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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Spectroscopic evidence of intra-unit-cell charge redistribution in a charge-neutral magnetic topological insulator

The magnetic topological insulator MnBi 6 Te 10 has emerged as a promising candidate for realizing the quantum anomalous Hall effect (QAHE), owing to its ability to retain ferromagnetism through precise control of anti-site defects. The next important task for realizing the QAHE is to tune the chemical potential into the energy gap formed by the broken time-reversal symmetry. Here we reveal an intra-unit-cell charge redistribution even when the overall doping suggests a near-charge-neutral condition. By performing time- and angle-resolved photoemission spectroscopy (trARPES) on the optimally 18% Sb-doped MnBi 6 Te 10 , we observe transient surface photovoltage (SPV) effects on both the MnBi 2 Te 4 and single-Bi 2 Te 3 terminations. Furthermore, we observe a time-dependent splitting of the band structure indicating multiple SPV shifts with different magnitudes. This observation suggests that adjacent plateaus with nominally the same terminating layer exhibit a strong intra-unit-cell charge redistribution, resulting in spontaneous electrical polarization. This is consistent with static micro-ARPES measurements revealing significant doping deviations from the charge-neutral configuration. Our findings underscore the challenges of engineering the family of Mn-Bi-Te materials to realize QAHE purely through chemical doping. Achieving the desired topological quantum phase requires both a uniform carrier doping and a ferromagnetic ground state. Furthermore, the light-induced polarization within each unit cell of ferromagnetic Mn(Bi 0.82 Sb 0.18 ) 6 Te 10 may open new possibilities for optoelectronic and spintronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower (DIVERS-H)

U.S. hydropower plants face potential threats from shrinking water supply, rising demands, and warmer stream temperatures from various causes. Power plant owners, operators, and regulators require new tools to take advantage of and interpret the diverse range of scientific data being produced by both observational methods (for example, satellite, radar, stream gauges) and computer modeling methods that evaluate and predict how earth's dynamic systems (atmosphere, oceans, land surface, and sea ice) are changing and interacting. Combining datasets such as these with AI-based analyses introduces a novel decision support system to help users anticipate and address potential impacts on power generation stations. This new technology has been named DIVERS-H for "Data Integration and Visualization for Enhanced Resilience and Sustainability in Hydropower." In Phase I, technical feasibility was established with the development and demonstration of all the new technologies that are required. Most notably, DIVERS-H will use new artificial intelligence (AI) methods to capture the complex dynamics of water availability, demand, and environmental changes. In addition, new data management software was developed, and a prototype user interface was implemented as the precursor to a full scale decision support system. With technical research complete, the project focus now shifts to development of a commercial software product to provide users with actionable insight into water availability and the risk/resilience of critical systems at their locations of interest. Although DIVER-H was originally conceived as a tool for hydroelectric power applications, the same underlying technology can be readily applied to other water-consuming systems including coal, natural gas, oil, and nuclear power plants.

Chaudhary, Aashish [Kitware, Inc., Clifton Park, N↗
DOE OSTI2025

Challenge Problem 1: Preliminary Results of the Direct Numerical Simulation of Transient Flows

This report presents the first direct numerical simulations (DNS) of transient mixed convection in an idealized downcomer-like channel (Challenge Problem 1, Phase II). Using the GPU-accelerated NekRS solver, we modeled a sudden decay in driving pressure, mimicking loss-of-flow events, and tracked the resulting evolution of Reynolds number, boundary-layer structure, turbulence statistics, and heat-transfer metrics. Key findings include the systematic thickening and eventual asymmetry of velocity and thermal boundary layers under buoyant deceleration; minimal “memory” lag in Reynolds shear stress and TKE profiles when sampled at matching Re, yet clear shifts of peak locations toward the cooled wall; overshoots in transient eddy-viscosity and eddy-diffusivity (and corresponding sub-unity turbulent Prandtl numbers) on the cooled side; and a pronounced transient Nusselt-number enhancement driven by wall-temperature inertia and residual eddy mixing. These effects combined to offer a temporary cooling margin above steady-state predictions during reactor LOF transients. Future work will extend this work to a more complex “Case II” geometry (90° turn + lower plenum) and generate multi-Re/Pr datasets for data-driven turbulence closures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Frustration-driven magnetic correlations in the spin-$\frac{5}{2}$ triangular lattice antiferromagnet RbFe⁢(HPO 3 ) 2

