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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Dramatic Rebrightening of the Type-changing Stripped-envelope Supernova SN 2023aew

Abstract Multipeaked supernovae with precursors, dramatic light-curve rebrightenings, and spectral transformation are rare, but are being discovered in increasing numbers by modern night-sky transient surveys like the Zwicky Transient Facility. Here, we present the observations and analysis of SN 2023aew, which showed a dramatic increase in brightness following an initial luminous (−17.4 mag) and long (∼100 days) unusual first peak (possibly precursor). SN 2023aew was classified as a Type IIb supernova during the first peak but changed its type to resemble a stripped-envelope supernova (SESN) after the marked rebrightening. We present comparisons of SN 2023aew’s spectral evolution with SESN subtypes and argue that it is similar to SNe Ibc during its main peak. P-Cygni Balmer lines are present during the first peak, but vanish during the second peak’s photospheric phase, before H α resurfaces again during the nebular phase. The nebular lines ([O i ], [Ca ii ], Mg i ], H α ) exhibit a double-peaked structure that hints toward a clumpy or nonspherical ejecta. We analyze the second peak in the light curve of SN 2023aew and find it to be broader than that of normal SESNe as well as requiring a very high 56 Ni mass to power the peak luminosity. We discuss the possible origins of SN 2023aew including an eruption scenario where a part of the envelope is ejected during the first peak and also powers the second peak of the light curve through interaction of the SN with the circumstellar medium.

Sharma, Yashvi (ORCID:0000000345311745)↗
DOE OSTI2022

Surface magnetic anisotropy-mediated spin Hall magnetoresistance and spin Seebeck effects in a YIG/Pt heterostructure

The role of magnon-phonon coupling in the low-temperature behavior of the spin Seebeck effect (SSE) in YIG/Pt has been puzzling for more than a decade. Here, to elucidate the origin of the anomalous peak around 80 K, we investigate the temperature evolution of SSE, spin Hall magnetoresistance (SMR), and magnetic anisotropy in the same YIG/Pt heterostructure. We find that these effects, along with magnetic damping, show the peaks at the same temperature (~80 K). This simultaneous occurrence, where no heat is applied in the case of SMR, rules out the phonon-magnon drag related origin of SSE in the YIG/Pt system. We further show that the intrinsic surface anisotropy behavior in YIG is responsible for controlling the SSE, SMR, and magnetic damping in the YIG/Pt structure. Our findings not only help to understand these effects fundamentally but also provide an effective way for improving them by manipulating the surface magnetic anisotropy for spin caloritronic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

How Bulk Sensitive is Hard X-ray Photoelectron Spectroscopy: Accounting for the Cathode–Electrolyte Interface when Addressing Oxygen Redox

Sensitivity to the `bulk' oxygen core orbital makes hard X-ray photoelectron spectroscopy (HAXPES) an appealing technique for studying oxygen redox candidates. Various studies have reported an additional O 1s peak (530-531 eV) at high voltages, which has been considered a direct signature of the bulk oxygen redox process. Here, we find the emergence of a 530.4 eV O 1s HAXPES peak for three model cathodes, Li 2 MnO 3 , Li-rich NMC, and NMC 442, that shows no clear link to oxygen redox. Instead, the 530.4 eV peak for these three systems is attributed to transition metal reduction and electrolyte decomposition in the near-surface region. Claims of oxygen redox relying on photoelectron spectroscopy must explicitly account for the surface sensitivity of this technique and the extent of the cathode degradation layer.

