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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Digital force prediction for milling

This paper presents a fully digital, integrated approach for milling force prediction with arbitrary end mill-work material combinations. The approach includes: 1) structured light scanning to identify the end mill’s cutting edge macro-geometry along the tool axis; 2) structured light scanning to measure the cutting edge cross-sectional rake and relief profiles; 3) finite element analysis of orthogonal cutting to determine the force model coefficients that relate the force to chip area using the work material’s constitutive model and tool’s rake and relief profiles; and 4) time domain simulation with inputs that include the measured cutting edge macro-geometry, finite element-based force model, and measured structural dynamics. Milling force predictions are compared to in-process measurements to validate the method.

42 ENGINEERING↗
DOE OSTI2025

Spectral line-shape in collinear laser spectroscopy after atomic charge exchange

Collinear laser spectroscopy experiments on fast, neutral beams have been extensively used for studies on short-lived radioactive nuclei, taking advantage of its high sensitivity. The resulting resonance line-shape is known to show significant distortion, due to the energy exchange during the charge-exchange neutralization process, which can cause large systematic uncertainty in the determined centroid. A model for the line shape was constructed and simulated to be compared to measured Al, Si, and Ni hyperfine spectra. It is shown that the distortion is caused mainly by the transfer of electron into many different energy levels in the projectile atom and subsequent decays, rather than secondary inelastic collisions, which were often assumed in the line shape analysis before. Furthermore, the model can also be applied to other projectile–alkali pairs, providing a reliable line-shape with less fitting parameters than conventional phenomenological models.

Atom↗
DOE OSTI2025

Extending Orbital-Optimized Density Functional Theory to L-Edge XPS and Beyond: Spin–Orbit Coupling via Nonorthogonal Quasi-Degenerate Perturbation Theory

Quantum mechanical calculations of core electron binding energies (CEBEs) are relevant to interpreting X-ray photoelectron spectroscopy (XPS). Orbital-optimized density functional theory (OO-DFT) accurately predicts K-edge CEBEs but is challenged by the presence of significant spin–orbit coupling (SOC) at L- and higher edges involving inner-shell orbitals with nonzero angular momentum. Here, to extend OO-DFT to L-edges and higher, our method utilizes scalar-relativistic, spin-restricted open-shell OO-DFT to construct a minimal, quasi-degenerate basis of core-hole states corresponding to a chosen inner-shell (e.g., ionizing all six possible 2p spin orbitals). Nonorthogonal configuration interaction (NOCI) is then used to obtain the matrix elements of the full Hamiltonian including SOC in this quasi-degenerate model space of determinants. Using a screened 1-electron SOC operator parametrized with the Dirac-Coulomb-Breit (DCB) Hamiltonian results in doublet splitting (DS) values for third row elements that are nearly in quantitative agreement with experiment. The resulting NOCI eigenvalues are shifted by the average of the (scalar) OO-DFT CEBEs to yield CEBEs (split by SOC) corrected for dynamic correlation. Comparing calculations on gas phase molecules with experimental results establishes that NO-QDPT with the SCAN functional (NO-QDPT/SCAN), using the DCB screened 1-electron SOC operator is accurate to about 0.2 eV for L-edge CEBEs of molecules containing third row atoms. However, this NO-QDPT approach becomes less accurate for fourth-row elements starting in the middle of the 3d transition metal series, with errors increasing as atomic number increases.

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

Atomically Dispersed Platinum in Surface and Subsurface Sites on MgO Have Contrasting Catalytic Properties for CO Oxidation

Atomically dispersed metals on metal oxide supports are a rapidly growing class of catalysts. Developing an understanding of where and how the metals are bonded to the supports is challenging because support surfaces are heterogeneous, and most reports lack a detailed consideration of these points. In this work, we report two atomically dispersed CO oxidation catalysts having markedly different metal–support interactions: platinum in the first layer of crystalline MgO powder and platinum in the second layer of this support. Structural models have been determined on the basis of data and computations, including those determined by extended X-ray absorption fine structure and X-ray absorption near edge structure spectroscopies, infrared spectroscopy of adsorbed CO, and scanning transmission electron microscopy. The data demonstrate the transformation of surface to subsurface platinum as the temperature of sample calcination increased. Catalyst performance data demonstrate the lower activity but greater stability of the subsurface platinum than of the surface platinum.

