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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 289 records · Page 16

On the Origin of Holes During Polarization Reset in Floating Body Ferroelectric FETs Towards Improving Switching Efficiency

In this article, we performed a comprehensive combined experimental and modeling study on the polarization reset mechanisms of floating body (i.e., channel) ferroelectric FETs, an important class of device with growing interests due to added functionalities and improved reliabilities. Using fully-depleted silicon-on-insulator (FDSOI) FeFET as a classical example, we demonstrate that: 1) without hole generation mechanisms, floating body FeFETs during reset is simply a capacitor divider, with negligible ferroelectric voltage drop for switching; ii) Band-to-band-tunneling (BTBT) around gate-to-S/D overlap even with zero drain bias generates holes to facilitate the reset in FDSOI FeFET, though at a slower speed and hold the reset state; iii) With scaling, S/D inner fringe field can enable fast reset, thus offering a potential efficiency boost approach; iv) a compact FDSOI FeFET model is developed that can capture the BTBT effect and reproduce the observed behaviors; v) the reset mechanism is also validated in a NAND string composed of FDSOI FeFETs, demonstrating its relevant applications. These insights show the strategies in improving reset efficiency, i.e., enhanced BTBT and inner fringe field.

42 ENGINEERING↗

Interpretation of hydrothermal conditions, production-injection induced effects, and evidence for enhanced geothermal system-type heat exchange in response to >30 years of production at Roosevelt Hot Springs, Utah, USA

The Roosevelt Hot Springs hydrothermal system is located at the base of the Mineral Mountains in southwestern Utah on the eastern side of the Basin and Range. Hydrothermal activity is related to relatively recent bimodal magmatism, and the system is hosted in coarsely crystalline rock made of Oligocene–Miocene granitoids and Precambrian gneiss. The hydrothermal plume covers ~5 km 2 , with a maximum temperature of 268 °C at ~750 m depth, and a vertically extensive fault-fracture mesh east of the Opal Mound fault controls the upflow of hydrothermal fluids. Power generation (currently 38 MWe gross) began in 1984, and up through 2016, four wells were used for fluid production, and three wells were used for edge-field injection. Chemical analyses of produced fluids show that modern reservoir fluid compositions are similar to but more concentrated than those at the start of production, having near-neutral pH, total dissolved solids of 7000–10,000 mg/kg, and ionic ratios of Cl/HCO 3 ~50–100, Cl/SO4 ~50–100, and Na/K ~4–5. Chemical geothermometers indicate equilibration temperatures that mainly range between 240° and 300 °C. Early production induced a steep drop in pressure (~3.0–3.5 MPa), which was accompanied by a 250–300 m lowering of piezometric levels in wells and development of a shallow steam zone across the system. Hydrothermal fluid compositions evolved continuously in response to production-related steam-loss and injection breakthrough, which is reflected by gradual increases in chloride of up to 35% and stable isotope ratios of up to ~2‰δ 18 O and ~10‰δD. Simple mixing model calculations suggest that there has been a significant amount, ~10–20 MW th , of sustained multi-decadal heat mining and enhanced geothermal system (EGS)–type heat transfer by the injectate as it returns to the production zone. Overall, the two factors that have sustained long-term power production (currently 38 MWe gross) are the increased upflow of deep chloride water and, to a lesser extent, the mining of heat at <1 km depth.

58 GEOSCIENCES↗

CEED-MS34: Improve performance and capabilities of CEED-enabled ECP applications on Summit/Sierra. Exascale Computing Project Milestone Report

The main goal of this milestone was to help CEED-enabled ECP applications, including ExaSMR, MARBL, ExaWind and ExaAM, to improve their performance and capabilities on GPU systems like Summit and Lassen/Sierra. In addition, the CEED team also worked to: add and improve support for additional hardware and programming models in the CEED software components; release the next version of the CEED software stack, CEED-3.0; and demonstrate performance of libParanumal kernels in libCEED, Nek and MFEM. These additional tasks contributed directly to the main CEED-MS34 goal and will also play an important role in CEED’s future milestones.