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

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2024

Dark energy survey year 3 results: miscentring calibration and X-ray-richness scaling relations in redMaPPer clusters

ABSTRACT We use Dark Energy Survey Year 3 (DES Y3) clusters with archival XMM–Newton and Chandra X-ray data to assess the centring performance of the redMaPPer cluster finder and to measure key richness observable scaling relations. We find that 10–20 per cent of redMaPPer clusters are miscentred, both when comparing to the X-ray peak position and to the visually identified central cluster galaxy. We find no significant difference in miscentring in bins of low versus high richness or redshift. The dominant reasons for miscentring include masked or missing data and the presence of other bright galaxies in the cluster. For half of the miscentred clusters, the correct central was one of the possible centrals identified by redMaPPer, while for ∼40 per cent of miscentred clusters, the correct central is not a redMaPPer member mostly due to masking. Additionally, we fit scaling relations of X-ray temperature and luminosity with richness. We find a TX–λ scatter of $0.21\pm 0.01$. While the scatter in TX–λ is consistent in redshift bins, we find modestly different slopes, with high-redshift clusters displaying a somewhat shallower relation. Splitting based on richness, we find a marginally larger scatter for our lowest richness bin, 20 < λ < 40. We note that the robustness of the scaling relations at lower richnesses is limited by the unknown selection function, but at λ > 75, we detect nearly all of the clusters falling within existing X-ray pointings. The X-ray properties of detected, serendipitous clusters are generally consistent with those of targeted clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Gravitational wave and CMB probes of axion kination

Rotations of an axion field in field space provide a natural origin for an era of kination domination, where the energy density is dominated by the kinetic term of the axion field, preceded by an early era of matter domination. Remarkably, no entropy is produced at the end of matter domination and hence these eras of matter and kination domination may occur even after Big Bang Nucleosynthesis. We derive constraints on these eras from both the cosmic microwave background and Big Bang Nucleosynthesis. We investigate how this cosmological scenario affects the spectrum of possible primordial gravitational waves and find that the spectrum features a triangular peak. We discuss how future observations of gravitational waves can probe the viable parameter space, including regions that produce axion dark matter by the kinetic misalignment mechanism or the baryon asymmetry by axiogenesis. For QCD axion dark matter produced by the kinetic misalignment mechanism, a modification to the inflationary gravitational wave spectrum occurs above 0.01 Hz and, for high values of the energy scale of inflation, the prospects for discovery are good. We briefly comment on implications for structure formation of the universe.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Precision Loading and Delivery of Molecular Cargo by Size-Controlled Coacervation of Gold Nanoparticles Functionalized with Elastin-like Peptides

Thermoresponsive elastin-like peptides (ELPs) have been extensively investigated in biotechnology and medicine, but little attention has been paid to the process by which coacervation causes ELP-decorated particles to aggregate. Here, using gold nanoparticles (AuNPs) functionalized with a cysteine-terminated 96-repeat of the VPGVG sequence (V96-Cys), we show that the size of the clusters that reversibly form above the ELP transition temperature can be finely controlled in the 250 to 930 nm range by specifying the concentration of free V96-Cys in solution and using AuNPs of different sizes. We further find that the localized surface plasmon resonance peak of the embedded AuNPs progressively red-shifts with cluster size, likely due to an increase in particle–particle contacts. We exploit this fine control over size to homogeneously load precise amounts of the dye Nile Red and the antibiotic Tetracycline into clusters of different hydrodynamic diameters and deliver cargos near-quantitatively by deconstructing the aggregates below the ELP transition temperature. Beyond establishing a key role for free ELPs in the agglomeration of ELP-functionalized particles, our results provide a path for the thermally controlled delivery of precise quantities of molecular cargo. This capability might prove useful in combination photothermal therapies and theranostic applications, and to trigger spatially and temporally uniform responses from biological, electronic, or optical systems.