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

Critical Role of Framework Flexibility and Disorder in Driving High Ionic Conductivity in LiNbOCl 4

Understanding Li-ion transport is key for the rational design of superionic solid electrolytes with exceptional ionic conductivities. LiNbOCl 4 is reported to be one of the most highly conducting materials in the recently realized new class of soft oxyhalide solid electrolytes, exhibiting an ionic conductivity of ~11 mS·cm -1 . Here, we apply X-ray/neutron diffraction and pair distribution function analysis - coupled with density functional theory/ab-initio molecular dynamics - to determine a structural model that provides a rationale for the high conductivity that we observe experimentally in this nanocrystalline solid. We show that it arises from unusually high framework flexibility at room temperature. This owes to isolated 1-D [NbOCl 4 ] - anionic chains which exhibit energetically favorable orientational disorder that is - in turn - correlated to multiple, disordered and equi-energetic Li + sites in the lattice. As the Li-ions sample the 3-D energy landscape with a fast predicted diffusion coefficient of 5.1 x 10 -7 cm 2 /s at room temperature (σ i calc = 17.4 mS·cm -1 ), the inorganic polymer chains can reorient or vice versa. The activation energy barrier for Li migration through the frustrated energy landscape is especially reduced by the elastic nature of the NbO 2 Cl 4 octahedra evident from very widely dispersed Cl-Nb-Cl bond angles in AIMD snapshots at 300 K. The phonon spectra are predominantly influenced by Cl vibrations in the low energy range, and there is strong overlap between the framework (Cl, Nb) and Li partial pDOS in the region between 1.2 - 4.0 THz. The framework flexibility is also reflected in a relatively low bulk modulus of 22 GPa. In conclusion, our findings pave the way for investigation of future “flex-ion” inorganic solids and open up a new direction for the design of high conductivity, soft solid electrolytes for all-solid-state batteries.

AIMD↗
DOE OSTI2025

CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Proteins and other biomolecules form dynamic macromolecular machines that are tightly orchestrated to move, bind, and perform chemistry. Cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) can access the intrinsic heterogeneity of these complexes and are therefore key tools for understanding their function. However, 3D reconstruction of the collected imaging data presents a challenging computational problem, especially without any starting information, a setting termed ab initio reconstruction. Here, in this study, we introduce cryoDRGN-AI, a method leveraging an expressive neural representation and combining an exhaustive search strategy with gradient-based optimization to process challenging heterogeneous datasets. Using cryoDRGN-AI, we reveal new conformational states in large datasets, reconstruct previously unresolved motions from unfiltered datasets, and demonstrate ab initio reconstruction of biomolecular complexes from in situ data. With this expressive and scalable model for structure determination, we hope to unlock the full potential of cryo-EM and cryo-ET as a high-throughput tool for structural biology and discovery.

Levy, Axel [Stanford Univ., CA (United States); SL↗
DOE OSTI2022

Thermodynamics of correlated electrons in a magnetic field

The Hofstadter–Hubbard model captures the physics of strongly correlated electrons in an applied magnetic field, which is relevant to many recent experiments on Moiré materials. Few large-scale, numerically exact simulations exists for this model. In this work, we simulate the Hubbard–Hofstadter model using the determinant quantum Monte Carlo (DQMC) algorithm. We report the field and Hubbard interaction strength dependence of charge compressibility, fermion sign, local moment, magnetic structure factor, and specific heat. The gross structure of magnetic Bloch bands and band gaps determined by the non-interacting Hofstadter spectrum is preserved in the presence of U. Incompressible regions of the phase diagram have improved fermion sign. At half filling and intermediate and larger couplings, a strong orbital magnetic field delocalizes electrons and reduces the effect of Hubbard U on thermodynamic properties of the system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

The impact of environmental effects on active galactic nuclei: A decline in the incidence of ionized outflows

Active galactic nuclei (AGNs) have generally been considered to be less frequent in denser environments due to a lower number of galaxy-galaxy interactions and/or the removal of their gas-rich reservoirs by the dense intergalactic medium. However, recent observational and theoretical works suggest that the effect of ram-pressure stripping acting on galaxies in dense environments might reduce the angular momentum of their gas, causing it to infall towards the super massive black hole at their centre, activating the AGN phase. In this work we explore the connection between environment and nuclear activity by evaluating the variation in the incidence of ionized outflows, a common phenomenon associated with nuclear activity, in AGNs across different environments. We select a sample of approximately 3300 optical AGNs from the Sloan Digital Sky Survey Data Release 13, which we match with a group catalogue to identify galaxies in isolation or residing in groups. We further probe their environments through the projected distance to the central galaxy of the group or cluster and the projected surface density to the fifth neighbour (δ 5 ). The presence of ionized outflows is determined through the modelling of the [O III] λ5007 emission line. We find that at lower masses (< 10 10.3 M ⊙ ), the fraction of ionized outflows is significantly lower in satellite AGNs (~7%) than in isolated (~22%) AGNs, probably due to their different AGN luminosity, L [O III] , in this stellar mass range. The fraction of outflows decreases at distances closer to the central galaxy of the group or cluster for all satellite AGNs; however, only the lower-mass ones (10 9 - 10 10.3 M ⊙ ) display a significant decline with δ 5 . Although this study does not include AGNs in the densest regions of galaxy clusters, our findings suggest that AGNs in dense environments accrete less gas than those in the field, potentially due to the removal of the gas reservoirs via stripping or starvation, leading to a negative connection between environment and AGN activity. Based on our results, we propose that the observed change in the incidence of outflows when moving towards denser regions of groups and clusters could contribute to the higher gas metallicities of cluster galaxies compared to field galaxies, especially at lower masses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Recombination rate analysis in long minority carrier lifetime mid-wave infrared InGaAs/InAsSb superlattices

