of the surfactant structure at the interface, and how this structure varies with surfactant coverage and fluid composition.

04 OIL SHALES AND TAR SANDS↗

thornado+FLASH-X: A Hybrid Discontinuous Galerkin–Implicit-explicit and Finite-volume Framework for Neutrino-radiation Hydrodynamics in Core-collapse Supernovae

We present neutrino-transport algorithms implemented in the toolkit for high-order neutrino-radiation hydrodynamics (thornado) and their coupling to self-gravitating hydrodynamics within the adaptive mesh refinement–based multiphysics simulation framework FLASH-X. thornado, developed primarily for simulations of core-collapse supernovae (CCSNe), employs a spectral, six-species two-moment formulation with algebraic closure and special-relativistic observer corrections accurate to $\mathcal{O}(v/c)$, and uses discontinuous Galerkin (DG) methods for phase-space discretization combined with implicit-explicit time stepping. A key development is a nonlinear neutrino–matter coupling algorithm based on nested fixed-point iteration with Anderson acceleration, enabling fully implicit treatment of collisional processes, including energy-coupling interactions such as neutrino–electron scattering and pair production. Coupling to finite-volume (FV) hydrodynamics is achieved through a hybrid DG-FV representation of the fluid variables and operator-split evolution within FLASH-X. The implementation is verified using basic transport tests with idealized opacities and relaxation and deleptonization problems with tabulated microphysics. Spherically symmetric CCSN simulations demonstrate accuracy and robustness of the coupled scheme, including close agreement with the CCSN simulation code Chimera. An axisymmetric CCSN simulation further demonstrates the viability of DG-based neutrino transport for multidimensional supernova modeling within FLASH-X. thornado’s neutrino-transport solver is GPU-enabled using OpenMP offloading or OpenACC, and all CCSN applications included in this work use the GPU implementation. Together, these results establish a foundation for future enhancements in physics fidelity, numerical algorithms, and computational performance, for increasingly realistic large-scale CCSN simulations.

Endeve, Eirik [Oak Ridge National Laboratory (ORNL↗

Final Report: Next Generation Diamond Drumhead X-Ray Optics

Problem / Opportunity Statement: Future high-impact scientific applications at synchrotron and Free-Electron Laser (FEL) X-ray sources require the development of processing and mounting methods for ultra-thin diamond crystals to meet the most challenging needs of pioneering research at next generation light source facilities. These methods should be capable of manufacturing crystal plates as thin as 10 micrometers over an area of a few mm2, and with a surface cut in different crystal orientations, such as the diamond {100}, {111}, {110} and {113} planes. Project Purpose and Approach: In Phase I, Great Lakes Crystal Technologies (GLCT) partnered with Stonybrook University (SUNY) to created thin diamond drumhead crystals. The purpose of the Phase I project is to transfer the drumhead membrane window etching technology from SUNY to GLCT. Testing of a device using the beamline at Stanford Linear Accelerator Laboratory was initially planned, however, a delay on the part of a third party service provided required us to get beamline testing done at Argonne National Laboratory. Phase I Taskwork: Testing of a high purity diamond plate thinning and etching process was performed. By SUNY and GLCT. Plates were sent to a third party service provider for thinning to ~100 microns, however, delays required that GLCT develop an in-house thinning process to complete the taskwork. GLCT successfully developed this in-house capability even though it was initially planned to be part of the Phase II Taskwork. Multiple practice and deliverable plates were provided to SUNY to be etched into the target drumhead devices. GLCT practiced and refined an in-house plate thinning process and produced five plates with thicknesses in the 60 – 150 micron range. Processing of the plates has begun and will continue in a no-cost extension period necessitated by the third party service provider delay. GLCT also procured and installed a reactive ion etching/inductively coupled plasma system. In addition, one of the thinned plates was measured at the Applied Photon Source at APL for a pre-processing assessment of the crystalline strain. After processing the plate into a drumhead and annealing, a post-processing assessment of the strain will be performed. Phase I Results: The initial data from GLCT’s plate thinning process development, SUNY’s drumhead etching processing, and characterization at APS/ANL demonstrate our teams capabilities to achieve the project goals. Commercial Applications & Benefits: The proposed technology will benefit advanced x-ray science performed at BNL and the 70+ additional advanced beamlines around the world. There are also a number of medical and homeland security applications which could benefit from the technology.