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

Molecular Origin of Nanoscale Anion Ordering of LiTFSI Electrolytes Revealed through SAXS/WAXS and Molecular Dynamics Simulations

Recent developments in “water-in-salt” electrolytes have precipitated a renewed effort to study imide-based electrolytes. While previous small-/wide-angle X-ray scattering (SAXS/WAXS) studies have attributed the emergence of a low-Q peak in the SAXS profile of aqueous LiTFSI electrolytes to nanometer-scale anion clustering, a molecular-level understanding of the root of these clusters remains unclear. Here, in this study, we combined molecular dynamics simulations and SAXS/WAXS to study the solvation structures of LiTFSI in acetonitrile, methanol, and water. We concluded that hydrogen bonding in water and MeOH stabilizes anion clusters, while nonpolar methyl groups on methanol and acetonitrile interrupt the nanoscale ordering of TFSI anions. This causes LiTFSI in water and MeOH electrolytes to exhibit two low-Q SAXS profile peaks while LiTFSI in acetonitrile exhibits only a single peak below Q = 1 Å –1 . These findings shed light on the underlying molecular origins of nanoscale anion clusters, which may help in the design of the next generation of electrolyte chemistries.

Trojanowski, Lucas [Univ. of Michigan, Ann Arbor, ↗
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

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Size-dependent errors in real-time electron density propagation

Real-time (RT) electron density propagation with time-dependent density functional theory (TDDFT) or Hartree–Fock (TDHF) is one of the most popular methods to model the charge transfer in molecules and materials. However, both RT-TDHF and RT-TDDFT within the adiabatic approximation are known to produce inaccurate evolution of the electron density away from the ground state in model systems, leading to large errors in charge transfer and erroneous shifting of peaks in absorption spectra. Given the poor performance of these methods with small model systems and the widespread use of the methods with larger molecular and material systems, here we bridge the gap in our understanding of these methods and examine the size-dependence of errors in RT density propagation. We analyze the performance of RT density propagation for systems of increasing size during the application of a continuous resonant field to induce Rabi-like oscillations, during charge-transfer dynamics, and for peak shifting in simulated absorption spectra. We find that the errors in the electron dynamics are indeed size dependent for these phenomena, with the largest system producing the results most aligned with those expected from linear response theory. The results suggest that although the RT-TDHF and RT-TDDFT methods may produce severe errors for model systems, the errors in charge transfer and resonantly driven electron dynamics may be much less significant for more realistic, large-scale molecules and materials.

Chemistry↗
DOE OSTI2023

Ubiquitous coexisting electron-mode couplings in high-temperature cuprate superconductors

In conventional superconductors, electron-phonon coupling plays a dominant role in generating superconductivity. In high-temperature cuprate superconductors, the existence of electron coupling with phonons and other boson modes and its role in producing high-temperature superconductivity remain unclear. The evidence of electron-boson coupling mainly comes from angle-resolved photoemission (ARPES) observations of ~70-meV nodal dispersion kink and ~40-meV antinodal kink. However, the reported results are sporadic and the nature of the involved bosons is still under debate. Here we report findings of ubiquitous two coexisting electron-mode couplings in cuprate superconductors. By taking ultrahigh-resolution laser-based ARPES measurements, we found that the electrons are coupled simultaneously with two sharp modes at ~70meV and ~40meV in different superconductors with different dopings, over the entire momentum space and at different temperatures above and below the superconducting transition temperature. These observations favor phonons as the origin of the modes coupled with electrons and the observed electron-mode couplings are unusual because the associated energy scales do not exhibit an obvious energy shift across the superconducting transition. We further find that the well-known “peak-dip-hump” structure, which has long been considered a hallmark of superconductivity, is also omnipresent and consists of “peak-double dip-double hump” finer structures that originate from electron coupling with two sharp modes. These results provide a unified picture for the ~70-meV and ~40-meV energy scales and their evolutions with momentum, doping and temperature. In conclusion, they provide key information to understand the origin of these energy scales and their role in generating anomalous normal state and high-temperature superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Plasmonic gold-cellulose nanofiber aerogels