Gallium is incorporated into the strain-balanced In(Ga)As/InAsSb superlattice system to achieve the same mid-wave infrared cutoff tunability as conventional Ga-free InAs/InAsSb type-II superlattices, but with an additional degree of design freedom to enable optimization of absorption and transport properties. Time-resolved photoluminescence measurements of InGaAs/InAsSb superlattice characterization- and doped device structures are reported from 77 to 300 K and compared to InAs/InAsSb. The low-injection photoluminescence decay yields the minority carrier lifetime, which is analyzed with a recombination rate model, enabling the determination of the temperature-dependent Shockley–Read–Hall, radiative, and Auger recombination lifetimes and extraction of defect energy levels and capture cross section defect concentration products. The Shockley–Read–Hall-limited lifetime of undoped InGaAs/InAsSb is marginally reduced from 2.3 to 1.4 μs due to the inclusion of Ga; however, given that Ga improves the vertical hole mobility by a factor of >10×, a diffusion-limited InGaAs/InAsSb superlattice nBn could expect a lower bound of 2.5× improvement in diffusion length with significant impact on photodetector quantum efficiency and radiation hardness. At temperatures below 120 K, the doped device structures are Shockley–Read–Hall limited at 0.5 μs, which shows promise for detector applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Surrogate models to optimize plasma-assisted atomic layer deposition in high aspect ratio features

In this work, we explore surrogate models to optimize plasma enhanced atomic layer deposition (PEALD) in high aspect ratio features. In plasma-based processes such as PEALD and atomic layer etching (ALE), surface recombination can dominate the reactivity of plasma species with the surface, which can lead to unfeasibly long exposure times to achieve full conformality inside nanostructures like high aspect ratio vias. Using a synthetic dataset based on simulations of PEALD, we train artificial neural networks to predict saturation times based on cross section thickness data obtained for partially coated conditions. The results obtained show that just two experiments in undersaturated conditions contain enough information to predict saturation times within 10% of the ground truth. A surrogate model trained to determine whether surface recombination dominates the plasma–surface interactions in a PEALD process achieves 99% accuracy. This demonstrates that machine learning can provide a new pathway to accelerate the optimization of PEALD processes in areas such as microelectronics. Our approach can be easily extended to ALE and more complex structures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Se diffusion in CdTe thin films for photovoltaics

Manipulating CdSeTe bandgrading to enhance photocurrent and carrier lifetime is an essential part of high-performance CdTe photovoltaics (PVs). Here, we examine Se diffusion kinetics in single-crystal and polycrystalline CdTe during deposition, thermal annealing, and CdCl 2 treatments. Se distributions are determined by dynamic secondary-ion-mass spectroscopy and Auger electron spectroscopy depth profiling and coupled with electron backscatter diffraction images of the crystalline structure. Effective bulk and grain boundary diffusion coefficients are determined by analytical models and discussed in the context of processing and film morphology. Se is found to diffuse in CdTe at much higher rates during CdCl 2 treatments than with thermal processing alone. GB diffusion also occurs at a significantly faster rate than bulk diffusion. As a result of these two effects, the near interface bulk and GB Se diffusion during CdCl 2 treatments dominates the bandgrading profiles in CdTe PVs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Evidence of Two-Source King Plot Nonlinearity in Spectroscopic Search for New Boson

Optical precision spectroscopy of isotope shifts can be used to test for new forces beyond the standard model, and to determine basic properties of atomic nuclei. We measure isotope shifts on the highly forbidden 2 S 1/2 → 2 F 7/2 octupole transition of trapped 168,170, 172, 174, 176 Yb ions. When combined with previous measurements in Yb + and very recent measurements in Yb, the data reveal a King plot nonlinearity of up to 240σ. Furthermore, the trends exhibited by experimental data are explained by nuclear density functional theory calculations with the Fayans functional. We also find, with 4.3σ confidence, that there is a second distinct source of nonlinearity, and discuss its possible origin.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Machine Learning (ML) Classifier to Assist Metadata Creation