Quayle, Paul↗

Molecular thermodynamics for scaling prediction: Case of membrane distillation

Membrane distillation (MD) for water treatment is significantly impaired by the scaling of dissolved minerals. The type and content of minerals generally measured as total dissolved solids (TDS) in hypersaline brines not only reduce the MD flux but also control the scaling behavior on the membrane surface. The scaling-induced pore blockage further reduces water flux and eventually leads to membrane wetting. The scaling problem is even more pronounced in the treatment of produced water (PW) as it contains 3–7 times higher TDS concentrations, compared to seawater. Theoretically, the necessary conditions for a salt to precipitate can be traced from its solubility product constant and activity of the constituents within the solution. Therefore, a comprehensive thermodynamic model is necessary to represent the electrolyte behavior and to predict the precipitation of different salts in a complex solution like PW. We pursued electrolyte Nonrandom Two Liquid Theory (eNRTL), a state-of-the-art electrolyte model, to address the PW fluid phase equilibria. With a fully parameterized eNRTL model, we predicted salt precipitations in two different PW samples and compared the results against the experimental findings. Furthermore, here we forecast the precipitation of salts in response to the change in PW concentration and temperature in the MD operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sign-free determinant quantum Monte Carlo study of excitonic density orders in a two-orbital Hubbard-Kanamori model

While excitonic instabilities in multiorbital systems recently have come under scrutiny in a variety of transition-metal compounds, understanding emergence of these instabilities from strong electronic interactions has remained a challenge. In this work, we present a sign-problem-free determinant quantum Monte Carlo study of excitonic density orders in a half-filled two-orbital Hubbard-Kanamori model with broken orbital degeneracy, which accounts for the role of Hund's coupling in transition-metal compounds. For strong inverted (negative) Hund's exchange, we find numerical evidence for the emergence of excitonic density order, with competition between anti-ferro-orbital order and Q = (π, π) excitonic density order as a function of orbital splitting and Hund's coupling. While inverted Hund's coupling stabilizes a spin-singlet excitonic density phase for weak orbital splitting, positive Hund's coupling favors a spin-triplet excitonic density phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Localized modes in the IR phase of QCD

Infrared (IR) dimension function d IR ( λ ) characterizes the space effectively utilized by QCD quarks at Dirac scale λ , and indirectly the space occupied by glue fields. It was proposed that its nonanalytic behavior in thermal reflects the separation of QCD system into an IR component and an independent bulk. Here we study the “plateau modes” in the IR component, whose dimensional properties were puzzling. Indeed, in the recent scenario of transition to IR phase, this low-dimensional plateau connects the Anderson-like mobility edge λ IR = 0 in Dirac spectrum with mobility edges ± λ A . For this structure to be truly Anderson-like, plateau modes have to be exponentially localized, implying that both the effective distances L eff ∝ L γ and the effective volumes V eff ∝ L d IR in these modes grow slower than any positive power of IR cutoff L . Although γ = 0 was confirmed in the plateau, it was found that d IR ≈ 1 . Here we apply the recently proposed technique to the problem. We conclude that a plateau mode of pure-glue QCD at UV cutoff a = 0.085 fm occupies a subvolume of IR dimension zero with probability at least 0.9999, substantiating this aspect of metal-to-critical scenario to a respective degree. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Spatial-Temporal PV Hosting Capacity Estimation and Evaluation