Here, a detailed study of the structural and magnetic properties of a spin-5/2 triangular lattice antiferromagnet RbFe⁢(HPO 3 ) 2 is presented using x-ray diffraction, magnetization, heat capacity, and 31 P nuclear magnetic resonance (NMR) experiments on a polycrystalline sample. The crystal structure features an equilateral triangular lattice of Fe 3+ ions. The thermodynamic measurements reveal the onset of a magnetic long-range order at 𝑇 N⁢1 ≃7.8K in zero field, followed by another low-temperature field-induced ordering at 𝑇 N⁢2 in higher fields. The transition at 𝑇 N⁢1 is further confirmed from the NMR spin lattice relaxation measurements. The value of the frustration ratio (𝑓≃7) implies moderate spin frustration in the compound. The 31 P NMR spectra exhibit two distinct spectral lines corresponding to two inequivalent phosphorus sites (P1 and P2), consistent with the crystal structure. The P1 site is strongly coupled with an isotropic hyperfine coupling of 𝐴$^{iso}_{hf}$ = 0.55⁢(2)⁢ T/𝜇 B while the P2 site is weakly coupled with 𝐴$^{iso}_{hf}$ = 0.25⁢(3)⁢ T/𝜇 B with the Fe 3+ ions. The magnetic susceptibility and NMR shift data are described well assuming a spin-5/2 isotropic triangular lattice antiferromagnetic model with an average exchange coupling of 𝐽/𝑘 B = 2.8⁢(2)⁢K. Below 𝑇 N⁢1 , the spectra evolve into a nearly rectangular powder pattern, indicating a commensurate antiferromagnetic type order. The 31 P spin-lattice relaxation rate well below 𝑇N⁢1 follows a 𝑇 3 temperature dependence, implying a two-magnon Raman scattering mechanism in the ordered state. Three well-defined phase regimes are clearly ascertained in the 𝐻−𝑇 phase diagram, reflecting a weak magnetic anisotropy in the compound.

Nagpal, V. [Indian Institute of Science Education ↗
DOE OSTI2025

Atomic Structural Features of Stacking Faults and Domain Connections in the Li- and Mn-Rich Cathode

Li- and Mn-rich layered oxides (LMRs), a class of earth-abundant materials for rechargeable Li-ion battery cathodes, crystallize into layered structures of two different symmetries: C2/m represented by Li 2 MnO 3 and R$\overline{3}$m represented by LiMn 0.5 Ni 0.5 O 2 . Fundamental questions about how the C2/m and R$\overline{3}$m domains spatially correlate within the same oxide grain and how the C2/m stacking faults arrange themselves when this happens still remain. Here, by using integrated differential phase contrast imaging in scanning transmission electron microscopy (STEM-iDPC), we probe the structural and compositional details of a prototypical, cobalt-free LMR material, 0.3Li 2 MnO 3 •0.7LiMn 0.5 Ni 0.5 O 2 (Li 1.13 Mn 0.57 Ni 0.3 O 2 ). The connection between the C2/m and R$\overline{3}$m domains is found to be abrupt, facilitated by the small lattice mismatch between the two structures. Stacking faults in the C2/m domains feature atomic plane shifting that accommodates stacking sequence changes, which explains why the stacking faults form in a random manner. Furthermore, a local disordering mechanism was identified to correlate with the C2/m stacking faults. Chemically, it is found that Ni coexists with Mn at the transition metal sites within the nominal Li 2 MnO 3 domain. As a result, this study demonstrates that STEM-iDPC is a very useful tool for capturing all the elements in a single image, revealing atomic details on domain connections and stacking faults in the LMRs.

Li-rich and Mn-rich oxides↗
DOE OSTI2025

Modeling MTS pyrolysis and SiC deposition kinetics using principal component analysis and neural networks

Accurate chemical kinetics modeling is crucial for improving the efficiency of chemical processing and synthesis of ceramic matrix composites. Detailed kinetic models are computationally expensive due to the large number of transported chemical species, while the simplified physics-based models, such as single-step global mechanisms, are efficient but often overlook key chemical intermediates and pathways. Recent deep learning approaches promise accurate and cost-effective models. Yet, they require additional closures for the transported nonlinear latent variables, complicating integration with existing solvers. In this work, we develop a hybrid linear—nonlinear reduced model for silicon carbide deposition from methyltrichlorosilane precursor by combining principal component analysis (PCA) and autoencoder (AE) neural network (NN) approaches. PCA is used to identify a smaller set of linear transport variables, enabling direct reuse of conventional transport solvers. NNs then reconstruct the full chemical state from these reduced variables. We demonstrate the method on a chemical vapor deposition reactor—comprising a gas-phase pyrolysis plug flow reactor and a heterogeneous surface reactor—over a wide range of temperatures, pressures, and residence times. Our PCA–AE model achieves high accuracy with only five transported scalars, achieving an eightfold cost reduction compared to detailed mechanisms, in both a priori (using data from the test set only) and a posteriori (coupled with a differential equation solver). In conclusion, notable errors arise primarily near training domain boundaries and for long residence times, indicating the need for domain shift indicators and better long-horizon predictions in future reduced chemistry model development.