Assembly of plasmonic nanomaterials into a low refractive index medium, such as an aerogel, holds a great promise for optical metamaterials, optical sensors, and photothermal energy converters. However, conventional plasmonic aerogels are opaque and optically isotropic composites, impeding them from being used as low-loss or polarization-dependent optical materials. Here we demonstrate a plasmonic-cellulose nanofiber composite aerogel that comprises of well-dispersed gold nanorods within a cellulose nanofiber network. The cellulose aerogel host is highly transparent owing to the small scattering cross-section of the nanofibers and forms a nematic liquid crystalline medium with strong optical birefringence. We find that the longitudinal surface plasmon resonance peak of gold nanorods shows a dramatic shift when probed for the cellulose aerogel compared with the wet gels. Simulations reveal the shift of surface plasmon resonance peak with gel drying can be attributed to the change of the effective refractive index of the gels. This composite material may provide a platform for three- dimensional plasmonic devices ranging from optical sensors to metamaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Astrometric Microlensing by Primordial Black Holes with the Roman Space Telescope

Abstract Primordial black holes (PBHs) could explain some fraction of dark matter and shed light on many areas of early-Universe physics. Despite over half a century of research interest, a PBH population has so far eluded detection. The most competitive constraints on the fraction of dark matter comprised of PBHs ( f DM ) in the (10 −9 –10) M ⊙ mass ranges come from photometric microlensing and bound f DM ≲ 10 −2 –10 −1 . With the advent of the Roman Space Telescope with its submilliarcsecond astrometric capabilities and its planned Galactic Bulge Time Domain Survey (GBTDS), detecting astrometric microlensing signatures will become routine. Compared with photometric microlensing, astrometric microlensing signals are sensitive to different lens masses–distance configurations and contain different information, making it a complimentary lensing probe. At submilliarcsecond astrometric precision, astrometric microlensing signals are typically detectable at larger lens–source separations than photometric signals, suggesting a microlensing detection channel of pure astrometric events. We use a Galactic simulation to predict the number of detectable microlensing events during the GBTDS via this pure astrometric microlensing channel. Assuming an absolute astrometric precision floor for bright stars of 0.1 mas for the GBTDS, we find that the number of detectable events peaks at ≈10 3 f DM for a population of 1 M ⊙ PBHs and tapers to ≈10 f DM and ≈100 f DM at 10 −4 M ⊙ and 10 3 M ⊙ , respectively. Accounting for the distinguishability of PBHs from stellar lenses, we conclude the GBTDS will be sensitive to a PBH population at f DM down to ≈10 −1 –10 −3 for (10 −1 –10 2 ) M ⊙ likely yielding novel PBH constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Nematic transition and nanoscale suppression of superconductivity in Fe(Te,Se)

The interplay of different electronic phases underlies the physics of unconventional superconductors. One of the most intriguing examples is a high-temperature superconductor, FeTe 1 – x Se x . This superconductor undergoes both a topological transition, linked to the electronic band inversion, and an electronic nematic phase transition, associated with rotation symmetry breaking, around the same Se composition where the superconducting transition temperature peaks. In this regime, nematic fluctuations and symmetry-breaking strain could be important, but this is yet to be fully explored. Using spectroscopic-imaging scanning tunnelling microscopy, we study the electronic nematic transition in FeTe 1 – x Se x as a function of composition. Near the critical Se composition, we find electronic nematicity in nanoscale regions. The superconducting coherence peaks are suppressed in areas where static nematic order is the strongest. By analysing atomic displacement in scanning tunnelling microscopy topographs, we find that small anisotropic strain can give rise to these strongly nematic localized regions. Furthermore, our experiments reveal a tendency of FeTe 1 – x Se x , near x ≈ 0.45, to form puddles hosting static nematic order, suggestive of nematic fluctuations pinned by structural inhomogeneity, and demonstrate the effect of anisotropic strain on superconductivity in this regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Solvable theory of a strange metal at the breakdown of a heavy Fermi liquid

