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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Imaging Anisotropic Waveguide Exciton Polaritons in Tin Sulfide

In recent years, novel materials supporting in-plane anisotropic polaritons have attracted a great deal of research interest due to their capability of shaping nanoscale field distributions and controlling nanophotonic energy flows. Here we report a nano-optical imaging study of waveguide exciton polaritons (EPs) in tin sulfide (SnS) in the near-infrared (near-IR) region using scattering-type scanning near-field optical microscopy (s-SNOM). With s-SNOM, we mapped in real space the propagative EPs in SnS, which show sensitive dependence on the excitation energy and sample thickness. Moreover, we found that both the polariton wavelength and propagation length are anisotropic in the sample plane. In particular, in a narrow spectral range from 1.32 to 1.44 eV, the EPs demonstrate quasi-one-dimensional propagation, which is rarely seen in natural polaritonic materials. Here, a further analysis indicates that the observed polariton anisotropy originates from the different optical band gaps and exciton binding energies along the two principal crystal axes of SnS.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Towards isolated attosecond electron bunches using ultrashort-pulse laser-solid interactions

We investigate MeV-level attosecond electron bunches from ultrashort-pulse laser-solid interactions through similarities between experimental and simulated electron energy spectra. We show measurements of the bunch duration and temporal structure from particle-in-cell simulations. The experimental observation of such bunches favors specular reflection direction when focusing the laser pulse onto a subwavelength boundary of thick overdense plasmas at grazing incidence. Particle-in-cell simulation further reveals that the attosecond duration is a result of ultra-thin (~tenth of a micron) gaps of zero electromagnetic energy density in the modulated reflected radiation, while the bunching (locally peaked electron concentration) comes from the highly-directional electron angular distribution acquired by the electrons in a grazing incidence setup. To isolate a single electron bunch, we perform simulations using 1-cycle laser pulses and analyze the effect of carrier-envelop phase with particle tracking. The duration of the electron bunch can be further decreased by increasing the laser intensity and the focal spot size, while its direction can be changed by tuning the preplasma density gradient.

High-harmonic generation↗
DOE OSTI2025

Controlled Synthesis of SnO 2 Nanocrystals with Tunable Band Gaps

Tin(IV) oxide nanocrystals (SnO 2 NCs) have significant potential in various applications, with their performance closely related to their band gap. The band gap is influenced by the size and shape of the NCs, which can be precisely controlled by adjusting reaction conditions. In this study, we present deliberately designed synthesis protocols to produce high-quality SnO 2 NCs with tunable band gaps using different methods. Key factors affecting the synthesis include control of the oxidizing agent, reaction temperature, solvent selection, and reaction time optimization. The resulting NCs were characterized by using TEM, XRD, XPS, and optical spectroscopy. Notably, SnO 2 NCs synthesized by controlling the oxidizing agent (air injection) in a hot organic solution were smaller in size and exhibited abundant oxygen vacancies. In contrast, extending the reaction time or using ethanol as a solvent in hydrothermal systems facilitated larger spherical or rod-like SnO 2 NCs with fewer oxygen vacancies. Further analysis of the band gap and valence band maximum energy revealed that the abundant vacancies in SnO 2 NCs synthesized with the air-controlled hot organic solution method resulted in a narrower band gap and an upshifted valence band. These synthetic strategies illustrate the potential for deliberately designing SnO 2 NCs with optimized electronic structures for various applications.

band gap↗
DOE OSTI2021

Cosmic antihelium-3 nuclei sensitivity of the GAPS experiment

The General Antiparticle Spectrometer (GAPS) is an Antarctic balloon experiment designed for low-energy (0.1-0.3 GeV/n) cosmic antinuclei as signatures of dark matter annihilation or decay. GAPS is optimized to detect low-energy antideuterons, as well as to provide unprecedented sensitivity to low-energy antiprotons and antihelium nuclei. The novel GAPS antiparticle detection technique, based on the formation, decay, and annihilation of exotic atoms, provides greater identification power for these low-energy antinuclei than previous magnetic spectrometer experiments. This work reports the sensitivity of GAPS to detect antihelium-3 nuclei, based on full instrument simulation, event reconstruction, and realistic atmospheric influence simulations. The report of antihelium nuclei candidate events by AMS-02 has generated considerable interest in antihelium nuclei as probes of dark matter and other beyond the Standard Model theories. GAPS is in a unique position to detect or set upper limits on the cosmic antihelium nuclei flux in an energy range that is essentially free of astrophysical background. In three 35-day long-duration balloon flights, GAPS will be sensitive to an antihelium flux on the level of $1.3^{+4.5}_{-1.2} $ ∙ 10 -6 m -2 sr -1 s -1 (GeV/n) -1 (95% confidence level) in the energy range of 0.11-0.3 GeV/n, opening a new window on rare cosmic physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