autoencoder neural networks↗
DOE OSTI2025

Outflowing photoionized plasma in Circinus X-1 using the high-resolution X-ray spectrometer Resolve onboard XRISM and the radiative transfer code cloudy

High-resolution X-ray spectroscopy is a key to understanding the mass inflow and outflow of compact objects. Spectral lines carry information about the ionization, density, and velocity structures through their intensity ratios and profiles. They are formed in non-local thermodynamic equilibrium conditions under the intense radiation field from the compact objects; thus radiative transfer (RT) calculation is a requisite for proper interpretations. We present such a study for a low-mass X-ray binary, Circinus X-1, from which the P Cygni profile was discovered using the X-ray grating spectrometer onboard Chandra. We observed the source using the X-ray microcalorimeter onboard XRISM at an orbital phase of 0.93–0.97 and revealed many spectral features unidentified before: the higher series transitions ($n{\rightarrow }1$; $n>2$) of highly ionized (H- and He-like) S, Ca, Ar, and Fe in emission and absorption, the Fe K$\alpha$ and K$\beta$ inner-shell excitation absorption of mildly ionized (O- to Li-like) Fe, and resolved fine-structure level transitions in the Fe Ly$\alpha$ and He$\alpha$ complexes. They blend with each other at different velocity shifts on top of apparently variable continuum emission that changed its flux by an order of magnitude within a 70 ks telescope time. Despite such complexity in the observed spectra, most of them can be explained by a simple model consisting of the photoionized plasma outflowing at $\sim$300 km s$^{-1}$ and the variable blocking material in the line of sight of the incident continuum emission from the accretion disk. We demonstrate this with the aid of the RT code cloudy for the line ratio diagnostics and spectral fitting. We further constrain the physical parameters of the outflow and argue that the outflow is launched close to the outer edge of the accretion disk and can be driven radiatively by being assisted by the line force calculated using the RT simulation.

X-rays: binaries↗
DOE OSTI2025

Measurements and models of enhanced recombination following inner-shell vacancies in liquid xenon

Electron-capture decays of 125 Xe and 127 Xe , and double-electron-capture decays of 124 Xe , are backgrounds in searches for weakly interacting massive particles (WIMPs) conducted by dual-phase xenon time projection chambers such as LUX-ZEPLIN (LZ). These decays produce signals with more light and less charge than equivalent-energy 𝛽 decays and correspondingly overlap more with WIMP signals. We measure three electron-capture charge yields in LZ: the 1.1 keV M-shell, 5.2 keV L-shell, and 33.2 keV K-shell at drift fields of 193 and 96.5 V/cm. The LL double-electron-capture decay of 124 Xe exhibits even more pronounced shifts in charge and light. We provide a first model of double-electron-capture charge yields using the link between ionization density and electron-ion recombination, and identify a need for more accurate calculations. Finally, we discuss the implications of the reduced charge yield of these decays and other interactions creating inner-shell vacancies for future dark matter searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Spin Correlations in the Parent Phase of Li 1–x Fe x ⁢ ODFeSe

Elucidating spin correlations in the parent compounds of high-temperature superconductors is crucial for understanding superconductivity. We used neutron scattering to study spin correlations in Li 1–x Fe x ⁢ ODFeSe, an insulating material with reduced electron carriers compared to its superconducting counterpart (T c = 41 K), serving as the undoped parent compound. Our findings show a reduced total fluctuating moment in this insulator relative to FeSe and 122 iron pnictides, likely due to increased interlayer distances from intercalation, which enhance fluctuations and reduce the intensity of spin excitations. Moreover, we observed a V-shaped spin wavelike excitation dispersion, contrasting with the twisted hourglass pattern in the superconducting counterpart. Electron doping shifts spin excitation from (π,0) point to an incommensurate position towards (π,π) direction below 65 meV. In conclusion, this transition from V-shaped to hourglasslike dispersion, akin to behaviors in hole-doped cuprates, suggests a potential shared mechanism in magnetism and superconductivity across these diverse systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Enhanced Manganese Oxidation at the Biofilm–Fluid Interface Drives Pore-Scale Patterns in Mineral Precipitation

