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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effective properties of semitransparent radiative cooling materials with spectrally variable properties

Radiative cooling is a promising solid-state, non-vapor-compression technology for passive refrigeration and air conditioning. Although this phenomenon occurs naturally, achieving a significant amount of cooling to make it a technically and economically viable technology requires highly engineered, spectrally selective radiative surfaces. These characteristics make radiative cooling difficult to estimate, particularly when it is integrated with other systems such as photovoltaic panels or building envelopes. The complexity further increases when the substrate also participates in the radiative cooling (along with the radiative coating). Energy estimation is becoming increasingly critical because of the recent focus on the semitransparent radiative coatings that transmit a variety of colors to enhance the aesthetic appeal of the system. In this work, we propose an iterative method to calculate the effective radiative properties, which provides the same net radiative cooling that would be observed using the spectral properties at both the coating and substrate surfaces. Compared to traditional methods that rely on either computationally expensive full spectral analysis or methods for averaging each radiative surface parameter locally, our proposed method focuses on calculating effective properties that provide the same the net cooling effect as a full spectral analysis by accounting the emissivity, absorptivity, and transmissivity collectively, thereby providing an overall estimation error of less than 0.2%. We believe that this study will be beneficial to the engineering communities that employ complex simulation codes and require lumped solar and thermal radiation related parameters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

TChem v2.0 - A Software Toolkit for the Analysis of Complex Kinetic Models

TChem is an open source software library for solving complex computational chemistry problems and analyzing detailed chemical kinetic models. The software provides support for: complex kinetic models for gas-phase and surface chemistry; thermodynamic properties based on NASA polynomials; species production/consumption rates; stable time integrator for solving stiff time ordinary differential equations; and, reactor models such as homogenous gas-phase ignition (with analytical Jacobian matrices), continuously stirred tank reactor, plug-flow reactor. This toolkit builds upon earlier versions that were written in C and featured tools for gas-phase chemistry only. The current version of the software was completely refactored in C++, uses an object-oriented programming model, and adopts Kokkos as its portability layer to make it ready for the next generation computing architectures i.e., multi/many core computing platforms with GPU accelerators. We have expanded the range of kinetic models to include surface chemistry and have added examples pertaining to Continuously Stirred Tank Reactors (CSTR) and Plug Flow Reactor (PFR) models to complement the homogenous ignition examples present in the earlier versions. To exploit the massive parallelism available from modern computing platforms, the current software interface is designed to evaluate samples in parallel, which enables large scale parametric studies, e.g. for sensitivity analysis and model calibration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Simple and Accurate One-Body Energy and Dipole Moment Surfaces for Water and Beyond

Water is often the testing ground for new, advanced force fields. While advanced functional forms for intermolecular interactions have been integral to the development of accurate water models, less attention has been paid to a transferable model for intramolecular valence terms. In this work, we present a one-body energy and dipole moment surface model, named 1B-UCB, that is simple yet accurate and can be feasibly adapted for both standard and advanced potentials. 1B-UCB for water is comparable in accuracy to those with much more complex functional forms, despite having drastically fewer parameters. The parametrization protocol has been implemented as part of the Q-Force automated workflow and requires only a quantum mechanical Hessian calculation as reference data, hence allowing it to be easily extended to a variety of molecular systems beyond water, which we demonstrate on a selection of small molecules with different symmetries.

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

Importance of Spatially Continuous Urban Surface Properties in Urban‐Resolving Earth System Modeling

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. Furthermore, these findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Cheng, Yifan [University of Illinois Urbana-Champa↗
DOE OSTI2022

Geometric prior of multi-resolution yielding manifolds and the local closest point projection for nearly non-smooth plasticity

Elastoplasticity models often introduce a scalar-valued yield function to implicitly represent the boundary between elastic and plastic material states. Here this paper introduces a new alternative where the yield envelope is represented by a manifold of which the topology and the geometry are learned from a set of data points in a parametric space (e.g. principal stress space, π-plane). Here, deep geometric learning enables us to reconstruct a highly complex yield envelope by breaking it down into multiple coordinate charts. The global atlas that consists of these coordinate charts in return allows us to represent the yield surface via multiple overlapping patches, each with a specific local parametrization. This setup provides several advantages over the classical implicit function representation approach. For instance, the availability of coordinate charts enables us to introduce an alternative stress integration algorithm where the trial stress may project directly on a local patch and hence circumvent the issues related to non-smoothness and the lack of convexity of yield surfaces. Meanwhile, the local parametric approach also enables us to predict hardening/softening locally in the parametric space, even without complete knowledge of the yield surface. Comparisons between the classical yield function approach on the non-smooth plasticity and anisotropic cam-clay plasticity model are provided to demonstrate the capacity of the models for highly precise yield surface and the feasibility of the implementation of the learned model in the local stress integration algorithm.

