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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Electromagnetic Induction (EMI) Data, 2024, Trail Creek, Colorado

This dataset contains Electromagnetic Induction (EMI) data collected at Trail Creek, Colorado, in 2024. EMI surveys were conducted to investigate the spatial distribution of electrical conductivity in the subsurface, providing insights into soil moisture and subsurface geological features. The surveys were performed along multiple transects to capture variations in conductivity influenced by changes in soil composition, moisture content, and underlying geological structures. This dataset complements other geophysical data collected in the region, including Electrical Resistivity Tomography (ERT) and Terrestrial LiDAR Scanning (TLS), providing a detailed understanding of the subsurface and its impact on surface vegetation and hydrological processes. The data are valuable for environmental geophysics, ecological research, and hydrological modeling in mountainous ecosystems. The files include: - data.zip: the raw EMI data (.csv) - inversion.zip: the inverted resistivity model (.csv and .kml) - kriging.zip: the kriging resistivity model (.csv, .tif, .kmz) - flmd.csv: file level metadata file describing all files within this dataset - dd.csv: data dictionary file describing the column headers within CSV files This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

CMD Mini-Explorer↗
DOE OSTI2026

Enhancement of HLW glass property-composition models

Since the WTP compositional space of HLW glasses is extremely large, development of HLW property-composition models is a multi-year task consisting of multiple phases. The primary focus of this work was to enhance the WTP HLW models of interest including PCT releases, spinel crystallization (T1%), viscosity, electrical conductivity, and TCLP-Cd response. Model development to predict nepheline formation upon CCC is the subject of a separate task. In particular, the earlier work has produced property-composition models for glass melt viscosity and glass melt electrical conductivity that showed good performance, while models for PCT releases and spinel crystallization (T1%) required improvement. Therefore, more efforts were directed in the present work to collect data and improve model performance for HLW glass PCT releases and spinel crystallization than for other properties. The present work is a continuation of earlier development phases and is responsive to the applicable Test Plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Field and Model Data Associated with the Manuscript “Drivers of Streamflow Intermittency in Humid Regions: 1. Evaluating Above- and Below-ground Controls of Flow Persistence in a Forested Catchment”

