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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Photodissociation Dynamics of Astrophysically Relevant Propyl Derivatives (C 3 H 7 X; X = CN, OH, HCO) at 157 nm Exploiting an Ultracompact Velocity Map Imaging Spectrometer: The (Iso)Propyl Channel

The photodissociation dynamics of astrophysically relevant propyl derivatives (C 3 H 7 X; X = CN, OH, HCO) at 157 nm exploiting an ultracompact velocity map imaging (UVMIS) setup has been reported. The successful operation of UVMIS allowed the exploration of the 157 nm photo dissociation of six (iso)propyl systems - n/i-propyl cyanide (C 3 H 7 CN), n/i-propyl alcohol (C 3 H 7 OH), and (iso)butanal (C 3 H 7 CHO) – to explore the C 3 H 7 loss channel. The distinct center-of-mass translational energy distributions for the i-C 3 H 7 X (X= CN, OH, HCO) could be explained through preferential excitation of the low frequency C-H bending modes of the formyl moiety compared to the higher frequency stretchings of the cyano and hydroxy moieties. Although the ionization energy of the n-C 3 H 7 radical exceeds the energy of a 157 nm photon, C 3 H 7 + was observed in the n-C 3 H 7 X (X= CN, OH, HCO) systems as a result of photoionization of vibrationally "hot" n-C 3 H 7 fragments, photoionization of i-C 3 H 7 after a hydrogen shift in vibrationally "hot" n-C 3 H 7 radicals, and/or two-photon ionization. Our experiments reveal that at least the isopropyl radical (i-C 3 H 7 ) and possibly the normal propyl radical (n-C 3 H 7 ) should be present in the interstellar medium and hence searched for by radio telescopes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Mapping gas around massive galaxies: cross-correlation of DES Y3 galaxies and Compton- y maps from SPT and Planck

ABSTRACT We cross-correlate positions of galaxies measured in data from the first three years of the Dark Energy Survey with Compton-y maps generated using data from the South Pole Telescope (SPT) and the Planck mission. We model this cross-correlation measurement together with the galaxy autocorrelation to constrain the distribution of gas in the Universe. We measure the hydrostatic mass bias or, equivalently, the mean halo bias-weighted electron pressure 〈bhPe 〉, using large-scale information. We find 〈bhPe 〉 to be $[0.16^{+0.03}_{-0.04},0.28^{+0.04}_{-0.05},0.45^{+0.06}_{-0.10},0.54^{+0.08}_{-0.07},0.61^{+0.08}_{-0.06},0.63^{+0.07}_{-0.08}]$ meV cm−3 at redshifts z ∼ [0.30, 0.46, 0.62, 0.77, 0.89, 0.97]. These values are consistent with previous work where measurements exist in the redshift range. We also constrain the mean gas profile using small-scale information, enabled by the high-resolution of the SPT data. We compare our measurements to different parametrized profiles based on the cosmo-OWLS hydrodynamical simulations. We find that our data are consistent with the simulation that assumes an AGN heating temperature of 108.5 K but are incompatible with the model that assumes an AGN heating temperature of 108.0 K. These comparisons indicate that the data prefer a higher value of electron pressure than the simulations within r500c of the galaxies’ haloes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Hydropower Market Report Story Map

This story map complements the fourth complete edition of the U.S. Hydropower Market Report (2024 update) and builds on the 2024 update. This update focuses on data and trends in 2024 and contextualizes this information compared to evolving high-level trends over the past 10–20 years. It contains information on U.S. hydropower (and pumped storage hydropower) development pipeline, relicenses, license surrenders, performance metrics, and supply chain.

Schmidt, Erik [ORNL] (ORCID:0000000244541330)↗
DOE OSTI2025

Energy innovation in the US buildings sector: Setting the stage and mapping the future

Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry.