Microbial oxidation of manganese (Mn) from aqueous Mn(II) to solid-phase Mn(III, IV) minerals catalyzes Mn(II) removal in natural and engineered porous systems. However, little is known about the spatiotemporal evolution of Mn biomineralization in confined spaces that experience simultaneous Mn(II) delivery and Mn oxide precipitation. Here, we combine time-lapse microscopy, image analysis, and mass spectrometry to quantify the extent and rate of Mn biomineralization by Pseudomonas putida GB-1 in an optically transparent two-dimensional porous medium. We found that Mn(II) oxidation initially occurred within biofilms but shifted over time toward the edges of biofilms in contact with pore fluid. Minerals precipitated outside of the initial biofilm footprint likely due to surface-mediated oxidation of Mn(II) by nascent biogenic Mn oxides, reinforcing a gradient in mineral accumulation from the Mn(II) source near the reactor inlet to the outlet. The rate of mineral precipitation outside the biofilm footprint surpassed the rate of mineral accumulation inside biofilms within 6 h and accounted for two-thirds of the total Mn oxide mass in the pore space at the end of the experiment. This work advances a mechanistic understanding of coupled biotic and abiotic Mn oxidation in porous environments while providing a novel platform to quantify microbe-mineral-fluid interactions.

Biofilms↗
DOE OSTI2026

Superionic conduction in solid polymer electrolytes – decoupling ion transport from segmental relaxation

Solvent-free, solid polymer electrolytes (SPEs) are promising candidates for next-generation, electrochemical energy storage systems due to their potential to enhance safety and performance, enable flexible device architectures, and streamline manufacturing processes. Conventional SPEs suffer from limited ionic conductivity due to the strong coupling between ion transport and (generally slow) polymer segmental relaxation. The realization of superionic conduction in SPEs, in which ions move faster than the structural relaxation of the polymers, requires a shift in design principles to promote this type of decoupled ion motion. In this perspective, we discuss how polymer architecture, ion–ion correlations, and ion–polymer interactions can unlock superionic behavior. We highlight several key design features, such as crystallinity, bulky side groups, high molecular weight, and percolating ionic aggregation, with a focus on creating low-barrier transport pathways in various polymer systems. We also demonstrate opportunities to combine polymer chemistry and data science through high-throughput and automated screening approaches to reveal how phase behavior, ion dynamics, and ionic interactions govern transport, thereby potentially enabling data-driven discovery of superionic polymer electrolyte materials.

Yang, Mengying [Univ. of Delaware, Newark, DE (Uni↗
DOE OSTI2025

HydroForecast Long-term: Improving hydropower’s resilience to climate change through accurate climate-scale

With hydrologic patterns and water availability across the globe shifting due to climate change, advancements in hydrologic prediction systems can help significantly reduce the uncertainties that utilities and water supply entities have in their decision making. Understanding and estimating hydrology at the climate scale is critical for managing water resources under changing climate scenarios. This project focuses on integrating state-of-the-art neural network modeling with downscaled climate projections to deliver the reliable water supply projections decades into the future to meet an urgent need from hydropower operators and water utilities. In this Phase 1 DOE SBIR proposal, we developed and validated a theory-guided neural network model, HydroForecast Long-term, for climate-scale hydrology and implemented the model within existing HydroForecast infrastructure. HydroForecast Long-term combines the most accurate streamflow modeling system with a flexible and scalable data architecture to generate water supply projections out to the year 2100. This report illustrates that we have achieved our four objectives: 1) create a prototype of HydroForecast Long-term, building the neural network prediction model, 2) build an automated data input pipeline that processes large amounts of data from the latest global temperature and precipitation climate models; 3) benchmark the accuracy of the hydrologic model over the recent two decades over a large set of diverse basins, and 4) create a set of output visuals and summary metrics informed by customer feedback that connect the data to critical decision points. This work empowers water users to make data-informed decisions supporting a resilient, renewable-powered grid and water system. The results advance the Department of Energy’s mission by addressing critical gaps in water supply planning under climate change.