This package contains field data, modeling files, and scripts supporting the investigation of the drivers of streamflow intermittency in a forested catchment. It includes the field data collected from electrical resistivity tomography (ERT) surveys, ground penetrating radar (GPR), continuous self-potential (SP) monitoring, electromagnetic (EM) imaging, groundwater and stilling well. In addition, it contains the data and results of the coupled water- and electrical-flow model developed using the COMSOL Multiphysics and Advanced Terrestrial Simulator (ATS), as well as software files and Jupyter notebooks used to process the data and generate figures in the manuscript submitted for peer review. The data archive is organized in the following directories: 1) Climate Includes hourly precipitation and daily evapotranspiration time series (2024 – 2025) provided as CSV files, alongside a text file detailing dataset units. 2) Coupled_model Contains two subfolders: Synthetic and Field_Application subfolder. Synthetic subfolder contains the ATS XML input script (can be opened using any code editor) for the four synthetic hydrological cases tested (Connected and gaining, Connected and losing, Disconnected and losing, and dry stream). It also includes other experimental cases to test the influence of precipitation and concentration gradient. For each synthetic case, the flow model simulation is executed using the ATS XML scripts and the included Python script (generate_data_set.py) to convert ATS output to COMSOL-ready input. COMSOL Multiphysics template (.mph can be opened with the commercial software COMSOL and requires a license) is executed using the ATS output data to simulate the potential field. It also includes the Synthetic_model_plot.ipynb (can be opened using any code editor) to visualize the SP result and generate manuscript figures. The data subfolder contains mesh files to run both the ATS (.exo and .stl files can be viewed using Paraview; .h5 files can be opened using HDFView software and h5py Python package) and COMSOL models. Field_Application subfolder contains two subfolders: ES_MDA_inversion and Final_Model. ES_MDA_inversion contains the Python script (.py can be opened using any code editor) and SP observation data used to run the Ensemble Smoother with Multiple Data Assimilation (ES-MDA) inversion sequence to get the optimal model parameters. The Final_model subfolder contains the ATS XML input scripts, data files, output data for the two SP sites. The same workflow steps outlined for the Synthetic subfolder apply here. It also contains the Jupyter notebook (Plot_final_calib.ipynb) to visualize the results of the modeled SP, stream-groundwater exchange and moisture content. 3) Discharge Includes the electrical conductivity (EC) time series (provided as CSV files) from salt slug injections. It also includes the Jupyter notebook (Discharge_process.ipynyb) used to estimate discharge. All discharge measurements collated into rating_curve_processed.csv 4) EM Contains the CSV file of the EM data from the DUALEM-42, including spatial coordinates (x, y, z), apparent conductivity, and in-phase measurements at 2 m coil separations for horizontal coplanar (HCP) and perpendicular (PRP) geometries. 5) ERT Contains raw resistivity data (provided as CSV files), spatial location of each of the electrodes (provided as CSV files), and files used for the resistivity inversion (.resipy can be opened with the open-source ResIPy software). 6) GPR Includes GPR field datasets collected at 100 MHz and 250 MHz antenna frequencies, along with the processing/interpretation project file (GPR_process.gpz can be viewed using EKKO_Project 6, a commercial software by Sensors & Software that requires a license). 7) Slug_test Includes the slug test data at all the groundwater wells provided as CSV files, as well as the Jupyter notebook (Slug_test.ipynb) for calculating hydraulic conductivity. 8) SP Contains the SP data collected in field at the two SP sites (one in the perennial reach and the other in the intermittent reach), provided as DAT files. 9) Well_data Contains two subfolders: 1) Raw, which provides unprocessed pressure, electrical conductivity and temperature timeseries downloaded from the loggers in all the groundwater and stilling wells, and 2) Processed, which contains sorted, QA/QC timeseries data for each well. The data archive also contains data_process.ipynb, a Jupyter notebook used for field data analysis and generating figures (plotting well, SP, climate, and discharge data, as well as calculating head gradient at sites with nested groundwater wells). It also includes DTW.ipynb, a Jupyter notebook containing the code for the dynamic time warping (DTW) with sliding window to evaluate SP signal synchronicity.

ATS↗
DOE OSTI2026

Temperature and conductivity in shock compressed bridgmanite MgSiO 3 up to 2 TPa

The melting behavior and transport properties of MgSiO 3 at multi-megabar pressures remain poorly constrained despite their importance for high-pressure silicate physics. Here we report the first direct measurements of temperature and optical reflectivity in shock-compressed bridgmanite (MgSiO 3 ) using laser-driven decaying shock compression combined with velocimetry and optical pyrometry. Temperature and reflectivity data spanning approximately 4000–60 000 K were used to constrain the MgSiO 3 melting curve and to infer its electrical conductivity. We find that the MgSiO 3 melting curve becomes shallower than that of iron above 400 GPa, yielding lower melting temperatures in planetary mantles than predicted by several previous theoretical estimates. Across the solid-liquid transition, the inferred electrical conductivity increases significantly, reaching ∼2000 Ω cm −1 . These results provide experimental benchmarks for theoretical models of silicate melting and transport under extreme pressure-temperature conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Additive‐Free Oxidized Spiro‐MeOTAD Hole Transport Layer Significantly Improves Thermal Solar Cell Stability

Perovskite solar cells are among the most promising new solar technologies, already surpassing polycrystalline silicon solar cell efficiencies. The stability of the highest efficiency devices at elevated temperature is, however, poor. These cells typically use Spiro-MeOTAD as the hole transporting layer. It is generally believed that additives, required for enhancing electrical conductivity and optimizing energy level alignment, are responsible for the reduced stability—inferring that Spiro-MeOTAD based hole transporting layers are intrinsically unstable. Here, a reliable noble metal free synthesis of Spiro-MeOTAD (bis(trifluoromethane)sulfonimide) 4 is presented which is used as the oxidizing agent. No additives are added to the partially oxidized Spiro-MeOTAD hole-transporting layer. Device efficiencies up to 24.2% are achieved. Electrical conductivity is largely developed by the first 1% oxidation. Further oxidation shifts the energy levels away from the vacuum level, which allows tuning of the energy level alignment without the use of additives—contradicting the current understanding of this system. Without additives, devices demonstrate significant improvement in stability at elevated temperatures up to 85 °C under one sun over 1400 h continuous illumination. The remaining degradation is pinpointed to ion migration and reactions in the perovskite layer which may be further suppressed with compositional engineering and adequate ion barrier layers.