97 MATHEMATICS AND COMPUTING↗

Agro-IBIS/THMB Modeled Yield, Nitrogen Loss, and Profitability Maps for the Raccoon River Basin, Iowa, USA

This data was used to assess the potential for improving water quality in this watershed when integrating miscanthus, a bioenergy perennial grass, on to areas of low profit under current corn-soybean management and areas of high nitrogen leaching under both current and future climate conditions. This dataset includes all observations (yield, streamflow, nitrogen loads) and model simulation data used from Dr. Kelsie Ferin’s (former PhD student with Dr. Andy VanLoocke, ISU Dept. of Agronomy) dissertation and publication in Global Change Biology – Bioenergy (DOI: 10.1111/gcbb.13078). Modeled output included in this dataset includes corn, soybean, and miscanthus yields, nitrogen leaching rates, net mineralization rates, land use cover fractions with and without the inclusion of miscanthus, profitability maps, additional soil property maps, and simulated streamflow and nitrogen loads near the outlet of the Raccoon River Basin (Van Meter, Iowa) for both historical and future climate conditions. This dataset includes a mixture of netCDF, .tiff, .csv, and .xlsx files. See README.pdf for more information.

Ferin, Kelsie↗

Ecosystems for Scientific Computing in the Age of AI

Scientific computing is at an inflection point. Artificial intelligence (AI) is reshaping how scientific software is developed, how teams collaborate, how projects are governed, and how the next generation is trained. Drawing on insights from a 2025 workshop report, this article argues that the future of discovery will depend on agile, robust ecosystems built through socio-technical co-design—the intentional integration of technical and human systems. This perspective is essential for ensuring that future scientific computing remains trustworthy, sustainable, and scalable. It combines advances in AI, high-performance computing, and software with new models for cross-disciplinary collaboration, education, and workforce development. Key recommendations include building modular, trustworthy AI-enabled software ecosystems; enabling teams to integrate AI into scientific workflows while preserving human creativity, integrity, and rigor; and developing adaptive training pathways that keep pace with rapid technological change. By sharing these perspectives, we hope to stimulate broader community dialogue and encourage coordinated action.

AI↗

Flexible Stellarator Physics Facility

We propose to build a Flexible Stellarator Physics Facility to explore promising regions of the vast parameter space of disruption-free stellarator solutions for Fusion Pilot Plants (FPPs). The FESAC Long Range Plan recognized the quasi-symmetric stellarator as “the leading US approach to developing disruption-free, low-recirculating-power fusion configurations”. To deliver the ambitious Decadal Vision for Commercial Fusion Energy, we must establish a persuasive stellarator program in parallel to the tokamak one: the stellarator will prove to be a better path to a reactor if theoretical predictions are confirmed and novel optimization techniques and strategies work as desired. Since the release of the Long Range Plan in 2020, stellarators have arguably made the most significant advances of all fusion concepts. Groundbreaking results from W7-X demonstrated low neoclassical transport and the successful operation of the island divertor. Advances in theory and modeling now allow us to minimize turbulent transport, to achieve equilibria with precise quasisymmetry, to reduce neoclassical transport and fast ion loss to levels far below what has been previously achieved, and to minimize the effect of coil manufacturing errors. If realized, these advances will lead to cost-effective stellarator designs with confinement comparable to tokamaks but without the fundamental challenges of disruptions and current drive.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Structure-function analysis of microRNA 3'-end trimming by Nibbler

Nibbler (Nbr) is a 3'-to-5' exoribonuclease whose catalytic 3'-end trimming activity impacts microRNA (miRNA) and PIWI-interacting RNA (piRNA) biogenesis. Here, we report on structural and functional studies to decipher the contributions of Nbr’s N-terminal domain (NTD) and exonucleolytic domain (EXO) in miRNA 3'-end trimming. We have solved the crystal structures of the NTD core and EXO domains of Nbr, both in the apo-state. The NTD-core domain of Aedes aegypti Nbr adopts a HEAT-like repeat scaffold with basic patches constituting an RNA-binding surface exhibiting a preference for binding double-strand RNA (dsRNA) over single-strand RNA (ssRNA). Structure-guided functional assays in Drosophila S2 cells confirmed a principal role of the NTD in exonucleolytic miRNA trimming, which depends on basic surface patches. Gain-of-function experiments revealed a potential role of the NTD in recruiting Nbr to Argonaute-bound small RNA substrates. The EXO domain of A. aegypti and Drosophila melanogaster Nbr adopt a mixed α/β-scaffold with a deep pocket lined by a DEDDy catalytic cleavage motif. We demonstrate that Nbr’s EXO domain exhibits Mn2+-dependent ssRNA-specific 3'-to-5' exoribonuclease activity. Modeling of a 3' terminal Uridine into the catalytic pocket of Nbr EXO indicates that 2'-O-methylation of the 3'-U would result in a steric clash with a tryptophan side chain, suggesting that 2'-O-methylation protects small RNAs from Nbr-mediated trimming. Overall, our data establish that Nbr requires its NTD as a substrate recruitment platform to execute exonucleolytic miRNA maturation, catalyzed by the ribonuclease EXO domain.