42 ENGINEERING↗
DOE OSTI2022

Nucleation and growth of molybdenum disulfide grown by thermal atomic layer deposition on metal oxides

To enable greater control over thermal atomic layer deposition (ALD) of molybdenum disulfide (MoS 2 ), here we report studies of the reactions of molybdenum hexafluoride (MoF 6 ) and hydrogen sulfide (H 2 S) with metal oxide substrates from nucleation to few-layer films. In situ quartz crystal microbalance experiments performed at 150, 200, and 250 °C revealed temperature-dependent nucleation behavior of the MoF 6 precursor, which is attributed to variations in surface hydroxyl concentration with temperature. In situ Fourier transform infrared spectroscopy coupled with ex situ x-ray photoelectron spectroscopy (XPS) indicated the presence of molybdenum oxide and molybdenum oxyfluoride species during nucleation. Density functional theory calculations additionally support the formation of these species as well as predicted metal oxide to fluoride conversion. Residual gas analysis revealed reaction by-products, and the combined experimental and computational results provided insights into proposed nucleation surface reactions. With additional ALD cycles, Fourier transform infrared spectroscopy indicated steady film growth after ~13 cycles at 200 °C. XPS revealed that higher deposition temperatures resulted in a higher fraction of MoS 2 within the films. Deposition temperature was found to play an important role in film morphology with amorphous films obtained at 200 °C and below, while layered films with vertical platelets were observed at 250 °C. Finally, these results provide an improved understanding of MoS 2 nucleation, which can guide surface preparation for the deposition of few-layer films and advance MoS 2 toward integration into device manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High–Resolution Maps of Near–Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

Permafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter–scale maps of near–surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near–surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k–fold cross validation, and the modeled extents of near–surface permafrost were compared to the observed extents at each site. At–a–site near–surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at–a–site prediction (70%–83%), yet they had greater accuracy when transferred to the non–training site (62%–78%). These models demonstrate the potential for integrating high–resolution spatial data and machine learning models to develop maps of near–surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Identifying Dense NiSe 2 /CoSe 2 Heterointerfaces Coupled with Surface High-Valence Bimetallic Sites for Synergistically Enhanced Oxygen Electrocatalysis

Constructing heterostructures with abundant interfaces is essential for integrating the multiple functionalities in single entities. Herein, the synthesis of NiSe 2 /CoSe 2 heterostructures with different interfacial densities via an innovative strategy of successive ion injection is reported. The resulting hybrid electrocatalyst with dense heterointerfaces exhibits superior electrocatalytic properties in an alkaline electrolyte, superior to other benchmarks and precious metal catalysts. Advanced synchrotron techniques, post structural characterizations, and density functional theory (DFT) simulations reveal that the introduction of atomic-level interfaces can lower the oxidation overpotential of bimetallic Ni and Co active sites (whereas Ni$^{2+}$ can be more easily activated than Co$^{2+}$) and induce the electronic interaction between the core selenides and surface in situ generated oxides/hydroxides, which play a critical role in synergistically reducing energetic barriers and accelerating reaction kinetics for catalyzing the oxygen evolution. Hence, the heterointerface structure facilitates the catalytic performance enhancement via increasing the intrinsic reactivity of metallic atoms and enhancing the synergistic effect between the inner selenides and surface oxidation species. This work not only complements the understanding on the origins of the activity of electrocatalysts based on metal selenides, but also sheds light on further surface and interfacial engineering of advanced hybrid materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Role of turbulent separatrix tangle in the improvement of the integrated pedestal and heat exhaust issue for stationary-operation tokamak fusion reactors