14 SOLAR ENERGY↗
DOE OSTI2025

Refining the two-band model for highly compensated semimetals using thermoelectric coefficients

In studying compensated semimetals, the two-band model has proven extremely useful in capturing electrical conductivity under magnetic field, as a function of density and mobility of electronlike and holelike carriers. However, it rarely offers practical insight into magnetothermoelectric properties. Here, in this work, we report the field dependence of thermoelectric (TE) coefficients in a highly compensated semimetal NbSb 2 , where we find the Seebeck (𝑆 𝑥⁢𝑥 ) and Nernst (𝑆 𝑥⁢𝑦 ) coefficients increase quadratically and linearly with applied magnetic field, respectively. Such field dependence was predicted in previous work that studied a system of two parabolic bands, within semiclassical Boltzmann transport theory when the following two conditions are simultaneously met: 𝜔 𝑐 ⁢𝜏 ≫ 1 and tan ⁡𝜃 𝐻 ≪ 1, where 𝜔 𝑐 and 𝜏 refer to the cyclotron frequency and relaxation time, respectively, and 𝜃 𝐻 is the Hall angle. Under these conditions, we find the field dependence of the TE coefficients directly provides a relation between the electronlike (𝑛 𝑒 ) and holelike (𝑛 ℎ ) carrier densities, which in turn can be used to refine two-band model fitting. With this, we find the compensation factor ($\frac{|Δ⁢𝑛|}{𝑛_{𝑒}}$, where Δ⁢𝑛 = 𝑛 𝑒 −𝑛 ℎ ) of NbSb 2 is two orders of magnitude smaller than what was found in unrestricted fitting, resulting in a larger saturation-field scale for magnetoresistance. Within the same framework of the semiclassical theory, we also deduce that the thermoelectric Hall angle tan⁡ 𝜃 𝛾 = $\frac{𝑆_{𝑥⁢𝑦}}{𝑆_{𝑥⁢𝑥}}$ can be expressed as ($\frac{Δ⁢𝑛}{𝑛_{𝑒}}$ ×𝜔 𝑐 ⁢𝜏) −1 , which serves as a parameter to predict the degree of compensation. Our findings offer crucial insights into identifying empirical conditions for field-induced enhancement of TE performance and into engineering-efficient thermoelectric devices based on semimetallic materials.

electrical conductivity↗
DOE OSTI2026

Surfactant Effects on Carbon Black Slurries for Aqueous Flow-Electrode Applications

Aqueous carbon black (CB) slurries are promising for flow-electrode applications due to their low cost and high electrical conductivity. Here, in this study, we investigate the impact of introducing a nonionic surfactant (Tween 20) on the rheological and electrical properties of 5 wt % Vulcan XC72R CB slurries in a 50 mM NaCl aqueous solution. We observe a Tween 20 critical concentration around 1.2 wt % that triggers an abrupt transition from a conductive gel to a high-resistance Newtonian fluid. This sudden network collapse coincides with a 250-fold reduction in settled mass, a 1–2 order of magnitude drop in viscosity, and a nearly 100-fold decrease in slurry conductivity. Centrifuged pellet conductivity measurements support the conclusion that this performance loss is largely due to the destruction of the gel network, rather than increased particle-to-particle resistance. SEM imaging suggests that the network is built from large 10 to 50 μm agglomerates that are fully dissolved above the critical surfactant concentration. We found that subcritical surfactant addition improved slurry shelf stability over 90 days, but that electrochemical cell testing revealed progressive performance degradation during operation. These results highlight the need for strategies that maximize long-term electrical conductivity without compromising viscosity, sedimentation stability, or resistance to accumulation on internal surfaces.

