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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Nernst power factor and figure of merit in the compensated semimetal ScSb

Recently, topological semimetals have emerged as strong candidates for solid-state thermomagnetic refrigerators due to their enhanced Nernst effect. This enhancement arises from the combined contributions of the Berry-curvature-induced anomalous Nernst coefficient associated with topological bands and the normal Nernst effect resulting from synergistic electron-hole compensation. Generally, these two effects are intertwined in topological semimetals, making it challenging to evaluate them independently. Here, we report the observation of a high Nernst effect in the electron-hole compensated semimetal ScSb with topologically trivial electronic band structures. Remarkably, we find a high maximum Nernst power factor of 𝑃⁢𝐹 𝑁 ∼ 35 × 10 −4 W m −1 K −2 in ScSb. The Nernst thermopower (𝑆 𝑥⁢𝑦 ) exhibits a peak of ∼ 47 µ⁢V/K at 12 K and 14 T, yielding a Nernst figure of merit (𝑧 𝑁 ) of ∼ 28 × 10 −4 K −1 . Notably, despite its trivial electronic band structure, both the 𝑃⁢𝐹 𝑁 and 𝑧 𝑁 values of ScSb are comparable to those observed in topological semimetals with Dirac band dispersions. In conclusion, the origin of the large Nernst signal in ScSb is explained by compensated electron and hole carriers, through Hall resistivity measurements, angle-resolved photoemission spectroscopy, and density functional theory calculations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Influence of Cation Size on the Local Atomic Structure and Electronic Properties of Ta Perovskite Oxynitrides

Partial anion substitution in transition metal oxides provides rich opportunities to control and tune physical and chemical properties, for example, combining the merits of oxides and nitrides. In addition, the possibility of resulting anion sublattice order provides a means to target polar and chiral structures based on a wide array of accessible structural archetypes by design. Here, in this work, we investigate the local structures of a family of perovskite tantalum oxynitrides—ATaO 2 N (A = Ba, Sr, and Ca)—using a combination of experimental and theoretical approaches including neutron total scattering, density functional theory (DFT), and ab initio molecular dynamics (AIMD) simulations. We present the first experimental study of chemical short-range order (CSRO) in CaTaO 2 N, confirming local cis N ordering of the anion sub-lattice. Our systematic exploration of a local structure across the A cation size series (from the larger Ba to the smaller Ca) reveals a perovskite motif increasingly distorted with respect to long-range average structures. DFT and AIMD simulations support the observed trends. Overall, structures with cis ordering of the nitrogen anions in each TaO 4 N 2 octahedron are favored over those with trans ordering. With diminishing A cation size, local cis ordering and Ta off-centering play decreasing roles in overall lattice stability, overshadowed by the stabilizing effects of octahedral tilting. The influence of these factors on local dipole formation and frustrated dipole ordering are discussed.

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

Experimental Structures of Antibody/MHC-I Complexes Reveal Details of Epitopes Overlooked by Computational Prediction

Abstract mAbs to MHC class I (MHC-I) molecules have proved to be crucial reagents for tissue typing and fundamental studies of immune recognition. To augment our understanding of epitopic sites seen by a set of anti–MHC-I mAb, we determined X-ray crystal structures of four complexes of anti–MHC-I Fabs bound to peptide/MHC-I/β2-microglobulin (pMHC-I). An anti–H2-Dd mAb, two anti–MHC-I α3 domain mAbs, and an anti–β2-microglobulin mAb bind pMHC-I at sites consistent with earlier mutational and functional experiments, and the structures explain allelomorph specificity. Comparison of the experimentally determined structures with computationally derived models using AlphaFold Multimer showed that although predictions of the individual pMHC-I heterodimers were quite acceptable, the computational models failed to properly identify the docking sites of the mAb on pMHC-I. The experimental and predicted structures provide insight into strengths and weaknesses of purely computational approaches and suggest areas that merit additional attention.