In this work, we introduce an effective theory for quantum critical points (QCPs) in heavy-fermion systems, involving a change in carrier density without symmetry breaking. Our theory captures a strongly coupled metallic QCP, leading to robust marginal Fermi-liquid transport phenomenology, and associated linear in temperature (T) "strange metal" resistivity, all within a controlled large-N limit. In the parameter regime of strong damping of emergent bosonic excitations, the QCP also displays a near-universal "Planckian" transport lifetime τ tr ~ℏ/(k B T). This is contrasted with the conventional so-called "slave boson" theory of the Kondo breakdown, where the large-N limit describes a weak coupling fixed point and nontrivial transport behavior may only be obtained through uncontrolled 1/N corrections. We also compute the weak-field Hall coefficient within the effective model as the system is tuned across the transition. We then find that, between the two plateaus reflecting the different carrier densities in the two Fermi-liquid phases, the Hall coefficient can develop a peak in the critical crossover regime, like in recent experimental findings, in the parameter regime of weak boson damping.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Statistical analysis of Al III and C III ] emission lines as virial black hole mass estimators in quasars

We test the usefulness of the intermediate ionisation lines Al IIIλ1860 and C III]λ1909 as reliable virial mass estimators for quasars. We identified a sample of 309 quasars from the Sloan Digital Sky Survey Data Release 16 (SDSS DR16) in the redshift range 1.2 ≤ z ≤ 1.4 that have [O II]λ3728 recorded on the same spectrum as Al IIIλ1860, Si III]λ1892, and C III]λ1909. We set the systemic quasar redshift using careful measurements of [O II]λ3728. We then classified the sources as Population A (Pop. A), extreme Population A (Pop. xA), and Population B (Pop. B), and analysed the 1900 Å blend using multi-component models to look for systematic line shifts of Al IIIλ1860 and C III]λ1909 along the quasar main sequence. We do not find significant shifts of the Al IIIλ1860 line peak in Pop. B or in the vast majority of Pop. A. For Pop. xA, a small median blueshift of -250 km s -1 was observed, motivating a decomposition of the Al III line profile into a virialised component centred at rest frame and a blueshifted component for an outflow emission. For Pop. B objects, we proved the empirical necessity to fit a redshifted very broad component, clearly seen in C III], and analysed the physical implications on a Pop. B composite spectrum using CLOUDY simulations. We find consistent black hole mass estimations using Al III and C III] as virial estimators for the bulk of Pop. A. Al III (and even C III]) is a reliable virial black hole mass estimator for Pop. A and Pop. B objects. The Pop. xA sources deserve special attention due to the significant blueshifted excess observed in the line profile of Al III, although it is not as large as the excess observed in C IVλ1549.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

BEYONDPLANCK XIII. Intensity foreground sampling, degeneracies, and priors

We present the intensity foreground algorithms and model employed within the BEYONDPLANCK analysis framework. The BEYONDPLANCK analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the Planck Low Frequency Instrument (LFI) data analysis. Given the scope of the BEYONDPLANCK analysis, a limited set of data is included in the component separation process, leading to foreground parameter degeneracies. In order to properly constrain the Galactic foreground parameters, we improve upon the previous Commander component separation implementation by adding a suite of algorithmic techniques. These algorithms are designed to improve the stability and computational efficiency for weakly constrained posterior distributions. These are: (1) joint foreground spectral parameter and amplitude sampling, building on ideas from MIRAMARE; (2) component-based monopole determination; (3) joint spectral parameter and monopole sampling; and (4) application of informative spatial priors for component amplitude maps. We find that the only spectral parameter with a significant signal-to-noise ratio using the current BEYONDPLANCK data set is the peak frequency of the anomalous microwave emission component, for which we find $ν$ p = 25.3 ± 0.5 GHz; all others must be constrained through external priors. Future works will be aimed at integrating many more data sets into this analysis, both map and time-ordered based, thereby gradually eliminating the currently observed degeneracies in a controlled manner with respect to both instrumental systematic effects and astrophysical degeneracies. When this happens, the simple LFI-oriented data model employed in the current work will need to be generalized to account for both a richer astrophysical model and additional instrumental effects. This work will be organized within the Open Science-based COSMOGLOBE community effort.

79 ASTRONOMY AND ASTROPHYSICS↗