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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Coupling Shared E-scooters and Public Transit: A Spatial and Temporal Analysis

The integration of shared e-scooters with public transit is a promising solution for urban mobility's first/last-mile challenge. This study explores spatiotemporal factors influencing this integration, using 35-day e-scooter trip data from Chicago. Employing a random-effect negative binomial approach, we modeled the frequency of e-scooter trips to access/egress to/from bus stops and train stations. Results indicate that weather conditions, design features like intersection density, and multimodal network density significantly influence usage. The transit system characteristics such as service frequency have a positive effect on the integration of e-scooters and trains while a similar effect for bus and e-scooter integration was not significant. Furthermore, safety-related variables such as accident and crime rates as well as demographic characteristics were also revealed to be significant factors in our study. These findings offer vital insights to urban planners and policymakers for infrastructure, safety enhancements, and interventions to encourage efficient e-scooter-public transit integration.

Chicago↗
DOE OSTI2017

Properties of tree rings in LSST sensors

Images of uniformly illuminated sensors for the Large Synoptic Survey Telescope have circular periodic patterns with an appearance similar to tree rings. Furthermore, these patterns are caused by circularly symmetric variations of the dopant concentration in the monocrystal silicon boule induced by the manufacturing process. Non-uniform charge density results in the parasitic electric field inside the silicon sensor, which may distort shapes of astronomical sources. Here, we analyzed data from fifteen LSST sensors produced by ITL to determine the main parameters of the tree rings: amplitude and period, and also variability across the sensors tested at Brookhaven National Laboratory. Tree ring pattern has a weak dependence on the wavelength. But the ring amplitude gets smaller as wavelength gets longer, since longer wavelengths penetrate deeper into the silicon. Tree ring amplitude gets larger as it gets closer to the outer part of the wafer, from 0.1 to 1.0%, indicating that the resistivity variation is larger for larger radii.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Competition between magnetic order and charge localization in Na 2 IrO 3 thin crystal devices thin crystal devices

Spin orbit assisted Mott insulators such as sodium iridate (Na 2 IrO 3 ) have been an important subject of study in recent years. In these materials, the interplay of electronic correlations, spin-orbit coupling, crystal field effects, and a honeycomb arrangement of ions bring exciting ground states, predicted in the frame of the Kitaev model. The insulating character of Na 2 IrO 3 has hampered its integration to an electronic device, desirable for applications, such as the manipulation of quasiparticles interesting for topological quantum computing. Here we show through electronic transport measurements supported by angle-resolved photoemission spectroscopy (ARPES) experiments, that electronic transport in Na 2 IrO 3 is ruled by variable range hopping and it is strongly dependent on the magnetic ordering transition known for bulk Na 2 IrO 3 , as well as on external electric fields. Furthermore, electronic transport measurements allow us to deduce a value for the localization length and the density of states in our Na 2 IrO 3 thin crystal devices, and offer an alternative approach to study insulating 2D-materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

INTRINSIC ELECTROMAGNETIC VARIABILITY IN CELESTIAL OBJECTS CONTAINING RAPIDLY SPINNING BLACK HOLES

Analytical studies have raised the concern that a mysterious expulsion of magnetic field lines by a rapidly spinning black hole (dubbed the black hole Meissner effect) would shut down the Blandford–Znajek process and quench the jets of active galactic nuclei and microquasars. This effect is, however, not seen observationally or in numerical simulations. Previous attempts at reconciling the predictions with observations have proposed several mechanisms to evade the Meissner effect. In this paper, we identify a new evasion mechanism and discuss its observational significance. Specifically, we show that the breakdown of stationarity is sufficient to remove the expulsion of the magnetic field at all multipole orders, and that the associated temporal variation is likely turbulent because of the existence of efficient mechanisms for sharing energy across different modes. Such an intrinsic (as opposed to being driven externally by, e.g., changes in the accretion rate) variability of the electromagnetic field can produce the recorded linear correlation between microvariability amplitudes and mean fluxes, help create magnetic randomness and seed sheared magnetic loops in jets, and lead to a better theoretical fit to the X-ray microvariability power spectral density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