59 BASIC BIOLOGICAL SCIENCES↗

Mass Transport in Membrane Systems: Flow Regime Identification by Fourier Analysis

The numerical calculation of local mass distributions in membrane systems by computational fluid dynamics (CFD) offers indispensable benefits. However, the concept to calculate such distributions in response to separate variations of operation conditions (OCs) makes it difficult to address overall, flow-physics-related questions, which require the consideration of the collective interaction of OCs. It is shown that such understanding-related relationships can be obtained by the analytical solution of the advection–diffusion equation considered. A Fourier series model (FSM) is presented, which provides exact solutions of an advection–diffusion equation for a wide range of OCs. On this basis, a new zeroth-order model is developed, which is very simple and as accurate as the complete FSM for all conditions of practical relevance. Advection-dominated blocked and diffusion-dominated unblocked flow regimes are identified (depending on a Péclet number which compares the flow geometry with a length scale imposed by the flow), which implies relevant requirements for the use of lab results for pilot- and full-scale applications. Analyses reveal the equivalence of variations of OCs, which offers a variety of options to accomplish desired flow regime changes.

Heinz, Stefan (ORCID:0000000248712416)↗

Limitations of Hydrogen Detection After 150 Years of Research on Hydrogen Embrittlement

Hydrogen's significance in contemporary society lies in its remarkable energy density, yet its integration into the worldwide energy grid presents a substantial challenge. Exposing materials to hydrogen environments leads to degradation of mechanical properties, damage, and failure. While the current approach for assessing hydrogen's impact on materials involves mainly multiscale modeling and mechanical testing, there exists a significant deficiency in detecting the intricate interactions between hydrogen and materials at the nanoatomic scales and under in situ conditions. This perspective review highlights the experimental endeavors aimed at bridging this gap, pointing toward the imminent need for new experimental techniques that can detect and map hydrogen in materials’ microstructures and their site‐specific dependencies.

Tunes, Matheus A.↗

Modeling Heterogeneity in UO 2 Nanoparticles Using X‐ray Absorption Spectroscopy

Abstract EXAFS provides the capability to interrogate nanoparticle (NP) structure in atomistic detail without relying on long‐range crystallinity. There is a limitation in that EXAFS provides averaged structural information, making it difficult to separate a small amount of heterogeneous structure from bulk. In this work, models were developed to extract surface‐specific information from conventional EXAFS measurements collected on UO 2 NPs of varying size. Specifically, the surface terminating species of UO 2 NPs was determined from comparison of coordination numbers with geometric models while the origin of static disorder was interrogated from user‐defined simulations. Results show that the degree of oxygenation on the NP surface does not significantly deviate from bulk surface and that static disorder is highly enhanced in NP surface layers but cannot be attributed to surface relaxation effects alone. The approach described herein has the potential to be adapted to a range of inorganic NP systems to interrogate surface structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibrational response and temperature of shock-compressed Pt: In situ extended x-ray absorption fine structure measurements to 325 GPa

Single pulse (~100 ps duration) extended x-ray absorption fine structure (EXAFS) measurements were obtained in laser shocked Pt to examine atomic vibrational properties and to determine temperatures for shock pressures from 72-325 GPa. Pt x-ray absorption spectra were recorded while a planar shock wave was propagating through the Pt sample. The absorption spectrum corresponding to the shocked Pt was obtained by subtracting the ambient Pt contribution from the measured absorption spectrum. Fits to the shocked state EXAFS data provided Pt lattice parameters consistent with the known Pt Hugoniot and the mean squared relative displacements (MSRDs) for nearest neighbor Pt atoms. Pt temperatures in the shocked state, estimated from the MSRDs using the correlated Debye model and correlated Einstein models, were consistent with both the Hugoniot temperatures calculated by integration along the Hugoniot and with the Hugoniot temperatures from published first-principles calculations. However, the agreement between the Hugoniot temperatures from EXAFS measurements and the calculated Hugoniot temperatures is not as good above 200 GPa, likely due to anharmonic effects. Furthermore, the present results demonstrate that single-pulse synchrotron EXAFS measurements in laser-shocked solids are useful for quantitative temperature determination and for examination of vibrational properties, including anharmonicity, at extreme pressure-temperature conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Photovoltaics at multi-terawatt scale: Waiting is not an option

We report a major renewable-energy milestone occurred in 2022: Photovoltaics (PV) exceeded a global installed capacity of 1 TW dc . But despite considerable growth and cost reduction over time, PV is still a small part of global electricity generation (4 to 5% for 2022), and the window is increasingly closing to take action at scale to cut greenhouse gas (GHG) emissions while meeting global energy needs for the future. PV is one of very few options that can be dispatched relatively quickly, but discussions of TW-scale growth at the global level may not be clearly communicating the needed size and speed for renewable-energy installation. A major global risk would be to make poor assumptions or mistakes in modeling and promoting the required PV deployment and industry growth and then realize by 2035 that we were profoundly wrong on the low side and need to ramp up manufacturing and deployment to unrealistic or unsustainable levels.

