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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 145 records · Page 8

Centroidal Voronoi tessellation based methods for optimal rain gauge location prediction

With more satellite and model precipitation data becoming available, new analytical methods are needed that can take advantage of emerging data patterns to make well informed predictions in many hydrological applications. Herein we propose a new strategy where we extract precipitation variability patterns and use correlation map to build the resulting density map that serves as an input to centroidal Voronoi tessellation construction that optimizes placement of precipitation gauges. We provide results of numerical experiments based on the data from the Alto-Adige region in Northern Italy and Oklahoma and compare them against actual gauge locations. This method provides an automated way for choosing new gauge locations and can be generalized to include physical constraints and to tackle other types of resource allocation problems.

54 ENVIRONMENTAL SCIENCES↗

Quantum Imaging of Magnetic Phase Transitions and Spin Fluctuations in Intrinsic Magnetic Topological Nanoflakes

Topological materials featuring exotic band structures, unconventional current flow patterns, and emergent organizing principles offer attractive platforms for the development of next-generation transformative quantum electronic technologies. The family of MnBi 2 T e4 (Bi 2 Te 3 )n materials is naturally relevant in this context due to their nontrivial band topology, tunable magnetism, and recently discovered extraordinary quantum transport behaviors. Despite numerous pioneering studies, to date, the local magnetic properties of MnBi 2 Te 4 (Bi 2 Te 3 )n remain an open question, hindering a comprehensive understanding of their fundamental material properties. Exploiting nitrogen-vacancy (NV) centers in diamond, we report nanoscale quantum imaging of magnetic phase transitions and spin fluctuations in exfoliated MnBi 2 Te 4 (Bi 2 Te 3 )n flakes, revealing the underlying spin transport physics and magnetic domains at the nanoscale. Furthermore, our results highlight the unique advantage of NV centers in exploring the magnetic properties of emergent quantum materials, opening new opportunities for investigating the interplay between topology and magnetism.

Antiferromagnetic materials↗

Mechanistic Understanding of the Growth Kinetics and Dynamics of Nanoparticle Superlattices by Coupling Interparticle Forces from Real-Time Measurements

Superlattice structures formed by nanoparticle (NP) self-assembly have attracted increasing attention due to their potential as a novel class of nanomaterials with enhanced physicochemical properties tailored by the assembly structure. However, many key questions remain regarding the correlation between the dynamics of individual NPs and the emerging superlattice patterns. Here we investigated the self-assembly of gold NPs by employing in situ transmission electron microscopy equipped with direct detection camera capabilities, which enabled us to track the rapid motion of individual nanoparticles in real time. By calculating the contributions of Brownian, van der Waals, hydrodynamic, and steric hindrance forces, we obtained a quantitative evaluation of the competitive interactions that drive the assembly process. Such competition between forces over various separations is critical for the kinetics of cluster growth, as well as the superlattice formation. Brownian motion resulted in random particle motions to form small-sized clusters, whose growth dynamics was characterized as reaction-limited aggregation. Subsequently, at relative short-range particle separation, van der Waals force overrode the Brownian force and dominantly drove the assembly process. In the close proximity, a delicate balance between van der Waals and steric hindrance forces surprisingly led to a unique dynamic nature of the assembled superlattice. Our study provides a fundamental understanding of coupling energetics and dynamics of NPs involved in the assembly process, enabling the control and design of the structure of nanoparticle superlattices.

Lee, Jaewon↗

Automated classification of big X-ray diffraction data using deep learning models

Abstract In current in situ X-ray diffraction (XRD) techniques, data generation surpasses human analytical capabilities, potentially leading to the loss of insights. Automated techniques require human intervention, and lack the performance and adaptability required for material exploration. Given the critical need for high-throughput automated XRD pattern analysis, we present a generalized deep learning model to classify a diverse set of materials’ crystal systems and space groups. In our approach, we generate training data with a holistic representation of patterns that emerge from varying experimental conditions and crystal properties. We also employ an expedited learning technique to refine our model’s expertise to experimental conditions. In addition, we optimize model architecture to elicit classification based on Bragg’s Law and use evaluation data to interpret our model’s decision-making. We evaluate our models using experimental data, materials unseen in training, and altered cubic crystals, where we observe state-of-the-art performance and even greater advances in space group classification.