Langevin, Jared↗
DOE OSTI2020

Mapping the Temperature-dependent and network site-specific onset of spectral diffusion at the surface of a water cluster cage

We explore the kinetic processes that sustain equilibrium in a microscopic, finite system. This is accomplished by monitoring the spontaneous, time-dependent frequency evolution (the frequency autocorrelation) of a single OH oscillator, embedded in a water cluster held in a temperature-controlled ion trap. The measurements are carried out by applying two-color, IR-IR photodissociation mass spectrometry to the D3O+?(HDO)(D2O)19 isotopologue of the “magic number” protonated water cluster, H+?(H2O)21. The OH group can occupy any one of the five spectroscopically distinct sites in the distorted pentagonal dodecahedron cage structure. The OH frequency is observed to evolve over tens of milliseconds in the temperature range (90-120 K). Starting at 100 K, large “jumps” are observed between two OH frequencies separated by ~300 cm-1 indicating migration of the OH group from the bound OH site at 3350 cm-1 to the free position at 3686 cm-1. Increasing the temperature to 110 K leads to partial interconversion among many sites. All sites are observed to interconvert at 120 K such that the distribution of the unique OH group among them adopts the form one would expect for a canonical ensemble. The spectral dynamics displayed by the clusters thus offer an unprecedented view into the molecular-level processes that drive spectral diffusion in an extended network of water molecules.

Yang, Nan↗
DOE OSTI2023

Grain Boundary Plane Measurement Using Transmission Electron Microscopy Automated Crystallographic Orientation Mapping for Atom Probe Tomography Specimens

Abstract Grain boundaries are critical in determining the properties of materials, including mechanical stability, conductivity, and corrosion resistance. The specific properties of materials depend not only on the misorientation of the crystals, the three most commonly characterized parameters, but also on the angle of the grain boundary plane between the two crystals, the final two parameters in the five-parameter macroscopic description of the grain boundary. The method presented here allows for the direct measurement of all five parameters of the grain boundary in a transmission electron microscopy specimen of various morphologies. This is especially applicable to atom probe specimens, where only a single-tilt axis is generally available, allowing the crystallographic description to be matched to the detailed chemical data available in the atom probe tomography. This method provides a platform for efficient grain boundary analysis in unique samples, saving operator time and allowing for ease of acquisition and interpretation in comparison with traditional electron diffraction methods.

Materials Science↗
DOE OSTI2024

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. Validation on simulations

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulationbased analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogs of the Dark Energy Survey (DES). Here, we implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $νw$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST, and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 percent, 15 percent, and 90 percent for S 8 , Ω m , and the figure-of-merit FoM S8;Ωm , respectively. We further find that non-Gaussian statistics improve constraints on w and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogs for each survey. In a companion paper we present an application to DES Year 3 data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Mapping Current Collection in Cross Section: The Case of Copper-Doped CdTe Solar Cells

For decades, copper has been used to improve the performance of cadmium telluride thin film solar cells. However, it has also been shown to be the main cause of metastability in CdTe. Recently a low activation energy has been reported for the thermal diffusion of Cu in CdTe explaining the ease of motion that it has under moderate temperatures. The community consensus is that copper segregates to the absorber grain boundaries, where it's either beneficial or detrimental to device performance depending on its concentration. Using nanoscale X-ray micrsocopy and a two-dimensional drift-diffusion model we present a preliminary correlation between local copper distribution and electrical performance of a single-junction CdTe/CdS solar cell.

CdTe↗
DOE OSTI2024

Unveiling and Mapping Polymorphs in Fluorite Y2TiO5 Using 4D-STEM and Unsupervised Machine Learning

Y2TiO5 belongs to the Ln2TiO5 (Ln = lanthanide or Y) family of ceramic materials and exhibits a range of desirable material properties such as radiation tolerance, frustrated magnetism, and large dielectric constant. However, understanding the complex crystal structure of Y2TiO5 remains elusive, given that Y2TiO5 can adopt multiple polymorphs such as cubic, orthorhombic, and hexagonal phases within the lattice. In this work, we report a detailed structural analysis of Y2TiO5 using four-dimensional scanning transmission electron microscopy coupled with unsupervised machine learning. The pyrochlore nanodomains, characterized by the ordered arrangement of yttrium cations on the A site of their A2BO5 structure, are present within the matrix of a predominantly fluorite-structured Y2TiO5 along with a third polymorph, the hexagonal phase. The pyrochlore phase is found to form 2 nm boundary regions around hexagonal phase stacking faults, highlighting the potential influence of the hexagonal phase on the occurrence and distribution of the pyrochlore phase. Lastly, we identify a unique pyrochlore phase with asymmetric arrangement of cation ordering along a single planar direction. Our findings provide invaluable insights into the possible mechanisms stabilizing pyrochlore nanodomains within the fluorite lattice of Y2TiO5.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Clifford Circuit-Based Heuristic Optimization of Fermion-To-Qubit Mappings