Abstract The magnetic separatrix surface is designed to provide the final and critical confinement to the hot stationary-operation core plasma in modern tokamak reactors in the absence of an external magnetic perturbation (MP) or transient magneto-hydrodynamic perturbation, while diverting the exhaust heat to divertor plates. All the stationary operational boundary plasma studies and reactor designs have been performed under this assumption. However, there has been a long-standing suspicion that a stationary-operation tokamak plasma even without external MPs or edge localized modes (ELMs) activities may not have a stable closed separatrix surface, especially near the magnetic X-point. Here, the first gyrokinetic numerical observation is reported that the divertor separatrix surface, due to homoclinic tangles caused by intrinsic electromagnetic turbulence, is not a stable closed surface in a stationary operation phase even without MPs or ELMs. Unlike the MP- or ELM-driven homoclinic tangles that could cause deleterious effects to core confinement or divertor plates, it is found that the micro-turbulence driven homoclinic tangles could connect the divertor plasma to the pedestal plasma in a constructive way by broadening the divertor heat-exhaust footprint and weakening the pedestal slope to the ELM-safe direction. Micro-turbulent homoclinic tangles can open a new research direction in understanding and controlling these two most troublesome and non-locally connected edge-plasma issues in a tokamak fusion reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

In Situ Surface Reconstruction via Lithium Residue Regulation for Direct Recycling of Ni-Rich Cathodes

Surface stability is crucial for the long cycling performance of Ni-rich cathodes, as it dictates and governs side reactions, preserves crystal integrity, and mitigates capacity degradation during cycling. For spent Ni-rich cathodes targeted for one-step direct recycling, constructing a robust and stable surface is particularly challenging because prior cycling induces severe structural and morphological degradation. Here, in this study, we introduce an in situ surface reconstruction strategy that converts surface lithium residues into a protective layer via a direct liquid-phase coating with ammonium dihydrogen phosphate (ADP). During the process, residual lithium remaining after the hydrothermal relithiation is removed, while a conformal lithium phosphate (Li 3 PO 4 , LPO) layer is formed to act as both a chemical barrier and a structural stabilizer. This dual function enhances cycling stability and rate capability in regenerated cathodes, and the approach is applicable to various Ni-rich compositions including spent LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) and scrap LiNi 0.866 Mn 0.066 Co 0.05 Al 0.018 O 2 (NCMA). Its scalability and compositional versatility make it a promising route for sustainable regeneration of high-performance cathode materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mixed Nanosphere Assemblies at a Liquid–Liquid Interface

The in-plane packing of gold (Au), polystyrene (PS), and silica (SiO 2 ) spherical nanoparticle (NP) mixtures at a water–oil interface is investigated in situ by UV–vis reflection spectroscopy. All NPs are functionalized with carboxylic acid such that they strongly interact with amine-functionalized ligands dissolved in an immiscible oil phase at the fluid interface. This interaction markedly increases the binding energy of these nanoparticle surfactants (NPSs). The separation distance between the Au NPSs and Au surface coverage are measured by the maximum plasmonic wavelength (λ max ) and integrated intensities as the assemblies saturate for different concentrations of non-plasmonic (PS/SiO 2 ) NPs. Further, as the PS/SiO 2 content increases, the time to reach intimate Au NP contact also increases, resulting from their hindered mobility. λ max changes within the first few minutes of adsorption due to weak attractive inter-NP forces. Additionally, a sharper peak in the reflection spectrum at NP saturation reveals tighter Au NP packing for assemblies with intermediate non-plasmonic NP content. Grazing incidence small angle X-ray scattering (GISAXS) and scanning electron microscopy (SEM) measurements confirm a decrease in Au NP domain size for mixtures with larger non-plasmonic NP content. The results demonstrate a simple means to probe interfacial phase separation behavior using in situ spectroscopy as interfacial structures densify into jammed, phase-separated NP films.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Liquid lithium wetting and percolation in a porous tungsten/liquid Li plasma facing component (PFC)

This work explores the concept of a hybrid material system designed to protect the plasma from high-Z material emission while also protecting an underlying high-Z wall material from erosion by integrating a low-Z component in the liquid phase. Plasma-surface interaction properties of a porous tungsten (W)-liquid metal hybrid system, having the favorable bulk thermomechanical properties of W while serving as a scaffold for a liquid metal with self-healing and radiative vapor shielding characteristics, are examined. W-substrates with 70% density of bulk W and 1–5 μm sized pores have been fabricated with 50-nm W powders using spark plasma sintering. Enhanced lithium (Li) wettability, driven by percolation through the porous W architecture, is demonstrated with in-situ liquid Li drop measurements. Finally, results show complete wetting of liquid Li at 250 °C in the porous W, 100 °C lower temperature than what has been observed on traditional W surfaces. In operando ion beam analysis of Li films deposited on porous W substrates provides microscopic evidence of Li percolation into the substrate and a first look at D retention up to a depth of 100 nm after plasma exposure at a flux of 10 20 m –2 s –1 , 250 eV/amu D + plasma to a fluence of 1.16 × 10 23 m –2 at a temperature of 200 °C.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Phase-field modeling of diffusion bonding in 316H stainless steel: Impact of processing conditions on grain morphology and bonding quality