Evaluating Photovoltaic Hosting Capacity (PVHC) is an essential step in the process of integrating solar energy into power grids, particularly when focusing on the distribution network (DN) as the primary integration target. PVHC needs to be investigated, especially in cases where the grids are unbalanced, and their operational conditions vary spatially and temporally. This motivation prompted us to propose a scalable model tailored to this application. In this paper, we applied linearization to the alternating current optimal power flow (AC-OPF) and solar inverters, transforming the original problem into a mixed-integer linear programming (MILP) problem. Additionally, we accounted for the battery energy storage system (BESS) as a time-coupling factor for calculating PVHC. We then compared the PVHC results between the IEEE-13 bus and SMART-DS San Francisco (SFO) cases and discussed the extent to which BESS can enhance the PVHC of a DN. Furthermore, we designed a web-based graphical visualization for the SFO case, enabling user interaction with raw data and simulation results on a map through a graphical user interface (GUI). In summary, our results and findings provide valuable insights for future three-phase unbalanced AC-OPF PVHC practices and their visualization.

AC-optimal power flow↗

Challenges and Prospects of Sodium‐Ion and Potassium‐Ion Batteries for Mass Production

The exponential growth of the lithium‐ion (LIB) market is causing a significant disparity between the supply chain and demand for its resources. In this regard, sodium‐ion and potassium‐ion batteries are promising alternatives to LIBs due to their low cost. However, the larger sizes of Na + and K + ions create challenges that prevent them from achieving energy densities comparable to LIBs while maintaining an acceptable cycle life. Here, in this perspective, the aim is to evaluate the status of Na‐ion and K‐ion batteries and the challenges associated with them on both fundamental and commercial levels. The focus is on the structural instability arising from phase transitions during cycling, intricate chemical degradation processes, and potential avenues for enhancing their performance with a specific goal of improving their viability for grid‐scale energy storage. Materials production and abundance limitations for the chemistries of the state‐of‐the‐art materials and account for critical parameters from both the perspective of researchers and investors are analyzed. This analysis aims to provide insights into the strategic trade‐offs required to effectively implement the technology in real‐world applications, such as grid‐scale storage and other areas. Furthermore, the utilization of metals with low or no supply‐chain problems as an important aspect of these trade‐offs is considered.

25 ENERGY STORAGE↗

Interfacial characteristics of P91 steel - Inconel 740H bimetallic structure fabricated using wire-arc additive manufacturing

Although bimetallic structures can offer unique solutions to engineering problems with varying functionality, joining two dissimilar alloys using additive manufacturing involves challenges such as cracking and segregation. In this work, bimetallic structures of Inconel 740H superalloy and P91 steel are processed using wire-arc additive manufacturing (WAAM) for the first time. P91 steel is directly deposited over 740H with a cooling time of 20 minutes in between the two depositions. During microstructure characterization, a large gradient zone with coarse grains spanning for ~2200 μm is observed. Moreover, the microhardness of the gradient zone is the least in comparison with the P91 and 740H deposits. No deleterious phase formation is found; however, intergranular cracks are observed along the gradient zone. In order to deduce the reason for cracking, non-equilibrium solidification simulations are performed for the mixed compositions of P91 and 740H in the gradient zone. Here, the reasons for crack formation in the gradient zone are the sudden change in the volumetric coefficient of thermal expansion due to the formation of MC carbides as well as the development of local strains from the thermal residual stresses. Therefore, altering the deposition sequence and introducing gradient layers with mixed composition between the P91 and 740H deposits will be beneficial in achieving defect-free builds. Through the integration of experiments and simulation, this work gains valuable insights into the processability of dissimilar alloy manufacturing using the WAAM technique.

20 FOSSIL-FUELED POWER PLANTS↗

In Situ Neutron Scattering Study of the Structure Dynamics of the Ru/Ca 2 N:e – Catalyst in Ammonia Synthesis