Materials science↗
DOE OSTI2025

In-plane thermal conductivity and the applicability of the Wiedemann–Franz law in dilute AlCu thin films

The Wiedemann–Franz (WF) law correlates heat and charge transport in metals. However, the validity of this correlation remains an open-ended question, especially in the context of inelastic scattering at room temperature. To address this gap in knowledge, we perform independent measurements of the in-plane thermal and electrical conductivities across four AlCu (0.5% Cu) films [thickness (⁠h⁠) ≈ 174, 98, 53, and 24 nm] using optical pump–probe metrologies and four-point probe techniques, respectively. For in-plane thermal conductivity measurements, we utilize time-domain thermoreflectance, in both concentric and beam-offset configurations, and the time-resolved magneto-optic Kerr effect. Our results show that the WF law overpredicts the thermal conductivity by at least ∼10% in all films, thus demonstrating modest deviations in predicted thermal conductivity when applying the WF law to dilute AlCu films. Using infrared variable angle spectroscopic ellipsometry, we demonstrate increased electron scattering rates in the thinnest film (⁠⁠h⁠ ≈ 24 nm), indicating electron-boundary scattering drives the reduction in in-plane thermal conductivity. Furthermore, this is generally an elastic scattering process, which is supported by our thermal conductivity measurements and analysis.

Electrical conductivity↗
DOE OSTI2025

A code-to-code benchmark for magneto-convection in a horizontal duct

Liquid metals and magnetic fields are used in many technical applications such as metallurgy, crystal growth and nuclear fusion reactors. When an electrically conducting fluid moves in a magnetic environment, electric currents and electromagnetic forces are generated that affect velocity and pressure losses in the flow. These magnetohydrodynamic (MHD) interactions have to be investigated to optimize the engineering processes. The characteristics of MHD flows depend on the geometrical configuration, the strength of the applied magnetic field, the electrical properties of fluid and structural materials and the thermal conditions. In the so-called blankets for fusion reactors, where liquid metals are used to breed the plasma fuel component tritium and to extract the generated heat, magneto-convective flows play a crucial role in determining heat and mass transfer. Therefore, the availability of numerical codes to simulate this type of flow is mandatory and their validation is a necessary step to guarantee the reliability of the results. For that reason, a benchmark problem has been defined to simulate liquid metal flows in a horizontal rectangular duct heated from below and exposed to a non-uniform magnetic field. Results obtained by five research groups using different codes are compared.

benchmark↗
DOE OSTI2025

Statistical inference of collision frequencies from x-ray Thomson scattering spectra

Thomson scattering spectra measure the response of plasma particles to incident radiation. In warm dense matter, which is opaque to visible light, x-ray Thomson scattering (XRTS) enables a detailed probe of the electron distribution and has been used as a diagnostic for electron temperature, density, and plasma ionization. In this work, we examine the sensitivities of inelastic XRTS signatures to modeling details, including the dynamic collision frequency and the electronic density of states. Applying verified Monte Carlo inversion methods to dynamic structure factors obtained from time-dependent density functional theory, we assess the utility of XRTS signals as a way to inform the dynamic collision frequency, especially its direct-current limit, which is directly related to the electrical conductivity.

Collision frequency↗
DOE OSTI2025

Modulating the Electronic Transport of 2D Sb2Te3 Nanoplates by Coinage Metal Intercalation

Thermoelectric materials are particularly relevant to the current energy infrastructure and demands of the 21st century, converting waste heat into usable electricity. The solution intercalation of zerovalent copper into Sb2Te3 nanoplates, a well-established thermoelectric material, is reported. The copper intercalant is homogeneously distributed throughout the nanoplates, confirmed by scanning transmission electron microscopy coupled with energy-dispersive X-ray spectroscopy. The copper composition was shown to be 6 at. % by X-ray photoelectron spectroscopy. Copper ordering within the van der Waals gaps of the nanoplates is confirmed by selected area electron diffraction. Fabrication and thermoelectric property measurements of single-crystal Sb2Te3 and Cu-Sb2Te3 nanoplate devices show effective modulation of electrical conductivity and Seebeck coefficient with Cu intercalation. X-ray photoelectron spectroscopic studies in the valence-band region reveal additional electronic states from copper that appear near the Fermi energy, postulated to act as electron acceptors, leading to modulation of the electronic transport properties.