Immunology↗
DOE OSTI2023

New Zintl Phase Yb 10 MgSb 9 with High Thermoelectric Performance

Abstract Yb 10 MgSb 9 is a new Zintl compound (with a composition closer to Yb 10.5 MgSb 9 ) and a promising thermoelectric material first reported in this work. Undoped Yb 10 MgSb 9 has an ultralow thermal conductivity due to crystallographic complexity and exhibits a relatively high peak p‐type Seebeck coefficient and high electrical resistivity. This is consistent with Zintl counting and density functional theory (DFT) calculations that the composition Yb 10.5 MgSb 9 should be a semiconductor. Na is found experimentally to be an effective p‐type dopant potentially due to the replacement of Na + for Yb 2+ , allowing for a significant decrease in electrical resistivity. With doping, a dramatic improvement of electrical conductivity is observed and the glass‐like thermal conductivity remains low, allowing for a significant enhancement of the thermoelectric figure of merit, zT . Doping increases the zT from 0.23 in undoped Yb 10 MgSb 9 to 1.06 in 7 at% Na‐doped Yb 10 MgSb 9 at 873K. This high thermoelectric performance found through Na‐doping places this material amongst the leading p‐type Zintl thermoelectrics, making it a promising candidate for future studies and high‐temperature thermoelectric applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ultrafast electron diffraction: Visualizing dynamic states of matter

Since the discovery of electron-wave duality, electron scattering instrumentation has developed into a powerful array of techniques for revealing the atomic structure of matter. Beyond detecting local lattice variations in equilibrium structures with the highest possible spatial resolution, recent research efforts have been directed toward the long-sought-after dream of visualizing the dynamic evolution of matter in real time. The atomic behavior at ultrafast timescales carries critical information on phase transition and chemical reaction dynamics, the coupling of electronic and nuclear degrees of freedom in materials and molecules, and the correlation among structure, function, and previously hidden metastable or nonequilibrium states of matter. Ultrafast electron pulses play an essential role in this scientific endeavor, and their generation has been facilitated by rapid technical advances in both ultrafast laser and particle accelerator technologies. Here this review presents a summary of the noteworthy developments in this field in the last few decades. The physics and technology of ultrafast electron beams is presented with an emphasis on the figures of merit most relevant for ultrafast electron diffraction experiments. Recent developments in the generation, manipulation, and characterization of ultrashort electron beams aimed at improving the combined spatiotemporal resolution of these measurements are discussed. The fundamentals of electron scattering from atomic matter and the theoretical frameworks for retrieving dynamic structural information from solid-state and gas-phase samples is described. Essential experimental techniques and several landmark works that have applied these approaches are also highlighted to demonstrate the widening applicability of these methods. Ultrafast electron probes with ever-improving capabilities, combined with other complementary photon-based or spectroscopic approaches, hold tremendous potential for revolutionizing our ability to observe and understand energy and matter at atomic scales.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Electron and hole mobility of rutile GeO 2 from first principles: An ultrawide-bandgap semiconductor for power electronics

Rutile germanium dioxide (r-GeO 2 ) is a recently predicted ultrawide-bandgap semiconductor with potential applications in high-power electronic devices, for which the carrier mobility is an important material parameter that controls the device efficiency. We apply first-principles calculations based on density functional and density functional perturbation theory to investigate carrier-phonon coupling in r-GeO 2 and predict its phonon-limited electron and hole mobilities as a function of temperature and crystallographic orientation. The calculated carrier mobilities at 300 K are μ elec , ⊥ c → = 244 cm 2 V –1 s –1 , μ elec , ∥ c → = 377 cm 2 V –1 s –1 , μ hole , ⊥ c → = 27 cm 2 V –1 s –1 , and μ hole , ∥ c → = 29 cm 2 V –1 s –1 . At room temperature, carrier scattering is dominated by the low-frequency polar-optical phonon modes. The predicted Baliga figure of merit of n -type r-GeO 2 surpasses several incumbent semiconductors such as Si, SiC, GaN, and β -Ga 2 O 3 , demonstrating its superior performance in high-power electronic devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Cosmology with second- and third-order shear statistics for the Dark Energy Survey: Methods and simulated analysis

We present a new pipeline designed for the robust inference of cosmological parameters using both second- and third-order shear statistics. We build a theoretical model for rapid evaluation of three-point correlations using our fastnc code and integrate it into the cosmosis framework. We measure the two-point functions 𝜉 ± and the full configuration-dependent three-point shear correlation functions across all auto- and cross-redshift bins. We compress the three-point functions into the mass aperture statistic ⟨ℳ$^{3}_{ap}$⟩ for a set of 796 simulated shear maps designed to model the Dark Energy Survey Year 3 data. We estimate from it the full covariance matrix and model the effects of intrinsic alignments, shear calibration biases and photometric redshift uncertainties. We apply scale cuts to minimize the contamination from the baryonic signal as modeled through hydrodynamical simulations. We find a significant improvement of 83% on the figure of merit in the Ω m − 𝑆 8 plane when we add the ⟨ℳ$^{3}_{ap}$⟩ data to 𝜉 ± . Here, we present our findings for all relevant cosmological and systematic uncertainty parameters and discuss the complementarity of third-order and second-order statistics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Strong Negative Thermal Expansion in a Low-Cost and Facile Oxide of Cu 2 P 2 O 7

