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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Wall modes and the transition to bulk convection in rotating Rayleigh-Bénard convection

We investigate states of rapidly rotating Rayleigh-Bénard convection in a cylindrical cell over a range of Rayleigh numbers 3 × 10 5 ≤ Ra ≤ 5 × 10 9 and Ekman numbers 10 − 6 ≤ Ek ≤ 10 − 4 for Prandtl number Pr = 0.8 and aspect ratios 1 / 5 ≤ Γ ≤ 5 using direct numerical simulations. We characterize, for perfectly insulating sidewall boundary conditions, the first transition to convection via wall mode instability and the nonlinear growth and instability of the resulting wall mode states, including a secondary transition to time dependence. We show how the radial structure of the vertical velocity u z and the temperature T is captured well by the linear eigenfunctions of the wall mode instability where the radial width of u z is δ u z ∼ Ek 1 / 3 r / H whereas δ T ∼ e − k r ( k is the wave number of a laterally infinite wall mode state). The disparity in spatial scales for Ek = 10 − 6 means that the heat transport is dominated by the radial structure of u z since T varies slowly over the radial scale δ u z . We further describe how the transition to a state of bulk convection is influenced by the presence of the wall mode states. We use temporal and spatial scales as measures of the local state of convection and the Nusselt number Nu as representative of global transport. Our results elucidate the evolution of the wall state of rotating convection and confirm that wall modes are strongly linked with the boundary zonal flow being the robust remnant of nonlinear wall mode states. We also show how the heat transport ( Nu ) contributions of wall modes and bulk modes are related and discuss approaches to disentangling their relative contributions. Published by the American Physical Society 2024

58 GEOSCIENCES↗
DOE OSTI2025

CCN Measurements at Urban Site during CoURAGE

Cloud condensation nuclei (CCN) measurements were collected during CoURAGE from March - June 2025 at the BSEC urban atmospheric chemistry supersite (39.32057 N, 76.6246 W). CCN number concentrations (# cm-3) were obtained at a frequency of 1 second using a cloud condensation nuclei counter (CCN-100, Droplet Measurement Technologies). The CCN counter was operated in stepping mode, measuring CCN over a range of supersaturations from 0.2 to 1.0%. The settings of the instrument were set such that the supersaturation increased in increments of 0.2% up to the maximum supersaturation, and then decreased in increments of 0.2% down to the minimum supersaturation in a repeating cycle. The supersaturation of the instrument was calibrated weekly using ammonium sulfate. The weekly calibrated supersaturation values have been applied to the data. Data during transitions between supersaturation values were removed and replaced with a value of -999. Transitions are defined as the first 210 seconds after a new supersaturation value to ensure the instrument has stabilized following a change in supersaturation. Data were also flagged with a value of -999 if there were concerns with the function of the instrument, specifically the presence of alarm codes, fogging of the optical particle counter (1st stage monitor > 0.4 V), or a sheath to sample flow ratio outside the expected range (< 9 or > 11).

CCN number density↗
DOE OSTI2024

Biogeochemical and community ecology responses to the wetting of non-perennial streams

Transitions between dry and wet hydrologic states are the defining characteristic of non-perennial rivers and streams, which constitute the majority of the global river network. Although past work has focused on stream drying characteristics, there has been less focus on how hydrology, ecology and biogeochemistry respond and interact during stream wetting. Wetting mechanisms are highly variable and can range from dramatic floods and debris flows to gradual saturation by upwelling groundwater. This variation in wetting affects ecological and biogeochemical functions, including nutrient processing, sediment transport and the assembly of biotic communities. Here, in this work, we synthesize evidence describing the hydrological mechanisms underpinning different types of wetting regimes, the associated biogeochemical and organismal responses, and the potential scientific and management implications for downstream ecosystems. This combined multidisciplinary understanding of wetting dynamics in non-perennial streams will be key to predicting and managing for the effects of climate change on non-perennial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A regularized-interface method as a unified formulation for simulations of high-pressure multiphase flows