13 HYDRO ENERGY↗
DOE OSTI2026

Toward Energy-Efficient HPC: Insights from Power Profiling a Cloud-Resolving Earth System Model

Power is a fundamental constraint as supercomputing advances to exascale. Efficient operation within strict power budgets requires application-aware power management based on a detailed understanding of application-level power behavior. This work analyzes the Energy Exascale Earth System Model (E3SM) atmosphere component, SCREAM, on Perlmutter (NERSC) and Frontier (OLCF). We characterize power variation across inputs, concurrency levels, and power caps, evaluate the energy impact of code optimizations, and attribute energy within the code using a newly developed GPU energy model. Results show that SCREAM’s peak power remains stable during its core execution phase and decreases gradually as concurrency increases. Power capping experiments reveal a performance–energy "sweet spot". On Perlmutter, limiting GPU power to 50% of thermal design power (TDP) achieves up to 15% energy savings with a 7% performance penalty. On Frontier, a 40% TDP cap yields up to 10% energy savings with less than 10% performance loss. Code optimizations reduce SCREAM energy by shortening run time without increasing power. Modeling reveals a critical insight: data movement accounts for approximately 70% of SCREAM’s GPU energy. This fundamentally shifts the optimization focus from FLOPS to data transfer reduction for this class of applications, offering the most impactful strategy for improving energy efficiency. This work establishes a foundation for practical, application-aware power management at exascale.

Zhao, Zhengji [Lawrence Berkeley National Laborato↗
DOE OSTI2025

Initial Conditions of Planet Formation: Time Constraints from Small Bodies and the Lifetime of Reservoirs in the Solar Protoplanetary Disk

This review explores the timescales of the initial phase of planet formation, from nebular dust (CAIs and chondrules) to planetesimal accretion and differentiation, using evidence from meteorite research. Aluminium-Mg systematics of CAIs indicate either an extended period of CAI formation (∼0.3 Ma) or an initial 26 Al heterogeneity, with evidence supporting a homogeneous 26 Al abundance in the protoplanetary disk. Thermal and aqueous alteration on the parent body can disturb the U-Pb and Al-Mg chronometers in chondrules. Focusing on relatively robust isochron data from plagioclase of pristine (types ≤3.05) chondrites indicates a shift in chondrule formation locations, moving from the inner to the outer disk over time. Ages of basaltic achondrites show that silicate differentiation on small bodies was well underway within the first few million years (Ma) of our solar system. Their age record, however, reveals inconsistencies between different chronometers, partly caused by (i) secondary disturbances due to thermal metamorphism, aqueous alteration, or impacts, (ii) the presence of xenolithic minerals, and (iii) potentially variable initial 26 Al abundances due to disturbances at the mineral scale. Nucleosynthetic isotope data indicate that parent bodies of iron and stony meteorites formed in two distinct regions within the protoplanetary disk: the inner, non-carbonaceous (NC) and the outer, carbonaceous (CC) region. Based on Hf-W chronometry it has been demonstrated that NC and CC parent bodies of magmatic iron meteorites segregated their cores within ∼1–3 Ma after CAI formation, implying that parent body accretion occurred within <1 Ma in both reservoirs. Combining accretion ages with nucleosynthetic data further reveals that, at first order, NC and CC reservoirs in the solar protoplanetary disk were established within 1 Ma and existed over several Ma with limited exchange between them. In the CR chondrite accretion region of the disk, planetary bodies formed over at least 3 Ma, while in most other regions, formation spanned at least 1 Ma, with minimal changes in nucleosynthetic isotope compositions. Aerodynamical size sorting of dust likely introduced or amplified some of these variations.

26Al distribution↗
DOE OSTI2024

Multifunctional Heat Pump with Energy Storage Capability

Replacing gas furnaces with heat pumps on a large scale can pose challenges to the electrical grid. It will significantly increase the demand, strain the electrical grid, especially during peak usage times. To ensure that heat pumps contribute to reducing emissions, it's essential to increase the share of renewable energy in the grid. However, the supply of renewable energy is unstable. Large scale of electrification must address the concern of grid resilience to meet necessary heating/cooling demands and shift peak electric load. All these require future heat pumps having energy storage capability. These systems can store excess energy during low-demand periods and release it during high-demand periods, reducing stress on the grid. This paper will introduce an innovative configuration, control, and laboratory investigations of a multifunctional packaged heat pump. In addition to the original indoor and outdoor air coils, the heat pump has a parallel hydronic loop with a brazed plate heat exchanger (BHP). The hydronic loop circulates hot/chilled water to store heating/cooling energy in phase change material (PCM). It is capable of space cooling, space heating, cooling energy storage/defrosting, water heating/heating energy storage with outdoor air source or indoor air source, and cooling/heating energy free discharge. The laboratory studies and breadboard unit are presented. Additionally, building energy simulation demonstrates utility cost reduction potential via charging PCM panels/ceilings during off-peak hours and releasing the energy during peak hours to mitigate the peak power consumption.