2D nanoplates↗
DOE OSTI2025

Numerical investigation of magneto-inertial fusion targets magnetized by dynamic enforcement of helical current flow

Magnetized Liner Inertial Fusion (MagLIF) targets require premagnetization to reduce thermal conduction losses from the laser-heated fuel to the liner material during implosion. MagLIF targets are typically magnetized by external magnetic field coils which are technologically limited to providing <20 T axial magnetic fields in the fusion fuel. We present a novel target design, AutoMag-D, which employs dynamic enforcement of helical current in the liner, resulting in >20 T axial magnetic field in the fuel region prior to implosion without the need of external magnetic field coils. These self-magnetizing liners are made of helically oriented alternating electrically conductive material and electrically insulating material surrounded by a thin, conductive outer radial layer. As the liner is pulsed with a ∼ 20 MA, ∼ 100 ns rise time drive current from Z, the outer layer of conductive material is shocked and intensely Joule heated, causing it to melt, vaporize, and turn to plasma. This allows the magnetic drive field to diffuse radially inward which dynamically enforces current flow in the helical conduction paths in the liner and produces axial magnetic field in the fuel region prior to implosion of the inner liner surface. AutoMag-D liner designs do not require dielectric breakdown of electrically insulating material (as in traditional auto-magnetizing helical liners) and do not require helical return current geometries (as in dynamic screw pinches). We present results from three-dimensional radiation-magnetohydrodynamic simulations of MagLIF implosions employing AutoMag-D liner designs. Simulated AutoMag-D targets demonstrate improved fuel conditions and thermonuclear yield compared to traditional MagLIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A Machine Learning Framework for Modeling Ensemble Properties of Atomically Disordered Materials

Atomic disorder can strongly influence material properties such as charge transport, optical response, and catalytic activity. However, efficiently modeling these disorder effects remains challenging for first-principles methods due to the cost of sampling large configurational spaces and computing complex physical quantities. Recent advances of machine learning techniques, particularly graph neural networks (GNNs), has enabled the efficient and accurate predictions of complex material properties, offering promising tools for studying disordered systems. In this work, we present a general machine-learning-assisted computational framework that integrates equivariant GNNs with Monte Carlo simulations to compute the thermodynamic and ensemble-averaged functional properties of disordered materials. Using the surface-termination-disordered MXene monolayer Ti 3 C 2 T 2–x as a representative system, we find that electrical conductivity exhibits an emergent peak near the order–disorder phase transition temperature due to the interplay between electron scattering and doping. In contrast, optical conductivity remains largely insensitive to local atomic disorder and reflects the global surface chemical composition. These results highlight the role of atomic disorder in affecting material properties and demonstrate the potential of our approach for statistically modeling disorder effects in a wide range of materials such as high-entropy alloys and spin liquids.

MXene↗
DOE OSTI2024

Tuning Optical and Electrical Properties of Vanadium Oxide with Topochemical Reduction and Substitutional Tin

Vanadium oxides are widely tunable materials, with many thermodynamically stable phases suitable for applications spanning catalysis to neuromorphic computing. The stability of vanadium in a range of oxidation states enables mixed-valence polymorphs of kinetically accessible metastable materials. Low-temperature synthetic routes to, and the properties of, these metastable materials are poorly understood and may unlock new optoelectronic and magnetic functionalities for expanded applications. In this work, we demonstrate topochemical reduction of α-V 2 O 5 to produce metastable vanadium oxide phases with tunable oxygen vacancies (>6%) and simultaneous substitutional tin incorporation (>3.5%). The chemistry is carried out at low temperature (65 °C) with solution-phase SnCl 2 , where Sn 2+ is oxidized to Sn 4+ as V 5+ sites are reduced to V 4+ during oxygen vacancy formation. Despite high oxygen vacancy and tin concentrations, the transformations are topochemical in that the symmetry of the parent crystal remains intact, although the unit cell expands. Band structure calculations show that these vacancies contribute electrons to the lattice, whereas substitutional tin contributes holes, yielding a compensation doping effect and control over the electronic properties. The SnCl 2 redox chemistry is effective on both solution-processed V 2 O 5 nanoparticle inks and mesoporous films cast from untreated inks, enabling versatile routes toward functional films with tunable optical and electronic properties. The electrical conductance rises concomitantly with the SnCl 2 concentration and treatment time, indicating a net increase in density of free electrons in the host lattice. This work provides a valuable demonstration of kinetic tailoring of electronic properties of vanadium–oxygen systems through top-down chemical manipulation from known thermodynamic phases.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Plasma hydrodynamics from mean force kinetic theory