A novel multi-phase, multi-component phase‐field model is presented to study the diffusion bonding of 316H stainless steel. Combined with targeted experimental investigations, this model simulates the bond-growth process and predicts the bonding quality. Unlike previous models, our approach captures the simultaneous evolution of voids and grain structures, while quantifying bonding quality using defined bonding ratio. A comprehensive analysis of bond process control is performed by changing temperature, pressure and surface roughness observing the resulting bond structure, which is consistent with experimental observations and analytical predictions. Temperature is determined to be the dominant factor, with the transition from a flat to a robust bond occurring between 1000 °C and 1050 °C. At the ideal bonding temperature of 1050 °C, a surface roughness exceeding 0.6 μm or an applied stress below 4 MPa results in poor bonding quality. Beyond this, higher pressures and smoother surfaces reduce void size, accelerate void shrinkage, and lead to improved bond integrity. This diffuse-interface model can be extended to other material systems if supplied with appropriate thermodynamic and kinetic data. In conclusion, this makes it an effective modeling platform for optimizing high-temperature diffusion bonding and developing reliable bonded components such as compact heat exchangers.

Diffusion bonding↗
DOE OSTI2024

Measurement of 3 Λ H production in Pb–Pb collisions at √ s NN = 5.02 TeV

The first measurement of 3 Λ H and $^{3}_{\overline{Λ}}$$\overline{H}$ differential production with respect to transverse momentum and centrality in Pb–Pb collisions at √ s NN = 5.02 TeV is presented. The 3 Λ H has been reconstructed via its two-charged-body decay channel, i.e., 3 Λ H → 3 He → π - . A Blast-Wave model fit of the p T -differential spectra of all nuclear species measured by the ALICE collaboration suggests that the kinetic freeze-out surface is consistent with that of other nuclei. The ratio between the integrated yields of 3 Λ H and 3 He is compared to predictions from the statistical hadronisation model and the coalescence model, with the latter being favoured by the presented measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Spatio-Kinetic Electronic Heterogeneity in MoS 2 Revealed by Ultrafast Electron Microscopy: Implications for Optoelectronics

There is broad interest in layered, two-dimensional (2D) semiconductors owing to their high optical absorption and ability to heterogeneously integrate with various substrates. In such layered semiconductors, mesoscopic imperfections, such as surface step edges, may affect charge carrier kinetics and device performance, but studying their effects on carrier transport with sufficient spatial and temporal resolution is a challenge. Using scanning ultrafast electron microscopy, we image the near-surface charge carrier kinetics with μm/ps spatiotemporal resolution in single-crystal MoS 2 samples with surface steps tens of nanometers in height. We find an approximately 3-fold increase in surface trap density near such surface steps compared to the uniform, flat surface regions. Despite the difference in trap state density, filling of the traps occurs over the same time scale (∼100 ps), but carrier recovery is much slower near the step compared to the uniform regions of the material. Furthermore, these results provide an approach to measure ultrafast dynamics and determine the required uniformity of layered materials depending on the speed limit constraints for specific applications.

SEM↗
DOE OSTI2021

Inhibition of Amyloid β-Induced Lipid Membrane Permeation and Amyloid β Aggregation by K162

Alzheimer's disease (AD) is characterized by progressive neurodegeneration associated with amyloid β (Aβ) peptide aggregation. The aggregation of Aβ monomers (AβMs) leads to the formation of Aβ oligomers (AβOs), the neurotoxic Aβ form, capable of permeating the cell membrane. Here, we investigated the effect of a fluorene-based active drug candidate, named K162, on both Aβ aggregation and AβO toxicity toward the bilayer lipid membrane (BLM). Electrochemical impedance spectroscopy (EIS), atomic force microscopy (AFM), and molecular dynamics (MD) were employed to show that K162 inhibits AβOs-induced BLM permeation, thus preserving BLM integrity. In the presence of K162, only shallow defects on the BLM surface were formed. Apparently, K162 modifies Aβ aggregation by bypassing the formation of toxic AβOs, and only nontoxic AβMs, dimers (AβDs), and fibrils (AβFs) are produced. Unlike other Aβ toxicity inhibitors, K162 preserves neurologically beneficial AβMs. This unique K162 inhibition mechanism provides an alternative AD therapeutic strategy that could be explored in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