Simulation of interacting Fermionic Hamiltonians is one of the most promising applications of quantum computers. However, the feasibility of analyzing Fermionic systems with a quantum computer hinges on the efficiency of Fermion-to-qubit mappings that encode nonlocal Fermionic degrees of freedom in local qubit degrees of freedom. While recent studies have highlighted the importance of designing Fermion-to-qubit mappings that are tailored to specific problem Hamiltonians, the methods proposed so far either are restricted to a narrow class of mappings or they use computationally expensive and unscalable brute-force search algorithms. Here, in this work, we address this challenge by designing a heuristic numerical optimization framework for Fermion-to-qubit mappings. To this end, we first translate the Fermion-to-qubit mapping problem to a Clifford circuit optimization problem and then use simulated annealing to optimize the average Pauli weight of the problem Hamiltonian. For all Fermionic Hamiltonians we have considered, the numerically optimized mappings outperform their conventional counterparts, including ternary-tree-based mappings that are known to be optimal for single creation and annihilation operators. We find that our optimized mappings yield between 15% and 40% improvements on the average Pauli weight when the simulation Hamiltonian has an intermediate level of complexity. Most remarkably, the optimized mappings improve the average Pauli weight for 6 × 6 nearest-neighbor hopping and Hubbard models by more than 40% and 20%, respectively. Surprisingly, we also find specific interaction Hamiltonians for which the optimized mapping outperforms any ternary-tree-based mapping. Our results establish heuristic numerical optimization as an effective method for obtaining mappings tailored for specific Fermionic Hamiltonian.

Hamiltonians↗
DOE OSTI2020

The Atacama Cosmology Telescope: arcminute-resolution maps of 18 000 square degrees of the microwave sky from ACT 2008–2018 data combined with Planck

This paper presents a maximum-likelihood algorithm for combining sky maps with disparate sky coverage, angular resolution and spatially varying anisotropic noise into a single map of the sky. We use this to merge hundreds of individual maps covering the 2008–2018 ACT observing seasons, resulting in by far the deepest ACT maps released so far. We also combine the maps with the full Planck maps, resulting in maps that have the best features of both Planck and ACT: Planck’s nearly white noise on intermediate and large angular scales and ACT’s high-resolution and sensitivity on small angular scales. The maps cover over 18 000 square degrees, nearly half the full sky, at 100, 150 and 220 GHz. Furthermore, they reveal 4 000 optically-confirmed clusters through the Sunyaev Zel’dovich effect (SZ) and 18 500 point source candidates at > 5σ, the largest single collection of SZ clusters and millimeter wave sources to date. The multi-frequency maps provide millimeter images of nearby galaxies and individual Milky Way nebulae, and even clear detections of several nearby stars. Other anticipated uses of these maps include, for example, thermal SZ and kinematic SZ cluster stacking, CMB cluster lensing and galactic dust science. The method itself has negligible bias. However, due to the preliminary nature of some of the component data sets, we caution that these maps should not be used for precision cosmological analysis. The maps are part of ACT DR5, and will be made available on LAMBDA no later than three months after the journal publication of this article, along with an interactive sky atlas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

CryoTEN: efficiently enhancing cryo-EM density maps using transformers

Abstract Motivation Cryogenic electron microscopy (cryo-EM) is a core experimental technique used to determine the structure of macromolecules such as proteins. However, the effectiveness of cryo-EM is often hindered by the noise and missing density values in cryo-EM density maps caused by experimental conditions such as low contrast and conformational heterogeneity. Although various global and local map-sharpening techniques are widely employed to improve cryo-EM density maps, it is still challenging to efficiently improve their quality for building better protein structures from them. Results In this study, we introduce CryoTEN—a 3D UNETR++ style transformer to improve cryo-EM maps effectively. CryoTEN is trained using a diverse set of 1295 cryo-EM maps as inputs and their corresponding simulated maps generated from known protein structures as targets. An independent test set containing 150 maps is used to evaluate CryoTEN, and the results demonstrate that it can robustly enhance the quality of cryo-EM density maps. In addition, automatic de novo protein structure modeling shows that protein structures built from the density maps processed by CryoTEN have substantially better quality than those built from the original maps. Compared to the existing state-of-the-art deep learning methods for enhancing cryo-EM density maps, CryoTEN ranks second in improving the quality of density maps, while running >10 times faster and requiring much less GPU memory than them. Availability and implementation The source code and data are freely available at https://github.com/jianlin-cheng/cryoten.

Biochemistry & Molecular Biology↗