NH 3 synthesis is one of the most critical industrial processes. Compared to commercial iron catalysts, Ru catalysts show high intrinsic activity in this reaction but suffer from hydrogen poisoning. By loading Ru onto supports such as electrides and hydrides, the hydrogen poisoning problem can be significantly alleviated. However, relevant studies on the structural dynamics of the Ru/electride catalysts under reaction conditions are very scarce. Taking advantage of the high sensitivity to hydrogen species, it is possible to obtain insights into the structural changes during the reaction using in situ neutron techniques. In this study, we have investigated the structural evolution of the Ru/Ca 2 N:e – catalyst during the ammonia synthesis reaction by in situ neutron scattering (inelastic neutron scattering, INS) technique. In situ INS experiments suggest that Ca 2 N:e – is likely converted to the Ca 2 NH phase during the reaction. Unlike the previously known structure where H and N atoms are intermixed, the formed Ca 2 NH exhibits a segregated structure where the H and N atoms are located in different layers separated by the Ca layer. In conclusion, density functional theory calculations of the reaction energetics reveal that there are minor changes in the barriers and thermodynamics of the first N hydrogenation step between the two phases (Ca 2 NH phase with segregated H/N layers and intermixed Ca 2 NH phase), suggesting the impact of the phases on the reaction kinetics to be relatively minimal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dissecting subcycle interference in photoelectron holography

Multipath holographic interference in strong-field quantum tunnel ionization is key to revealing subangstrom attosecond dynamics for molecular movies. This critical subcycle motion is often obscured by longer timescale effects such as ring-shaped patterns that appear in above-threshold ionization (ATI). In the present work, we overcome this problem by combining two techniques in theory and experimental analysis: unit-cell averaging and time-filtering data and simulations. Together these suppress ATI rings and enable an unprecedented highly detailed quantitative match between strong-field ionization experiments in argon and the Coulomb-quantum orbit strong-field approximation (CQSFA) theory. Velocity map images reveal fine modulations on the holographic spiderlike interference fringes that form near the polarization axis. CQSFA theory traces this to the interference of three types of electron pathways. The level of agreement between experiment and theory allows sensitive determination of quantum phase differences and symmetries, providing an important tool for quantitative dynamical imaging in quantum systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

Random insights into the complexity of two-dimensional tensor network calculations

Projected entangled pair states (PEPS) offer memory-efficient representations of some quantum many-body states that obey an entanglement area law and are the basis for classical simulations of ground states in two-dimensional (2d) condensed matter systems. However, rigorous results show that exactly computing observables from a 2d PEPS state is generically a computationally hard problem. Yet approximation schemes for computing properties of 2d PEPS are regularly used, and empirically seen to succeed, for a large subclass of (“not too entangled”) condensed matter ground states. Adopting the philosophy of random matrix theory, in this work, we analyze the complexity of approximately contracting a 2d random PEPS by exploiting an analytic mapping to an effective replicated statistical mechanics model that permits a controlled analysis at a large bond dimension. Through this statistical-mechanics lens, we argue that (i) although approximately sampling wave-function amplitudes of random PEPS faces a computational-complexity phase transition above a critical bond dimension, and (ii) one can generically efficiently estimate the norm and correlation functions for any finite bond dimension. Furthermore, these results are supported numerically for various bond-dimension regimes. It is an important open question whether the above results for random PEPS apply more generally also to PEPS representing physically relevant ground states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Inverse design for waveguide dispersion with a differentiable mode solver

Inverse design of optical components based on adjoint sensitivity analysis has the potential to address the most challenging photonic engineering problems. However, existing inverse design tools based on finite-difference-time-domain (FDTD) models are poorly suited for optimizing waveguide modes for adiabatic transformation or perturbative coupling, which lies at the heart of many important photonic devices. Among these, dispersion engineering of optical waveguides is especially challenging in ultrafast and nonlinear optical applications involving broad optical bandwidths and frequency-dependent anisotropic dielectric material response. In this work, we develop gradient back-propagation through a general-purpose electromagnetic eigenmode solver and use it to demonstrate waveguide dispersion optimization for second harmonic generation with maximized phase-matching bandwidth. This optimization of three design parameters converges in eight steps, reducing the computational cost of optimization by ∼100x compared to exhaustive search and identifying new designs for broadband optical frequency doubling of laser sources in the 1.3–1.4 µm wavelength range. Furthermore, we demonstrate that the computational cost of gradient back-propagation is independent of the number of parameters, as required for optimization of complex geometries. This technique enables practical inverse design for a broad range of previously intractable photonic devices.

Gray, Dodd (ORCID:000000030469599X)↗