The injection of multi-species fluids into high-pressure and high-temperature environments beyond the species' critical points is commonly found in engineering applications. At these conditions, for immiscible species, both subcritical interfacial dynamics and supercritical mixing can coexist due to variations in temperature around the mixture critical point. The modeling of these complex transcritical phenomena for large-scale configurations is so far not possible. To address this issue, we propose the Regularized-Interface Method (RIM) as a unified formulation that can describe both sub- and supercritical processes as well as the transition between them. The proposed method is derived via filtering of the nanoscale interface-resolving formulation based on van der Waals' linear gradient theory. Thus, this approach allows for the consistent modeling of interfacial dynamics that vanishes at supercritical conditions, while significantly reducing the temporal and spatial resolution constraints of the original nanoscale formulation. The resulting RIM formulation is examined in interface-capturing simulations of sub-, trans-, and supercritical fuel injection processes, involving droplets and jets. Furthermore, these results highlight the importance of resolving spatio-temporal transitions from subcritical interfacial dynamics to supercritical mixing in high-pressure multiphase simulations, in contrast to commonly employed diffused-interface methods, where interfacial dynamics are often neglected.

Interface capturing↗
DOE OSTI2024

Forecasting high-dimensional spatio-temporal systems from sparse measurements

This paper introduces a new neural network architecture designed to forecast high-dimensional spatio-temporal data using only sparse measurements. The architecture uses a two-stage end-to-end framework that combines neural ordinary differential equations (NODEs) with vision transformers. Initially, our approach models the underlying dynamics of complex systems within a low-dimensional space; and then it reconstructs the corresponding high-dimensional spatial fields. Many traditional methods involve decoding high-dimensional spatial fields before modeling the dynamics, while some other methods use an encoder to transition from high-dimensional observations to a latent space for dynamic modeling. In contrast, our approach directly uses sparse measurements to model the dynamics, bypassing the need for an encoder. This direct approach simplifies the modeling process, reduces computational complexity, and enhances the efficiency and scalability of the method for large datasets. We demonstrate the effectiveness of our framework through applications to various spatio-temporal systems, including fluid flows and global weather patterns. Although sparse measurements have limitations, our experiments reveal that they are sufficient to forecast system dynamics accurately over long time horizons. Our results also indicate that the performance of our proposed method remains robust across different sensor placement strategies, with further improvements as the number of sensors increases. This robustness underscores the flexibility of our architecture, particularly in real-world scenarios where sensor data is often sparse and unevenly distributed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Chromium enhances the mechanical performance of 3d transition metal high entropy alloys

A comprehensive examination of the compositional effects on the deformation behavior of high entropy alloys (HEAs) was conducted through nanoindentation, indentation creep, and stress relaxation experiments at ambient temperature. The alloys investigated included NiCoFe, NiCoCr, NiCoCrFe, and NiCoCrFeMn, all of which underwent identical thermomechanical processing. From the experimental results, NiCoCr exhibited the highest maximum shear stress for dislocation nucleation (13 GPa) and nanoindentation hardness (3.8 GPa) among the alloys tested. It also showed the lowest stress sensitivity (0.02) and activation volume (3–4 b 3 ) under creep and stress relaxation conditions, indicative of its superior plastic flow properties. Density functional theory (DFT) calculations further revealed an uneven charge density and larger bonding-length variation in NiCoCr due to the presence of Cr, which increased lattice distortion, impeding dislocation movement. Furthermore, in this study, post-deformation microscopy using transmission electron microscopy (TEM) revealed a high density of stacking faults and twins in NiCoCr that effectively enhanced its creep strength. The results highlight the significance of specific elemental effects, particularly from Cr in this study, over configurational entropy effect (i.e., compositional complexity) in governing the deformation microstructure and mechanical properties of HEAs. Finally, these insights will be instrumental for the design and optimization of advanced alloys for load-bearing applications.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Low-temperature access to active iron and iron/nickel nitrides as potential electrocatalysts for the oxygen evolution reaction