Negative thermal expansion (NTE) behaviors have been observed in various types of compounds. The achievement in the merits of promising low-cost and facile NTE oxides remains challenging. In the present work, a simple and low-cost Cu 2 P 2 O 7 has been found to exhibit the strongest NTE among the oxides (alpha(v) similar to -27.69 X 10 -6 K -1 , 5-375 K). The complex NTE mechanism has been investigated by the combined methods of high-resolution synchrotron X-ray diffraction, neutron powder diffraction, X-ray pair distribution function, extended X-ray absorption fine structure spectroscopy, and density functional theory calculations. Interesting, the direct experimental evidence reveals that the coupling twist and rotation of PO 4 and CuO 5 polyhedra are the inherent factors for the NTE nature of Cu 2 P 2 O 7 , which is triggered by the transverse vibrations of oxygen atoms. The present new NTE material of Cu 2 P 2 O 7 also has been verified for the practical application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Optical and Plasmonic Properties of High-Electron-Density Epitaxial and Oxidative Controlled Titanium Nitride Thin Films

The present paper reports on the fabrication, detailed structural characterizations, and theoretical modeling of titanium nitride (TiN) and its isostructural oxide derivative, titanium oxynitride (TiNO) thin films that have excellent plasmonic properties and that also have the potential to overcome the limitation of noble metal and refractory metals. The TiNO films deposited at 700 °C in high vacuum conditions have the highest reflectance (R = ~ 95%), largest negative dielectric constant (ε 1 = –161), and maximal plasmonic figure of merit (FoM = –ε 1 /ε 2 ) of 1.2, followed by the 600 °C samples deposited in a vacuum (R = ~ 85%, ε 1 = –145, FoM = 0.8) and 700 °C–5 mTorr sample (R = ~ 82%, ε 1 = –8, FoM = 0.3). To corroborate our experimental observations, we calculated the phonon dispersions and Raman active modes of TiNO by using the virtual crystal approximation. From the experimental and theoretical studies, a multilayer optical model has been proposed for the TiN/TiNO epitaxial thin films for obtaining individual complex dielectric functions from which many other optical parameters can be calculated. The advantages of oxide derivatives of TiN are the continuation of similar free electron density as in TiN and the acquisition of additional features such as oxygen-dependent semiconductivity with a tunable bandgap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

ResNet and CycleGAN for pulse shape discrimination of He-4 detector pulses: Recovering pulses conventional algorithms fail to label unanimously

Pulse shape discrimination (PSD) capable detectors, such as He-4, that respond to neutron and gamma-ray 7 interactions have a threshold deposited energy value below which n/γ discrimination vanishes when using 8 conventional PSD algorithms. Recent attempts in applying supervised learning based artificial neural 9 networks for PSD use the pulses in the separated regions to train the networks so they can be used to classify 10 another set of separated pulses. In doing so, pulses previously indistinguishable are not recovered for 11 classification, which would have increased the number of neutron and gamma-ray pulses that could be used 12 for further analysis. Assuming the reason why conventional PSD algorithms have unseparated regions is 13 because the parameter space of the algorithms fail to capture the intrinsic (but subtle) distinguishing 14 behavior of some of the neutron and gamma-ray pulses, a cycle-consistent generative adversarial network 15 (CycleGAN) was trained to amplify those differences and extract well separated neutron and gamma-ray 16 clusters. Results show that, once the network is trained with pulses from separated and unseparated regions, 17 it was able to transform the pulses in the unseparated region to improve the PSD. Subsequent n/γ 18 classification was performed using deep residual network (ResNet) that takes pulses with 512 data points 19 as an input. Two different ResNets were explored – simple ResNet and modified ResNet which takes 20 segmented pulse inputs in the first layer and the corresponding time axis values in the last hidden layer. 21 The later approach enables the network to extract time correlated pulse features to enhance its ability to 22 capture the pulse behaviors relevant for PSD. Although it achieves slightly lower accuracy, 99.41% versus 23 99.89%, based on simply counting the number of correct n/γ labels assigned, compared to the simple 24 ResNet, the modified ResNets architecture was able to decreases the cross-entropy loss function by half, 25 which implies that the correct n/γ labels assigned are less likely to be accidental. PSD parameter 26 distributions based on n/γ classification by ResNet before and after transforming unseparated pulses using 27 CycleGAN show that by enhancing the separation between neutrons and gamma-rays, the transformation 28 helps improve the performance of classifier networks that are trained using labeled dataset. The 29 enhancement of neutron and gamma-ray separation by the CycleGAN increased the PSD figure of merit 30 (FOM) by up to 70% in some regions. Here, the results show that, if a given detector achieves clear separation 31 between neutron and gamma-ray pulses in any energy region, such neural network approaches can help 32 lower the energy threshold for the separation and increasing the number of neutron and gamma-ray pulses 33 that can be used for further analysis.