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

Quaternary MgSiN 2 -GaN alloy semiconductors for deep UV applications

Ultrawide direct band gap semiconductors hold great promise for deep ultraviolet optoelectronic applications. Here we evaluate the potential of MgSiN 2 -GaN alloys for this purpose. Although MgSiN 2 itself has an indirect gap ~0.4 eV below its direct gap of ~6.5 eV, its different sign lattice mismatch from GaN in two different basal plane directions could avoid the tensile strain which limits Al x Ga 1–x N on GaN for high x. Two octet-rule-preserving structures (with space groups Pmn2 1 and P1n1) of a 50% alloy of MgSiN 2 and GaN are investigated and are both found to have gaps larger than 4.75 eV using quasiparticle self-consistent GW calculations. Both are nearly direct gap in the sense that the indirect gap is less than 0.1 eV lower than the direct gap. Furthermore, their mixing energies are positive yet small, with values of 8 (31) meV/atom for Pmn2 1 (P1n1), indicating only a small driving force toward phase separation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Global properties of nuclei at finite-temperature within the covariant energy density functional theory

In stellar environments nuclei appear at finite temperatures, becoming extremely hot in core-collapse supernovae and neutron-star mergers. However, due to theoretical and computational complexity, most model calculations of nuclear properties are performed at zero temperature, while those existing at finite temperatures are limited only to selected regions of the nuclide chart. In this study we perform the global calculation of nuclear properties for even-even 8 ≤ Z ≤ 104 nuclei at temperatures in range 0 ≤ T ≤ 2 MeV. Calculations are based on the finite-temperature relativistic Hartree-Bogoliubov model supplemented by the Bonche-Levit-Vautherin vapor subtraction procedure. We find that near the neutron-drip line the continuum states have significant contribution already at moderate temperature T ≈ 1 MeV, thus emphasizing the necessity of the vapor subtraction procedure. Results include neutron emission lifetimes, quadrupole deformations, neutron-skin thickness, proton and neutron pairing gaps, entropy and excitation energy. Up to the temperature T ≈ 1 MeV, the nuclear landscape is influenced only moderately by the finite-temperature effects, mainly by reducing the pairing correlations. Here, as the temperature increases further, the effects on nuclear structures become pronounced, reducing both the deformations and the shell effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Yu-Shiba-Rusinov States in a Superconductor with Topological Z 2 Bands

A Yu-Shiba-Rusinov (YSR) state is a localized in-gap state induced by a magnetic impurity in a superconductor. Recent experiments used an STM tip to manipulate the exchange coupling between an Fe adatom and the FeTe 0.55 Se 0.45 superconductor possessing a Z 2 nontrivial band structure with topological surface states. As the tip moves close to the single Fe adatom, the energy of the in-gap state modulates and exhibits a zero-energy crossing followed by an unusual return to zero energy, which cannot be understood by coupling the magnetic impurity to the superconducting topological surface Dirac cone. Here, we numerically and analytically study the YSR states in superconductors with nontrivial Z 2 bands and show the emergence of the two zero-energy crossings as a function of the exchange coupling between the magnetic impurity and the bulk states. We analyze the role of the topological surface states and compare in-gap states to systems with trivial Z 2 bands. The spin polarization of the YSR states is further studied for future experimental measurement.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Monte Carlo Explicitly Correlated Second-Order Many-Body Green’s Function Calculations of Semiconductor Band Gaps

A systematically converging series of ab initio, post-density-functional, size-consistent, electron-correlated approximations is desired for predictive computing of felectronic band structures of insulating, semiconducting, and metallic solids. A series that meets all of these desiderata (except the applicability to metals) is ab initio many-body Green's function theory based on Gaussian-type-orbital (GTO) basis sets. Here, its leading-order approximation, the second-order Green's function (GF2) method in the diagonal and frequency-independent approximations with the aug-cc-pVDZ basis set, is applied to the fundamental band gaps of three semiconductors (diamond, silicon, and silicon carbide in the zincblende structure) using cluster models. Corrections are made to the basis-set-incompleteness errors by the explicit-correlation (F12) ansatz (GF2-F12) for the valence band edges. The crystals are modeled as surface-passivated clusters of increasing sizes, whose wave functions are expanded by up to 2709 GTO basis functions. Immense computational costs of these calculations are overcome by the highly scalable stochastic algorithm of the Monte Carlo GF2-F12 method, whose operation cost per state increases only as a cubic power of system size, which has a tiny memory footprint and easily achieves near-perfect parallel efficiency on thousands of CPUs or on hundreds of GPUs. The correlated, F12-corrected highest-occupied and lowest-unoccupied molecular-orbital energy (HOMO-LUMO) gap is 5.78 ± 0.07 eV for C 87 H 76 as compared with the experimental value of the fundamental (indirect) band gap of bulk diamond at 5.48 eV. The correlated, F12-corrected HOMO-LUMO gaps for Si 75 H 76 and Si 32 C 43 H 76 are 2.56 ± 0.15 eV and 3.50 ± 0.12 eV, respectively, which are expected to decrease further with increasing cluster sizes. As a result, the experimental fundamental (indirect) band gaps of bulk silicon and silicon carbide are 1.17 eV and 2.42 eV, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Surface Amorphization of Vanadium Dioxide (B) for K-ion Battery