Low-temperature, scalable routes to transition metal nitride (TMN) nanoparticles are desirable for a wide range of applications, yet their synthesis typically requires high temperatures (>350 °C) and reactive gas environments (e.g., NH 3 or H 2 /N 2 ). Here, we report a colloidal synthesis of mono- and bimetallic TMN nanoparticles using preformed metal carbonyl clusters as precursors and urea or diethylenetriamine (DETA) as nitrogen sources. This strategy enables access to size-controlled, phase-pure ε-Fe 3 N x and Fe y Ni 3−y N nanoparticles at temperatures below 300 °C, without the need for flowing reactive gas atmospheres. By systematically varying nitrogen precursor, reaction temperature, and cluster identity, we achieve tunable nitrogen stoichiometry (x) and phase selectivity between N-rich and N-poor TMNs. Structural and magnetic characterization confirms clean decomposition of the precursors and phase formation consistent with controlled nitridation at the nanoscale. Preliminary electrochemical measurements in alkaline media demonstrate that these materials exhibit oxygen evolution reaction (OER) overpotentials comparable to RuO 2 , highlighting their viability for future electrocatalytic applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

The National Transmission Planning Study: Chapter 4: AC Power Flow Analysis for 2035 Scenarios

The National Transmission Planning Study (NTP Study) was led by the U.S. Department of Energy's Grid Deployment Office, in partnership with the National Renewable Energy Laboratory and Pacific Northwest National Laboratory. The study sought to develop new national grid-scale planning tools and methods that can be used by industry, especially when planning for interregional transmission capacity needs; identify potential transmission solutions that will provide broad-scale benefits to electric customers under a wide range of potential futures; inform planning processes for regional and interregional transmission; and identify interregional and national strategies to maintain grid reliability as the grid transitions, including to a reliance on low- and zero-carbon energy resources. The NTP Study is presented as a collection of six chapters.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2024

Response of salt intrusion in a tidal estuary to regional climatic forcing

Abstract Salinity distribution in a large tidal estuary is subject to estuarine adjustment under the influences of multiple physical drivers such as freshwater pulses and sea level rise, and is crucial to upstream water quality, aquaculture, and ecosystem functions of the estuary. To better understand the estuarine salinity response to climate change, the unstructured-grid Finite Volume Community Ocean Model was implemented to simulate the salt intrusion in the Delaware Bay Estuary. The model was first validated by multiple observational data sets and subsequently applied in an idealized setting to examine the response of salt front to freshwater pulses in high flow conditions, followed by a long-term drought condition supported by a multi-decadal streamflow drought analysis in the estuary. The model results showed that after the freshwater pulses the salt front location moved further upstream with sea level rise. Under the simulated long-term drought condition, the adjustment timescale of salt intrusion varies nonlinearly with sea level rise. With a significant increase in sea level rise, the adjustment timescale starts to decrease. This shift suggests a transition into a different regime where the estuary becomes more stratified, as indicated by an increasing bulk Simpson number with rising sea levels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Coherent Transfer of Lattice Entropy via Extreme Nonlinear Phononics in Metal Halide Perovskites

Entropy transfer in metal halide perovskites, characterized by significant lattice anharmonicity and low stiffness, underlies the remarkable properties observed in their optoelectronic applications, ranging from solar cells to lasers. The conventional view of this transfer involves stochastic processes occurring within a thermal bath of phonons, where the lattice arrangement and energy flow from higher- to lower-frequency modes. Here, we unveil a comprehensive chronological sequence detailing a conceptually distinct coherent transfer of entropy in a prototypical perovskite CH 3 NH 3 Pbl 3 . The terahertz periodic modulation imposes vibrational coherence into electronic states, leading to the emergence of mixed (vibronic) quantum beat between approximately 3 and 0.3 THz. We highlight a well-structured bidirectional time-frequency transfer of these diverse phonon modes, each developing at different times and transitioning from high to low frequencies from 3 to 0.3 THz, before reversing direction and ascending to around 0.8 THz. First-principles molecular dynamics simulations disentangle a complex web of coherent-phononic coupling pathways and identify the salient roles of the initial modes in shaping entropy evolution at later stages. Capitalizing on coherent entropy transfer and dynamic anharmonicity presents a compelling opportunity to exceed the fundamental thermodynamic (Shockley-Queisser) limit of photoconversion efficiency and to pioneer novel optoelectronic functionalities. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Resonance-stabilized radical clustering bridges the gap between gaseous precursors and soot in the inception stage