4He↗
DOE OSTI2025

SAM Linear Fresnel Model, Project B (CRADA Final Report)

Objective performance and economic modeling of solar thermal plants is of keen interest to many EPRI funders. One solar thermal technology that is not currently available to model in any non-vendor, non-proprietary tool is linear Fresnel. This technology has garnered enough interest from EPRI funders to merit investing in a tool to objectively model its performance. Early in 2010, EPRI performed a comparison of modeling solar thermal power plants using the IPSEPRO, CNRS and Solar Advisor (SAM) tools. After completing this effort, EPRI decided to adopt NREL’s Solar Advisor Model as its default modeling tool based in part on user friendliness, flexibility, number of technologies covered, integrated financial model and ease of running sensitivities. Furthermore, it was recognized that NREL continues to invest considerable time and resources into improving capabilities and functionality of the model.

14 SOLAR ENERGY↗
DOE OSTI2021

Accelerated discovery of a large family of quaternary chalcogenides with very low lattice thermal conductivity

The development of efficient thermal energy management devices such as thermoelectrics and barrier coatings often relies on compounds having low lattice thermal conductivity (κ l ). Here, we present the computational discovery of a large family of 628 thermodynamically stable quaternary chalcogenides, AMM'Q 3 (A = alkali/alkaline earth/post-transition metals; M/M' = transition metals, lanthanides; Q = chalcogens) using high-throughput density functional theory (DFT) calculations. We validate the presence of low κ l in these materials by calculating κ l of several predicted stable compounds using the Peierls–Boltzmann transport equation. Our analysis reveals that the low κ l originates from the presence of either a strong lattice anharmonicity that enhances the phonon-scatterings or rattler cations that lead to multiple scattering channels in their crystal structures. Our thermoelectric calculations indicate that some of the predicted semiconductors may possess high energy conversion efficiency with their figure-of-merits exceeding 1 near 600 K. Our predictions suggest experimental research opportunities in the synthesis and characterization of these stable, low κ l compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Data-driven design of novel halide perovskite alloys

The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring combinatorial chemical spaces. Here, in this work, we develop a framework powered by high-throughput computations and machine learning for the design and prediction of mixed cation halide perovskite alloys. In a chemical space of ABX 3 perovskites with a selected set of options for A, B, and X species, pseudo-cubic structures with B-site mixing are simulated using density functional theory (DFT) and several properties are computed, including stability, lattice constant, band gap, vacancy formation energy, refractive index, and optical absorption spectrum, using both semi-local and hybrid functionals. Neural networks (NN) are used to train predictive models for every property using tabulated elemental properties of A, B, and X site species as descriptors. Starting from a DFT dataset of 229 points, we use the trained NN models to predict the structural, energetic, electronic, and optical properties of an extensive dataset of 17955 compounds, and perform high-throughput screening in terms of stability, band gap, and defect tolerance, to obtain 392 promising compounds that are ranked as potential absorbers according to their photovoltaic figure of merit. Compositional trends in the screened set of attractive mixed cation halide perovskites are revealed and additional computations are performed on selected compounds. The data-driven design framework developed here is promising for designing novel mixed compositions and can be extended to a wider perovskite chemical space in terms of A, B, and X species, different kinds of mixing at the A, B, or X sites, non-cubic phases, and other properties of interest.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Semiconducting Small Molecules as Active Materials for p-Type Accumulation Mode Organic Electrochemical Transistors

A series of semiconducting small molecules with bithiophene or bis-3,4-ethylenedioxythiophene cores are designed and synthesized. The molecules display stable reversible oxidation in solution and can be reversibly oxidized in the solid state with aqueous electrolyte when functionalized with polar triethylene glycol side chains. Evidence of promising ion injection properties observed with cyclic voltammetry is complemented by strong electrochromism probed by spectroelectrochemistry. Blending these molecules with high molecular weight polyethylene oxide (PEO) is found to improve both ion injection and thin film stability. The molecules and their corresponding PEO blends are investigated as active layers in organic electrochemical transistors (OECTs). For the most promising molecule:polymer blend (P4E4:PEO), p-type accumulation mode OECTs with µA drain currents, μS peak transconductances, and a µC* figure-of-merit value of 0.81 F V -1 cm -1 s -1 are obtained.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics

Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed deep learning (PiDL) addresses these challenges by incorporating physical principles into the model. Most PiDL approaches regularize training by embedding governing equations into the loss function, yet this depends heavily on extensive hyperparameter tuning to weigh each loss term. To this end, we propose to leverage physics prior knowledge by “baking” the discretized governing equations into the neural network architecture via the connection between the partial differential equations (PDE) operators and network structures, resulting in a PDE-preserved neural network (PPNN). This method, embedding discretized PDEs through convolutional residual networks in a multi-resolution setting, largely improves the generalizability and long-term prediction accuracy, outperforming conventional black-box models. The effectiveness and merit of the proposed methods have been demonstrated across various spatiotemporal dynamical systems governed by spatiotemporal PDEs, including reaction-diffusion, Burgers’, and Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Electronic properties of corundum-like Ir 2 O 3 and Ir 2 O 3 -Ga 2 O 3 alloys

In the hexagonal, corundum-like structure, α-Ga 2 O 3 has a bandgap of ~5.1 eV, which, combined with its relatively small electron effective mass, high Baliga's figure of merit, and high breakdown field, makes it a promising candidate for power electronics. Ga 2 O 3 is easy to dope n-type, but impossible to dope p-type, impeding the realization of some electronic device designs. Developing a lattice-matched p-type material that forms a high-quality heterojunction with n-type Ga 2 O 3 would open new opportunities in electronics and perhaps optoelectronic devices. In this work, we studied Ir 2 O 3 as a candidate for that purpose. Using hybrid density functional theory calculations we predict the electronic band structure of α-Ir 2 O 3 and compare that to α-Ga 2 O 3 , and study the stability and electronic properties of α-(Ir x Ga 1–x ) 2 O 3 alloys. We discuss the band offset between the two materials and compare it with recently available experimental data. We find that the Ir d bands that compose the top of the valence band in α-Ir 2 O 3 are much higher in energy than O p bands in α-Ga 2 O 3 , possibly enabling effective p-type doping. Finally, our results provide an insight into using the Ir 2 O 3 or Ir 2 O 3 -Ga 2 O 3 alloys as p-type material lattice-matched to α-Ga 2 O 3 for the realization of p–n heterojunctions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

All-aerosol-jet-printed highly sensitive and selective polyaniline-based ammonia sensors: a route toward low-cost, low-power gas detection

In this work, we report the design and scalable fabrication of a low-cost and low-power polyaniline-based (PANI) ammonia (NH3) gas sensor on polyimide (PI) substrates using additive manufacturing techniques. The silver interdigitated electrode (IDE) arrays and conducting polymer films are printed onto PI using a direct-write technology of aerosol-jet printing. Morphological characteristics are examined by scanning electron microscopy and energy-dispersive X-ray analysis which reveal homogeneously printed PANI film on the IDE platform. The gas sensing performance is evaluated in the analytical early leak detection range of 5–1000 ppm NH3 in air as a function of both thermal (23 °C, 50 °C, 80 °C) and relative humidity (RH = 0%, 30%, 50%) exposures. The sensor exhibits sensitivity down to 5 ppm NH3 with a sub-ppm detection limit and good repeatability. We observe rapid NH3 detection at 0% RH with very extended times for equilibration and recovery. However, at both 30 and 50% RH, the room temperature response and recovery times are reduced to only about 1 min and 5 min, respectively. Experiments also reveal good sensitivity toward the analyte even at higher operating temperatures. Present results merit the practical application of aerosol-jet-printed, low-power sensors for industrial applications where low-level hazardous gas detection is essential.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Characterization of a LaB6 tip as a thermionically enhanced photoemitter

There is a widespread interest in time-resolved electron spectroscopies such as ultrafast electron diffraction, ultrafast electron microscopy, and ultrafast electron energy loss spectroscopy. These techniques require pulsed electron beams with both high current and brightness. LaB6 is commonly used as a thermionic emitter because of its low work function and high electron yield. However, its use as a pulsed photocathode has not been widely explored. Here, we present measurements of the electron yield from a LaB6 filament exposed to 392 nm UV ultrafast laser pulses under a wide range of filament temperatures. We find that sample heating strongly enhances photoelectron yield, an effect known as thermionically enhanced photoemission. However, it also creates potentially undesirable, continuous thermionic background. We conclude that the ideal optimal operating conditions strongly depend on the type of measurement and require defining and quantifying an appropriate figure of merit.

Physics↗