Mean force kinetic theory is used to evaluate the electrical conductivity, thermal conductivity, electrothermal coefficient, thermoelectric coefficient, and shear viscosity of a two-component plasma. The results are compared with molecular dynamics simulations. These simulations are made possible by assuming a repulsive Coulomb force for all interactions. Good agreement is found for all coefficients up to a Coulomb coupling strength of Γ ≈ 20. This is over 100-times larger than the coupling strength at which traditional theories break down. It is concluded that mean force kinetic theory is a promising framework for extending hydrodynamics to dense plasmas.

Electrical conductivity↗
DOE OSTI2025

Soil Moisture Data for TRACER project (Houston, TX)

The purpose of this study was to collect and distribute ground-truth soil water content and meteorological data in the Houston, TX, area, supporting the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility, and the 2022 field campaign for the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). The files herein contain soil water content and meteorological data for three stations that the Bureau of Economic Geology at UT Austin installed in the Houston, TX, area during the period of performance. The data includes soil moisture, volumetric water content, electrical conductivity of soil, soil temperature, rain precipitation, air temperature and other parameters. Data files within this data set contain measurements at both sub-hourly and 1-hour resolution measurements. The sub-hourly meteorological data file names end with “TRACER_SubHourly_met.dat”, and the sub-hourly soil data files end with “TRACER_SubHourly_soil.dat”. For the 1-hour resolution data, the files ending with "_Soil_flagged.dat” contain mean hourly volumetric soil water content and temperature measured at 5, 10, 20 and 50 cm depths. The files ending with “_Meteoro_flagged.dat” contain mean hourly measured precipitation, air temperature and humidity, wind speed and direction, and solar radiation. All data have undergone QA/QC procedures that are described by Caldwell et al. (2019) and Dorigo et al. (2013) for the soil-specific data, and EPA (2008) for the meteorological data.

Air temperature↗
DOE OSTI2025

Machine learning-accelerated path integral molecular dynamics simulations of reactive organic electrolytes

Hydrogen bonded electrolytes that exhibit accelerated proton transport via sequential reactive hops have drawn interest for their promise in clean energy applications. Molecular dynamics simulations of these electrolytes offer the opportunity to uncover microscopic mechanistic details that could be used to design and tune the properties of candidate electrolyte technologies. However, accurately modeling the proton transfer reactions and transport properties that give rise to high charge conductivites in these electrolytes proves computationally challenging because of the need to perform lengthy condensed phase simulations, treating both the electronic and nuclear degrees of freedom quantum mechanically. In this paper, we demonstrate that such a modeling task can be efficiently achieved with the use of density functional theory (DFT)-trained machine learning potentials (MLP) to accelerate path integral molecular dynamics (PIMD) simulations. We highlight the practical utility of this approach by using it to benchmark how closely PIMD simulations employing different DFT exchange–correlation functionals reproduce the composition-dependent densities, diffusion coefficients, and electrical conductivities of mixtures consisting of imidazole and levulinic acid. Even with the speedup afforded by our MLPs, PIMD simulations remain quite expensive. Furthermore, in order to render PIMD more computationally tractable, we introduce and benchmark the accuracy of a ring polymer contraction approach that leverages a computationally efficient short-range MLP to accelerate our PIMD simulations by an additional factor of four.

Chemical bonding↗