Carbonaceous particles are widespread in combustion, atmospheric, extraterrestrial, and nanomaterials environments. Resonance-stabilized radicals (RSRs) are commonly identified in fuel combustion and pyrolysis processes and play an essential role in carbonaceous particle formation. Despite their importance, comprehensive experimental and mechanistic understanding of particle inception through RSR reactions is lacking. This work investigated particle size distribution, chemical composition, and thermal behavior of soot particles generated by the flow reactor pyrolysis reactions of typical RSRs, in particular, 1-indenyl, 1-methylnaphthyl, and 2-methylnaphthyl radicals, and by the pyrolysis of hydrocarbons with a variety of structures. Particle size distributions show soot particles with mobility diameters in an incipient-particle range of 1.3 to 1.6 nm. Laser desorption/ionization mass spectrometry results suggest that soot products consist of much larger covalently bound clusters (CBCs) than those observed in the gas phase. Under our experimental conditions, the CBCs exhibit a phase transition for particles with calculated molecular diameters of around 1.5 nm. Evaporation experiments and thermogravimetric analysis of the soot products reveal distinct thermal characteristics for small and large CBCs. These results implicate CBCs as bridges between gas-phase species and soot particles. The present work provides a soot-inception mechanism called RSR clustering (RSRC) that is characterized by the reactive clustering of RSRs. The RSRC mechanism contrasts with conventional soot formation models that attribute soot inception primarily to the aggregation of large-size polycyclic aromatic hydrocarbons.

carbonaceous particle↗
DOE OSTI2024

Vanishing adsorption limit of Riemann problem solutions for the polymer model

Here we examine the vanishing adsorption limit of solutions of Riemann problems for the Glimm–Isaacson model of chemical flooding of a petroleum reservoir. A contact discontinuity is deemed admissible if it is the limit of traveling waves or rarefaction waves for an augmented system that accounts for weak chemical adsorption onto the rock. We prove that this criterion justifies the admissibility criteria adopted previously by Keyfitz–Kranzer, Isaacson–Temple and de Souza–Marchesin, provided that the fractional flow function depends monotonically on chemical concentration. We also demonstrate that the adsorption criterion selects the undercompressive contact discontinuities required to solve the general Riemann problem in an example model with non-monotone dependence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Chemically Separable Ruthenium Hydride Isomers with Distinct Hydride Transfer Properties

Transition metal hydrides are key intermediates in biological and industrial catalysis, where control over hydride donor ability (hydricity) is essential for optimizing reactivity. Herein, we report a series of isomeric ruthenium hydrides in which the ligand trans to the ruthenium hydride bond–either an N-heterocyclic carbene or pyridine–modulates the thermodynamic hydricity by up to 8 kcal mol –1 . These hydrides exhibited distinct reactivity toward CO 2 and various organic hydride acceptors, enabling detailed kinetic and mechanistic analysis. Stopped-flow experiments, isotopic labeling, and computational studies supported an outer-sphere hydride transfer mechanism. Linear free energy relationships (LFERs) and Marcus relationships were utilized to correlate the changes in thermodynamics and kinetics, revealing that ligands with strong trans effects and trans influence can disrupt conventional scaling relationships, which can be a powerful strategy for promoting new reactivity paradigms in hydride transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Neoclassical transport and profile prediction in transport barriers

Strong gradient regions in tokamaks, such as the pedestal or internal transport barriers, are regions of reduced turbulence where neoclassical transport can play a dominant role. However, standard neoclassical transport theory assumes that the gradient length scales of density, temperature, and potential are of the order of the system size. In the pedestal, gradient length scales are much shorter and are measured to be of the order of the ion poloidal gyroradius. We present an extension of neoclassical theory that is applicable in transport barriers of large aspect ratio tokamaks. We show that particle and momentum transport are connected in such a way that a source of parallel momentum can drive a significant neoclassical ion particle flux. In strong gradient regions, density, electric potential, mean parallel flow, and ion temperature are shown to no longer be flux functions. Instead, they have a small but important poloidally varying piece that modifies the transport equations to lowest order. This introduces a nonlinearity in the transport problem through the coupling with quasineutrality that yields multiple co-existing solutions when solving for the plasma profiles. The different solutions could be connected to low and high transport states and jumps between solutions could provide a new neoclassical explanation for H-L back-transitions.