Shen, Bo↗
DOE OSTI2026

Dynamics of iodine geminate recombination in supercritical xenon solvent: Caging effect

Understanding the dynamics of chemical reactions in solutions is vital, as their rates and kinetics are significantly affected by the solvent environment. Supercritical solvents offer extensive applications in chemical reactions by enabling the manipulation of the solution environment. Here, in this study, we investigate the geminate recombination of iodine in a supercritical xenon solvent by using ReaxFF-based molecular dynamics simulations. Our findings reveal that the highest iodine recombination rate occurs near supercritical conditions, while lower-pressure conditions lead to reduced collision rates and unstable recombination, and higher-pressure conditions hinder iodine diffusion, resulting in a lower recombination rate. Our analysis shows that the xenon local density at the time of recombination is at least 2.5 times higher than the global density, confirming the presence of xenon clusters surrounding the Iodine atoms. This observation is further supported by coordination number analysis, which confirms an elevated xenon local density during recombination. In addition, the correlation between the total energy of xenon atoms within a cluster and recombined iodine atoms underscores the kinetic energy transfer process, validating the occurrence of geminate recombination. The excess kinetic energy from the recombining iodine atoms is transferred to the surrounding xenon atoms. Our examination of geminate recombination demonstrates that iodine atoms confined within xenon clusters—whether through manual insertion of atoms or the fast dissociation of an iodine molecule within xenon clusters—are more likely to recombine as primary geminate recombination. However, extending the iodine molecule dissociation time allows iodine atoms to diffuse out of the cluster, and the recombination to shift toward secondary geminate recombination.

Cage effect↗
DOE OSTI2026

Variability in Performance of a Machine Learning Seismicity Catalog: Central Italy, 2016–2017

Machine learning (ML) catalogs contain many more earthquakes than routine catalogs, but their performance in phase picking and earthquake detection has not been fully evaluated. We develop station‐level detection probabilities using logistic regression and combine them across a seismic network to compute spatial magnitude‐of‐completeness fields. We apply this approach to two catalogs from the 2016–2017 Central Italy sequence that were constructed from the same seismic network, one routine and one ML‐based. At the station level, the ML picker increases detection sensitivity by identifying smaller magnitude events and detecting earthquakes at greater distances. Spatially, the magnitude of completeness decreases substantially, with median values shifting from 1.6 to 0.5 for P waves and from 1.7 to 0.5 for S waves. However, the ML catalog also shows greater variability in station‐level performance than the routine catalog. These results demonstrate that ML‐based improvements in detectability are widespread but spatially nonuniform, highlighting their benefits, their limitations, and the potential for further improvements.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Inhomogeneous magnetic ordered state and evolution of magnetic fluctuations in Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 revealed by 31 P NMR

SrCo 2 ⁢P 2 with a tetragonal structure is known to be a Stoner-enhanced Pauli paramagnetic metal being nearly ferromagnetic. Recently J. Schmidt et al. [Phys. Rev. B 108, 174415 (2023)] reported that a ferromagnetic ordered state is actually induced by a small Ni substitution for Co of x = 0.02 in Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 where an antiferromagnetic ordered phase also appears by further Ni substitution with x = 0.06–0.35. Here, in this work, using nuclear magnetic resonance (NMR) measurements on 31 P nuclei, we have investigated how the magnetic properties change by the Ni substitution in Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 from a microscopic point of view, especially focusing on the evolution of magnetic fluctuations with the Ni substitution and the characterization of the magnetically ordered states. The temperature dependencies of the 31 P spin-lattice relaxation rate divided by temperature (1/T 1 ⁢T) and Knight shift (K) for SrCo 2 ⁢P 2 are reasonably explained by a model where a double-peak structure for the density of states near the Fermi energy is assumed. Based on a Korringa ratio analysis using the T 1 and K data, ferromagnetic spin fluctuations are found to dominate in the ferromagnetic Sr⁢(Co 1–x ⁢Ni x ) 2 ⁢P 2 as well as the antiferromagnets where no clear antiferromagnetic fluctuations are observed. We also found the distribution of the ordered Co moments in the magnetically ordered states from the analysis of the 31 P-NMR spectra exhibiting a characteristic rectangular-like shape.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