14 SOLAR ENERGY↗

California’s 2023 snow deluge: Contextualizing an extreme snow year against future climate change

The increasing prevalence of low snow conditions in a warming climate has attracted substantial attention in recent years, but a focus exclusively on low snow leaves high snow years relatively underexplored. However, these large snow years are hydrologically and economically important in regions where snow is critical for water resources. Here, we introduce the term “snow deluge” and use anomalously high snowpack in California’s Sierra Nevada during the 2023 water year as a case study. Snow monitoring sites across the state had a median 41 y return interval for April 1 snow water equivalent (SWE). Similarly, a process-based snow model showed a 54 y return interval for statewide April 1 SWE (90% CI: 38 to 109 y). While snow droughts can result from either warm or dry conditions, snow deluges require both cool and wet conditions. Relative to the last century, cool-season temperature and precipitation during California’s 2023 snow deluge were both moderately anomalous, while temperature was highly anomalous relative to recent climatology. Downscaled climate models in the Shared Socioeconomic Pathway-370 scenario indicate that California snow deluges—which we define as the 20 y April 1 SWE event—are projected to decline with climate change (58% decline by late century), although less so than median snow years (73% decline by late century). This pattern occurs across the western United States. Changes to snow deluge, and discrepancies between snow deluge and median snow year changes, could impact water resources and ecosystems. Understanding these changes is therefore critical to appropriate climate adaptation.

Marshall, Adrienne M.↗

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Abstract Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

59 BASIC BIOLOGICAL SCIENCES↗

An Evaluation of Dynamical Downscaling Methods Used to Project Regional Climate Change

In the past decade, dynamical downscaling using “pseudo-global-warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)-simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic-scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large-scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic-scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

54 ENVIRONMENTAL SCIENCES↗

Characterization of Low-energy Ionization Signals in Silicon Detectors for the Nab Experiment

The Nab (Neutron a b) experiment is designed to measure the beta-antineutrino angular correlation in free neutron 𝛽 decay with an ultimate precision goal of 0.1%, providing input for tests of Cabibbo-Kobayashi-Maskawa matrix unitarity. This measurement is performed via detection of electrons and protons in delayed coincidence using custom large-area segmented silicon detectors. We present the characterization of one such detector system to establish the proton energy and timing response, using a dedicated proton accelerator. The detected proton peak was studied for 25, 30, and 35 keV incident protons on a set of detector segments and multiple cooling cycles over a one-year period. Ionization losses were consistent with models of the detector dead layer with thicknesses less than 100 nm. The detected proton peak was stable within the uncertainty from energy calibration (0.25 keV). The rise times of detector pulses from 109Cd and 113Sn conversion electron sources were used to extract the impurity density profile and establish a precise model for the detector timing response. The observed impurity density profile varied from (2±2)×109/cm3 at the center to (26±2)×109/cm3 at the edge. This impurity density profile was then used to characterize systematic effects in proton time-of-flight measurements due to detector pulse-shape effects; the resultant proton timing systematic uncertainties were below 0.3 ns, which is sufficient for the Nab experiment.

Taylor, RJ [North Carolina State University]↗

Challenges and Vision for Standardization of Biopolymer Data Sets for Machine Learning

Machine learning (ML) is transforming materials research, yet potential for biopolymer discovery remains constrained by fragmented data and nonstandardized reporting. Biopolymers differ significantly from synthetic polymers, requiring specialized approaches to represent their biosynthetic origins, hierarchical structures, and application-specific metrics. In this Perspective, we identify three core challenges limiting biopolymer representation: information encoding, data quality, and data sharing. We describe the most pressing issues and propose commensurate approaches to address each key challenge. Recommendations include the design and adoption of biopolymer-specific fingerprinting and representation frameworks, development of hybrid human-large language model (LLM) data extraction strategies, and expanding Findable, Accessible, Interoperable, Reusable (FAIR)-compliant repositories. We propose a robust foundation to define interoperable, high-quality data sets that capture the full context of biopolymer materials. Standardized metadata, shared ontologies, and community-driven infrastructure would enable scalable, reproducible workflows and accelerate the ML-driven development of biopolymers.

36 MATERIALS SCIENCE↗