The Atmospheric Radiation Measurement (ARM) Data Center is responsible for the timely collection, archival, and curation of science data products. These products are freely available through an online data repository. Metadata creation is paramount for scientific users to find and access over seven petabytes of atmospheric science data. The hierarchical metadata structure allows users to search for information at both broad and narrow levels. This project aims to leverage 30 years’ worth of manually created metadata to enable machine predictions of broad-term classifications from narrow-term descriptions. These classification predictions would assist metadata coordinators with their term selections. This paper discusses the cleaning and preprocessing of the training data, the pipeline developed to determine the best model for this task, and the creation of an API metadata classifier for ARM measurement metadata. Our results show that the Linear Support Vector Classification (LinearSVC) algorithm, along with the Term Frequency – Inverse Document Frequency (TF-IDF) vectorizer, is well-suited for our multi-class classification task. Lengthier input training data led to better results, and artificial balancing was unnecessary for this particular use case. This predictive classifier enhances efficiency in metadata creation, as well as supports greater consistency and accuracy in metadata tagging.

Collier, Hannah [ORNL] (ORCID:0000000341284292)↗
DOE OSTI2025

Economic Storage Size Optimization for Electric Vehicle Extreme-Fast Charging Stations

En-route charging infrastructure for electric vehicles is critical to support transportation needs. These charging stations are likely to have high loads and especially sharp peak loads given fast charging capabilities needed to meet transportation schedules. In order to reduce both strain on distribution grid infrastructure and charging station operational costs, many stations are likely to employ behind the meter storage. This paper demonstrates a behind the meter storage sizing optimization that employs an open-source agent-based vehicle behavior model (BEAM) to determine the best sizing across many scenarios. This optimization and analysis is novel in that it examines how storage size impacts not only charging station cost and peak load, but also vehicle queue times. The optimization is also applied across a wide analysis region with sufficient diversity and numbers to provide novel statistical analysis of optimal sizes.

Aka, Julius↗
DOE OSTI2020

Lithium pollution of a white dwarf records the accretion of an extrasolar planetesimal

Tidal disruption and subsequent accretion of planetesimals by white dwarfs can reveal the elemental abundances of rocky bodies in exoplanetary systems. Those abundances provide information on the composition of the nebula from which the systems formed, which is analogous to how meteorite abundances inform our understanding of the early Solar System. We report the detection of lithium, sodium, potassium, and calcium in the atmosphere of the white dwarf Gaia DR2 4353607450860305024, which we ascribe to the accretion of a planetesimal. Using model atmospheres, we determine abundance ratios of these elements, and, with the exception of lithium, they are consistent with meteoritic values in the Solar System. We compare the measured lithium abundance with measurements in old stars and with expectations from Big Bang nucleosynthesis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Scalar and tensor resonances in $J/\psi $ radiative decays

We perform a systematic analysis of the J/ψ → γπ 0 π 0 and → γ$K$$^{0}_{S}$$K$$^{0}_{S}$ partial waves measured by BESIII. We use a large set of amplitude parametrizations to reduce the model bias. We determine the physical properties of seven scalar and tensor resonances in the 1–2.5GeV mass range. These include the well known f 0 (1500) and f 0 (1710), that are considered to be the primary glueball candidates. The hierarchy of resonance couplings determined from this analysis favors the latter as the one with the largest glueball component.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

PVwindow (Photovoltaic Window Simulator) [SWR-22-01]

PVwindow simulates photovoltaic window properties by allowing the user build stacks of thin film materials that compose the window layers. The only needed inputs are the complex refractive indices and thicknesses of the materials. The software will simulate the optical transmission, front reflection, and back reflection of the stack using the transfer matrix method. Properties specific to PV window optics such as visible transmittance and color are also calculated. The optics code extracts the number of absorbed photons in the PV absorber layer and solves the single diode equation to yield theoretical photovoltaic metrics such as power conversion efficiency, fill factor, open circuit voltage, and short circuit current of the PV window when illuminated at an arbitrary angle or from either side of the stack. The software tool ultimately allows researchers to design photovoltaic windows and simulate their properties. The software also exports files that can be read into LBL Window software or into the EnergyPlus and Open Studio building energy modeling software to determine larger scale energy impacts of PV window integration.

Wheeler, Lance↗