Chemistry↗

Observation of moiré excitons in WSe 2 /WS 2 heterostructure superlattices

Moiré superlattices enable the generation of new quantum phenomena in two-dimensional heterostructures, in which the interactions between the atomically thin layers qualitatively change the electronic band structure of the superlattice. For example, mini-Dirac points, tunable Mott insulator states and the Hofstadter butterfly pattern can emerge in different types of graphene/boron nitride moiré superlattices, whereas correlated insulating states and superconductivity have been reported in twisted bilayer graphene moiré superlattices. In addition to their pronounced effects on single-particle states, moiré superlattices have recently been predicted to host excited states such as moiré exciton bands. Here we report the observation of moiré superlattice exciton states in tungsten diselenide/tungsten disulfide (WSe 2 /WS 2 ) heterostructures in which the layers are closely aligned. These moiré exciton states manifest as multiple emergent peaks around the original WSe 2 A exciton resonance in the absorption spectra, and they exhibit gate dependences that are distinct from that of the A exciton in WSe 2 monolayers and in WSe 2 /WS 2 heterostructures with large twist angles. These phenomena can be described by a theoretical model in which the periodic moiré potential is much stronger than the exciton kinetic energy and generates multiple flat exciton minibands. The moiré exciton bands provide an attractive platform from which to explore and control excited states of matter, such as topological excitons and a correlated exciton Hubbard model, in transition-metal dichalcogenides.

36 MATERIALS SCIENCE↗

Shape control and compartmentalization in active colloidal cells

Significance Advances in simulation and synthesis of nanoparticles and colloids are leading to a new class of active colloidal systems where self-propelled and self-rotated particles convert energy to motion. Such systems hold promise for the possibility of colloidal machines––integrated systems of colloids able to carry out functions. An important step in this direction is appropriately confining colloids within cells whose shape can be controlled and within which activity can be compartmentalized. This paper uses theory and computer simulation to propose active colloidal cells and investigates their behavior. Our findings provide motivation and design rules for the fabrication of primitive colloidal machines.

36 MATERIALS SCIENCE↗

EMITTING ELECTRONS AND SOURCE ACTIVITY IN MARKARIAN 501

We study the variation of the broadband spectral energy distribution (SED) of the BL Lac object Mrk 501 as a function of source activity, from quiescent to flaring. Through {chi}{sup 2}-minimization we model eight simultaneous SED data sets with a one-zone synchrotron self-Compton (SSC) model, and examine how model parameters vary with source activity. The emerging variability pattern of Mrk 501 is complex, with the Compton component arising from {gamma}-e scatterings that sometimes are (mostly) Thomson and sometimes (mostly) extreme Klein-Nishina. This can be seen from the variation of the Compton to synchrotron peak distance according to source state. The underlying electron spectra are faint/soft in quiescent states and bright/hard in flaring states. A comparison with Mrk 421 suggests that the typical values of the SSC parameters are different in the two sources: however, in both jets the energy density is particle-dominated in all states.

79 ASTRONOMY AND ASTROPHYSICS↗

MAGNETIC FLUX TRANSPORT AND THE LONG-TERM EVOLUTION OF SOLAR ACTIVE REGIONS

With multiple vantage points around the Sun, Solar Terrestrial Relations Observatory (STEREO) and Solar Dynamics Observatory imaging observations provide a unique opportunity to view the solar surface continuously. We use He ii 304 Å data from these observatories to isolate and track ten active regions and study their long-term evolution. We find that active regions typically follow a standard pattern of emergence over several days followed by a slower decay that is proportional in time to the peak intensity in the region. Since STEREO does not make direct observations of the magnetic field, we employ a flux-luminosity relationship to infer the total unsigned magnetic flux evolution. To investigate this magnetic flux decay over several rotations we use a surface flux transport model, the Advective Flux Transport model, that simulates convective flows using a time-varying velocity field and find that the model provides realistic predictions when information about the active region's magnetic field strength and distribution at peak flux is available. Finally, we illustrate how 304 Å images can be used as a proxy for magnetic flux measurements when magnetic field data is not accessible.