Trinczek, Silvia [Princeton Plasma Physics Laborat↗
DOE OSTI2025

Methane pyrolysis by Joule heating for graphitic carbon and hydrogen production

The global energy transition toward sustainability requires technologies that can decarbonize energy carriers and fuels while producing valuable materials. Methane, a primary component of natural gas, is both a high-energy-density fuel and a significant greenhouse gas. This study reports an approach for methane pyrolysis utilizing Joule heating within the deposition substrate to drive the endothermic reaction. With electric current passing through a resistive porous carbon cloth, heat is generated to break C-H bonds of methane molecules. Here, the decomposition of methane as it flows through the cloth results in hydrogen production and the formation of conformally layered graphite around the carbon fibers. The effects of input power, chamber pressure, feedstock flow rate, and process duration on hydrogen and graphite production are characterized via in situ mass spectrometry and laser absorption spectroscopy, resulting in methane conversion rates up to 88%, with hydrogen and carbon yields of 82% and 72%, respectively. Material characterization verifies uniform high-quality graphite deposition, with a Raman I D /I G ratio of 0.1 and 3.38 Å d-spacing. This Joule heating method for catalyst-free methane pyrolysis offers the potential for advancing hydrogen production technology by simultaneously producing valuable materials such as solid graphite, thus enhancing the economic viability of the fuel decarbonization process.

Energy Resources↗
DOE OSTI2025

Ultralow-temperature cryogenic transmission electron microscopy using a new helium flow cryostat stage

Advances in cryogenic electron microscopy have opened new avenues for probing quantum phenomena in correlated materials. This study reports the installation and performance of a new side-entry condenZero cryogenic cooling system for JEOL (Scanning) Transmission Electron Microscopes (S/TEM), utilizing compressed liquid helium (LHe) and designed for imaging and spectroscopy at ultra-low temperatures. The system includes an external dewar mounted on a vibration-damping stage and a pressurized, low-noise helium transfer line with a remotely controllable needle valve, ensuring stable and efficient LHe flow with minimal thermal and mechanical noise. Performance evaluation demonstrates a stable base temperature of 4.37 K measured using a Cernox bare chip sensor on the holder with temperature fluctuations within ±0.004 K. Complementary in-situ electron energy-loss spectroscopy (EELS) via aluminum bulk plasmon analysis was used to measure the local specimen temperature and validate cryogenic operation during experiments. The integration of cryogenic cooling with other microscopy techniques, including electron diffraction and Lorentz TEM, was demonstrated by resolving charge density wave (CDW) transitions in NbSe2 using electron diffraction, and imaging nanometric magnetic skyrmions in MnSi via Lorentz TEM. In conclusion, this platform provides reliable cryogenic operation below 7 K, establishing a low-drift route for direct visualization of electronic and magnetic phase transformations in quantum materials.

Charge density wave↗
DOE OSTI2025

Machine Learning for Real-time Fusion Plasma Behavior Prediction and Manipulation (Final Report)

The goal of this project is to implement real-time analysis of 2D Beam Emission Spectroscopy (BES) data to predict and control transient and high-bandwidth events at DIII-D. In essence, we wish to bring high-bandwidth fluctuation diagnostics into the realm of real-time measurements and control. The BES ML models will necessarily be deep neural networks (DNN) with a “data flow” architecture for compatibility with high-throughput, low-latency evaluation on a field-programmable gate array (FPGA) or other emerging processor technologies. The real-time output will be fed to the plasma control system (PCS) for real-time control tasks, specifically for ELM control and avoidance and for QH-mode access and sustainment. We anticipate that the real-time analysis of fluctuation diagnostics will create new enabling technologies to predict and control transient events such as confinement mode transitions, edge-localized modes, Alfven eigenmode events, and disruptions. The proposed research is aligned with ITER research needs and DIII-D programmatic goals. For instance, the prediction and avoidance of ELM events is critical for ITER machine safety. Also, H-mode access with RMP ELM suppression in ITER is an active research area due to high separatrix density, narrow SOL width, and elevated LH transition power threshold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