Given the merits of low cost, fast ionic transport in electrolyte, and high operating voltage, potassium ion batteries (PIBs) are promising alternatives to lithium-ion batteries. However, developing suitable electrode materials that can reversibly accommodate large potassium ions is a great challenge. In this paper, guided by density functional theory (DFT) calculations, it is demonstrated that the strategy of interfacial engineering via surface amorphization of VO 2 (B) nanorods (SA-VO 2 ), which results in the formation of a crystalline core/amorphous shell heterostructure, enables superior K + storage performance in terms of large capacity, outstanding rate capability, and long cycle stability working as an anode for PIBs. DFT calculations reveal that the created crystalline/amorphous heterointerface in SA-VO 2 can substantially lower the surface energy, narrow the band gap, and reduce the K + diffusion barrier of VO 2 (B). These conditions enable enhanced K + storage capacity and rapid K + /electron transfer, which result in large capacity and outstanding rate capability. Using in situ X-ray diffraction and in situ transmission electron microscopy complemented by ex situ microscopic and spectroscopic techniques, it is unveiled that the superior cycling stability originates from the excellent phase reversibility with negligible strain response and robust mechanical behavior of SA-VO 2 upon (de)potassiation.

25 ENERGY STORAGE↗
DOE OSTI2025

Scaling of energy delivered through an electrostatic discharge to a small series load

We study the energy delivered through a small-resistance series “victim” load during electrostatic discharge events in air. For gap lengths over 1 mm, the fraction of the stored energy delivered is mostly gap-length independent, with a slight decrease at larger gaps due to electrode geometry. The energy to the victim scales linearly with circuit capacitance and victim load resistance but is not strongly dependent on circuit inductance. This scaling leads to a simple approach to predicting the maximum energy that will be delivered to a series resistance for the case where the victim load resistance is lower than the spark resistance.

42 ENGINEERING↗
DOE OSTI2026

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗
DOE OSTI2023

Suppression of quasiparticle poisoning in transmon qubits by gap engineering

The performance of various superconducting devices operating at ultra-low temperatures is impaired by the presence of non-equilibrium quasiparticles. Inelastic quasiparticle (QP) tunneling across Josephson junctions in superconducting qubits results in decoherence and spurious excitations and, notably, can trigger correlated errors that severely impede quantum error correction. In this work, we use "gap engineering" to suppress the tunneling of low-energy quasiparticles in Al-based transmon qubits, a leading building block for superconducting quantum processors. By implementing potential barriers for QP, we strongly suppress QP tunneling across the junction and preserve charge parity for over $10^3$ seconds. The suppression of QP tunneling also results in a reduction in the qubit energy relaxation rates. The demonstrated approach to gap engineering can be easily implemented in all Al-based circuits with Josephson junctions.

Kamenov, Plamen↗
DOE OSTI2021

Sustained Oxygen Spectral Gaps and Their Dynamic Evolution in the Inner Magnetosphere

Van Allen Probes observations of ion spectra often show a sustained gap within a very narrow energy range throughout the full orbit. To understand their formation mechanism, we statistically investigate the characteristics of the narrow gaps for oxygen ions and find that they are most frequently observed near the noon sector with a peak occurrence rate of over 30%. The magnetic moment (μ) of the oxygen ions in the gap shows a strong dependence on magnetic local time (MLT), with higher and lower μ values in the morning and afternoon sectors, respectively. Moreover, we find through superposed epoch analysis that the gap formation also depends on geomagnetic conditions. Those gaps formed at lower magnetic moments (μ < 3,000 keV/G) are associated with stable convection electric fields, which enable magnetospheric ions to follow a steady drift pattern that facilitates the gap formation by corotational drift resonance. On the other hand, gaps with higher μ values are statistically preceded by a gradual increase of geomagnetic activity. Here, we suggest that ions within the gap were originally located inside the Alfven layer following closed drift paths, before they were transitioned into open drift paths as the convection electric field was enhanced. The sunward drift of these ions, with very low fluxes, forms a drainage void in the dayside magnetosphere manifested as the sustained gap in the oxygen spectrum. This scenario is supported by particle-tracing simulations, which reproduce most of the observed characteristics and therefore provide new insights into inner magnetospheric dynamics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Density-Matrix Based Extended Lagrangian Born–Oppenheimer Molecular Dynamics