79 ASTRONOMY AND ASTROPHYSICS↗

Fine-scale vegetation composition and structure shape spatiotemporal variation in surface albedo across a low Arctic tundra landscape

The unprecedented rate of warming in the Arctic is driving changes in the structure and composition of tundra vegetation. Increases in deciduous tall shrub cover, height, and density are of particular concern, as these changes alter local surface albedo in ways that could amplify effects on the regional surface energy budget (SEB). Despite this importance, significant uncertainties remain in understanding the interplay between fine-scale vegetation patterns and emergent albedo dynamics across space and time. Here, we address these uncertainties by (1) quantifying spatiotemporal variation in surface shortwave albedo and (2) determining the relative influence of fine-scale vegetation composition, structure, and environmental conditions on albedo across a representative low-Arctic tundra landscape on Alaska’s Seward Peninsula. To do this, we synthesized multi-scale, multi-platform remote sensing observations, including a novel Landsat-derived albedo time series, a fine-scale map of Arctic plant functional type (PFT) fractional cover, and airborne LiDAR estimates of canopy height and topography. We show that there are substantial reductions in winter albedo for pixels dominated by tall, woody PFTs (28.13%) relative to pixels dominated by non-woody vegetation, but almost no change in summer albedo (3% increase). Further, we identified a unimodal trend in the relationship between canopy height and the timing of the springtime transition from high (snowy) to low (leafy) albedo (peak at 5.5 m), possibly because of competing ‘snow-fence’ and ‘protrusion’ snow-shrub interactions. To explore the primary drivers of albedo, we constructed a random forest model and found that canopy height and the fractional cover of woody PFTs were as- or more important predictors of winter albedo than topographic features. These findings provide strong evidence for the impacts of local vegetation characteristics on regional surface albedo, highlighting the need for better quantification of snow-shrub interactions to accurately predict the Arctic’s SEB under future environmental change.

Arctic↗

Guiding Self-Assembly of Active Colloids by Temporal Modulation of Activity

Self-organization phenomena in ensembles of self-propelled particles open pathways to the synthesis of new dynamic states not accessible by traditional equilibrium processes. The challenge is to develop a set of principles that facilitate the control and manipulation of emergent active states. In this study, we report that dielectric rolling colloids energized by a pulsating electric field self-organize into alternating square lattices with a lattice constant controlled by the parameters of the field. We combine experiments and simulations to examine spatiotemporal properties of the emergent collective patterns and investigate the underlying dynamics of the self-organization.We reveal the resistance of the dynamic lattices to compression and expansion stresses leading to a hysteretic behavior of the lattice constant. The general mechanism of pattern synthesis and control in active ensembles via temporal modulation of activity can be applied to other active colloidal systems.

36 MATERIALS SCIENCE↗

Kinetic effects of self-organization in low-temperature magnetized plasmas (Final Report for DE-SC0019045: 9/1/2018-8/31/2019)

The research goal of this Early Career Research Program project is to advance the science of low temperature magnetized plasmas using first-principles kinetic, e.g., solving the Boltzmann equation, models. A better understanding of the plasma transport properties, such as electrical resistivity and thermal conductivity must be obtained to better control and design magnetized plasma sources. A key physical phenomenon in low-temperature magnetized plasmas is the self-organization of plasma flows, e.g., coherent plasma structures and transition between different discharge modes. Understanding the physics of coherent plasma structures has been identified as one of the four important frontier topics in a recent workshop by the Office of Fusion Energy Science. These self-emerging plasma patterns results from the nonlinear coupling between plasma constituents (ions, electrons, and neutral atoms), electromagnetic fields, and materials. The physics of low-temperature magnetized plasmas is particularly complex because (i) the collisionless instabilities affect collisional phenomena (ionization, transport, etc.) and vice versa and (ii) the presence of materials (sheath, electron injection, etc.) influences the bulk plasma properties in low-temperature plasma (LTP) devices. Computational models of these plasma flows remain challenging because the plasma density can vary several orders of magnitudes, a wide range of temporal and spatial scales must be resolved, the phenomena are inherently three-dimensional, and various physical processes, such as wall interaction, instabilities, inelastic collisions, etc., must be simultaneously and self-consistently taken into account. Understanding the fundamental transport mechanisms in cross-field configurations enables additional controllability of plasma properties and electron energy distribution functions (EEDFs).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Position Papers for the ASCR Workshop on the Management and Storage of Scientific Data

The purpose of this workshop is to identify priority research directions in the area of data management for high-performance and scientific computing above and beyond HPC’s traditional "the parallel file system is the data-management system" model. Supporting the breadth of the DOE mission, including the explosion of AI uses and the growing needs of experimental and observational science, motivates revisiting our assumptions about data management. There are many facets of this topic to explore including: (1) Interfaces for accessing data that resides on traditional persistent storage as well as memory devices; (2) Storage-system architecture design that supports scientific workflows on varied hierarchical storage and networking devices; (3) Devising metadata management infrastructure to support FAIR principles (Findability, Accessibility, Interoperability, and Reusability); (4) Capturing provenance information about scientific data; (5) Utilizing AI to learn I/O patterns of emerging workloads for efficient data management; (6) Providing data management support for AI and complex workflows; and (7) Understanding the overlap between traditional storage systems and I/O (SSIO) efforts and data management. While the program committee has identified these topics as important areas for discussion, we welcome position papers from the community that propose additional topics of interest for discussion at the workshop. The workshop agenda will include breakout sessions for discussing these and selected topic areas to inform priority research directions for data management for high-performance and scientific computing.

97 MATHEMATICS AND COMPUTING↗

Report for the ASCR Workshop on the Management and Storage of Scientific Data

The purpose of this workshop is to identify priority research directions in the area of data management for high-performance and scientific computing above and beyond HPC’s traditional "the parallel file system is the data-management system" model. Supporting the breadth of the DOE mission, including the explosion of AI uses and the growing needs of experimental and observational science, motivates revisiting our assumptions about data management. There are many facets of this topic to explore including: (1) Interfaces for accessing data that resides on traditional persistent storage as well as memory devices; (2) Storage-system architecture design that supports scientific workflows on varied hierarchical storage and networking devices; (3) Devising metadata management infrastructure to support FAIR principles (Findability, Accessibility, Interoperability, and Reusability); (4) Capturing provenance information about scientific data; (5) Utilizing AI to learn I/O patterns of emerging workloads for efficient data management; (6) Providing data management support for AI and complex workflows; and (7) Understanding the overlap between traditional storage systems and I/O (SSIO) efforts and data management. While the program committee has identified these topics as important areas for discussion, we welcome position papers from the community that propose additional topics of interest for discussion at the workshop. The workshop agenda will include breakout sessions for discussing these and selected topic areas to inform priority research directions for data management for high-performance and scientific computing.

97 MATHEMATICS AND COMPUTING↗

Empirical Indicators of Transmission Value in the Southeast United States

Concurrent differences in energy price between different parts of the electric grid are a key indicator of the value of additional transmission. In areas without a wholesale electricity market, such as the Southeast, an alternative indicator to price is the Federal Energy Regulatory Commission’s (FERC) system lambda data. This economic metric represents the minimized marginal production costs of thermal generators, including fuel and other variable operation and maintenance expenses. Balancing Authorities report a single system lambda for their entire balancing area. Most Southeastern lambdas exhibit sufficient price variation to support a transmission valuation analysis, although incomplete accounting of congestion costs or scarcity rents during peak load hours may underestimate the true value of transmission capacity. With transmission value defined as the annual average hourly absolute price difference between two regions and FERC’s system lambda data used as a price proxy, we find the following results in the Southeast region during 2012-2023 (reported in $\$2024$/MWh): Intra‐regional findings: Annual averages historically span $\$2$–$\$28$/MWh and average $\$12$/MWh in SERTP and span $\$4$–$\$19$/MWh and average $\$9$/MWh in FRCC, disregarding transmission value driven by anomalous data. The ranges of transmission value reported here are large, spanning an order of magnitude in some cases. Much of this variation is driven by year-to-year changes, with 2022 having a particularly high intra-regional transmission value due to elevated natural gas prices. Inter‐regional corridors: Annual average transmission values across three broader regions range from $\$6$ to $\$28$/MWh with a long-term average of $\$11$/MWh. Much of the transmission value is concentrated in a small portion of hours. Across all regions, severe weather—particularly polar vortex events in January 2018, February 2021, and December 2022—drives the largest price spreads. Seasonal patterns also emerge, with summer afternoons and fall mornings contributing consistently to transmission value, as for example between MISO and SOCO in 2023.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Virtual Power Plant Architecture and Resilient Design