Extended Lagrangian Born–Oppenheimer molecular dynamics [ Phys. Rev. Lett. 2008, 100, 123004] is presented for Hartree–Fock theory, where the extended electronic degrees of freedom are represented by a density matrix, including fractional occupation numbers at elevated electronic temperatures. In contrast to regular direct Born–Oppenheimer molecular dynamics simulations, no iterative self-consistent field optimization is required prior to the force evaluations. To sample regions of the potential energy landscape where the gap is small or vanishing, which leads to particular convergence problems in regular direct Born–Oppenheimer molecular dynamics simulations, an adaptive integration scheme for the extended electronic degrees of freedom is presented. The integration scheme is based on a tunable, low-rank approximation of a fourth-order kernel, K, that determines the metric tensor, T ≡ K T K, used in the extended harmonic oscillator of the Lagrangian that generates the dynamics of the electronic degrees of freedom. Here, the formulation and algorithms provide a general guide to implement extended Lagrangian Born–Oppenheimer molecular dynamics for quantum chemistry, density functional theory, and semiempirical methods using a density matrix formalism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Layer Edge States Stabilized by Internal Electric Fields in Two-Dimensional Hybrid Perovskites

Two-dimensional (2D) organic-inorganic hybrid perovskites have been intensively explored in recent years due to their tunable band gaps and exciton binding energies and increased stability with respect to three-dimensional (3D) hybrid perovskites. Experimental observations suggest the existence of localized edge states in 2D hybrid perovskites which facilitate extremely efficient electron-hole dissociation and long carrier lifetimes, while multiple origins for their formation have been proposed. Using first-principles calculations, we demonstrate that layer edge states are stabilized by internal electric fields created by polarized molecular alignment of organic cations in 2D hybrid perovskites when they are two layers or thicker. Overall, our study gives a simple physical explanation of the edge state formation, and facilitating the design and manipulation of layer edge states for optoelectronic applications.

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

Resonant Multiple-Phonon Absorption Causes Efficient Anti-Stokes Photoluminescence in CsPbBr 3 Nanocrystals

Lead halide perovskite nanocrystals, such as CsPbBr 3 , exhibit efficient photoluminescence (PL) up-conversion, also referred to as anti-Stokes photoluminescence (ASPL). This is a phenomenon where irradiating nanocrystals up to 100 meV below gap results in higher energy band edge emission. Most surprising is that ASPL efficiencies approach unity and involve single-photon interactions with multiple phonons. This is unexpected given the statistically disfavored nature of multiple-phonon absorption. Here, in this study, we report and rationalize near-unity anti-Stokes photoluminescence efficiencies in CsPbBr 3 nanocrystals and attribute them to resonant multiple-phonon absorption by polarons. The theory explains paradoxically large efficiencies for intrinsically disfavored, multiple-phonon-assisted ASPL in nanocrystals. Moreover, the developed microscopic mechanism has immediate and important implications for applications of ASPL toward condensed phase optical refrigeration.

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

Density of states prediction for materials discovery via contrastive learning from probabilistic embeddings

Abstract Machine learning for materials discovery has largely focused on predicting an individual scalar rather than multiple related properties, where spectral properties are an important example. Fundamental spectral properties include the phonon density of states (phDOS) and the electronic density of states (eDOS), which individually or collectively are the origins of a breadth of materials observables and functions. Building upon the success of graph attention networks for encoding crystalline materials, we introduce a probabilistic embedding generator specifically tailored to the prediction of spectral properties. Coupled with supervised contrastive learning, our materials-to-spectrum (Mat2Spec) model outperforms state-of-the-art methods for predicting ab initio phDOS and eDOS for crystalline materials. We demonstrate Mat2Spec’s ability to identify eDOS gaps below the Fermi energy, validating predictions with ab initio calculations and thereby discovering candidate thermoelectrics and transparent conductors. Mat2Spec is an exemplar framework for predicting spectral properties of materials via strategically incorporated machine learning techniques.

97 MATHEMATICS AND COMPUTING↗