Virtual Power Plants (VPPs) represent a fundamental shift in electric grid operations, aggregating distributed energy resources (DERs) such as solar panels and battery storage to deliver utility-scale grid services traditionally provided by centralized power plants. This report examines the unique architectural, operational, and digital assurance considerations that distinguish VPPs from conventional utility infrastructure as they scale from pilot projects to mainstream deployment across the United States. While VPPs offer significant opportunities for grid modernization and enhanced flexibility, their distributed, multi-stakeholder architecture introduces distinct security challenges that differ fundamentally from traditional generation facilities. The analysis identifies risks in VPP operations, including device-level security gaps, platform vulnerabilities, and communication protocol weaknesses that create expanded attack surfaces compared to centralized power plants. Through examination of real-world incidents and emerging threat patterns, the report demonstrates how some VPPs' reliance on consumer-owned devices, public internet infrastructure, and complex vendor ecosystems require new approaches to digital assurance and operational security. The findings provide practical guidance for utilities, regulators, and aggregators to implement robust security frameworks and operational best practices essential for maintaining grid reliability as VPP deployment accelerates under the Federal Energy Regulatory Commission (FERC) Order 2222 and related regulatory initiatives.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Climate-driven disturbances in the San Juan River sub-basin of the Colorado River

Accelerated climate change and associated forest disturbances in the southwestern USA are anticipated to have substantial impacts on regional water resources. Few studies have quantified the impact of both climate change and land cover disturbances on water balances on the basin scale, and none on the regional scale. In this work, we evaluate the impacts of forest disturbances and climate change on a headwater basin to the Colorado River, the San Juan River watershed, using a robustly calibrated (Nash–Sutcliffe efficiency 0.76) hydrologic model run with updated formulations that improve estimates of evapotranspiration for semi-arid regions. Our results show that future disturbances will have a substantial impact on streamflow with implications for water resource management. Our findings are in contradiction with conventional thinking that forest disturbances reduce evapotranspiration and increase streamflow. In this study, annual average regional streamflow under the coupled climate–disturbance scenarios is at least 6–11 % lower than those scenarios accounting for climate change alone; for forested zones of the San Juan River basin, streamflow is 15–21 % lower. The monthly signals of altered streamflow point to an emergent streamflow pattern related to changes in forests of the disturbed systems. Exacerbated reductions of mean and low flows under disturbance scenarios indicate a high risk of low water availability for forested headwater systems of the Colorado River basin. Furthermore, these findings also indicate that explicit representation of land cover disturbances is required in modeling efforts that consider the impact of climate change on water resources.

54 ENVIRONMENTAL SCIENCES↗

Protein gradients on the nucleoid position the carbon-fixing organelles of cyanobacteria

Carboxysomes are protein-based bacterial organelles encapsulating key enzymes of the Calvin-Benson-Bassham cycle. Previous work has implicated a ParA-like protein (hereafter McdA) as important for spatially organizing carboxysomes along the longitudinal axis of the model cyanobacterium Synechococcus elongatus PCC 7942. Yet, how self-organization of McdA emerges and contributes to carboxysome positioning is unknown. Here, we identify a small protein, termed McdB that localizes to carboxysomes and drives emergent oscillatory patterning of McdA on the nucleoid. Our results demonstrate that McdB directly stimulates McdA ATPase activity and its release from DNA, driving carboxysome-dependent depletion of McdA locally on the nucleoid and promoting directed motion of carboxysomes towards increased concentrations of McdA. We propose that McdA and McdB are a previously unknown class of self-organizing proteins that utilize a Brownian-ratchet mechanism to position carboxysomes in cyanobacteria, rather than a cytoskeletal system. These results have broader implications for understanding spatial organization of protein mega-complexes and organelles in bacteria.

59 BASIC BIOLOGICAL SCIENCES↗