X-Rays from the Location of the Double-humped Transient ASASSN-15lh

We present the detection of persistent soft X-ray radiation with L{sub x}∼10{sup 41}–10{sup 42} erg s{sup –1} at the location of the extremely luminous, double-humped transient ASASSN-15lh as revealed by Chandra and Swift. We interpret this finding in the context of observations from our multiwavelength campaign, which revealed the presence of weak narrow nebular emission features from the host-galaxy nucleus and clear differences with respect to superluminous supernova optical spectra. Significant UV flux variability on short timescales detected at the time of the rebrightening disfavors the shock interaction scenario as the source of energy powering the long-lived UV emission, while deep radio limits exclude the presence of relativistic jets propagating into a low-density environment. We propose a model where the extreme luminosity and double-peaked temporal structure of ASASSN-15lh is powered by a central source of ionizing radiation that produces a sudden change in the ejecta opacity at later times. As a result, UV radiation can more easily escape, producing the second bump in the light curve. We discuss different interpretations for the intrinsic nature of the ionizing source. We conclude that, if the X-ray source is physically associated with the optical–UV transient, then ASASSN-15lh most likely represents the tidal disruption of a main-sequence star by the most massive spinning black hole detected to date. In this case, ASASSN-15lh and similar events discovered in the future would constitute the most direct probes of very massive, dormant, spinning, supermassive black holes in galaxies. Future monitoring of the X-rays may allow us to distinguish between the supernova hypothesis and the hypothesis of a tidal disruption event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Exploring the Inner Acceleration Region of Solar Wind: A Study Based on Coronagraphic UV and Visible Light Data

This work combined coronagraphic visible light (VL) and UV data to provide with an unprecedented view of the inner corona where the nascent solar wind is accelerated. The UV (H i Lyα) and VL (polarized brightness) images (reconstructed with SOHO/UVCS, LASCO, and Mauna Loa data) have been analyzed with the Doppler dimming technique to provide for the first time daily 2D images of the radial wind speed between 1 and 6 R {sub ⊙} over 1 month of observations. Results show that both polar and equatorial regions are characterized at the base of the corona by plasma outflows at speeds >100 km s{sup −1}. The plasma is then decelerated within ∼1.5 R {sub ⊙} at the poles and ∼2.0 R {sub ⊙} at the equator, where local minima of the expansion speeds are reached, and gently reaccelerated higher up, reaching speeds typical of fast and slow wind components. The mass flux is highly variable with latitude and time at the equator and more uniform and stable over the poles. The polar flow is asymmetric, with speeds above the south pole lower than those above the north pole. A correlation (anticorrelation) between the wind speed and its density is found below (above) ∼1.8 R {sub ⊙}. The 2D distribution of forces responsible for deceleration and reacceleration of solar wind is provided and interpreted in terms of Alfvén waves. These results provide a possible connection between small-scale outflows reported with other instruments at the base of the corona and bulk wind flows measured higher up.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Probing the gamma-ray variability in 3C 279 using broad-band observations

In this study, we present the results of a broad-band radio-to-GeV observing campaign organized to get a better understanding of the radiation processes responsible for the γ-ray flares observed in 3C 279. The total intensity and polarization observations of the source were carried out between 2013 December 28 and 2014 January 03 using the Fermi-Large Area Telescope, Swift-XRT, Swift-UVOT, and Korean VLBI Network telescopes. A prominent flare observed in the optical/near-UV passbands was found to be correlated with a concurrent γ-ray flare at a confidence level >95 percent, which suggests a co-spatial origin of the two. Moreover, the flaring activity in the two regimes was accompanied by no significant spectral variations. A peak in the X-ray light curve coincides with the peaks of the fractional polarization curves at 43 and 86 GHz radio bands. No prominent variation was noticed for the total intensity and the electric vector position angle observations at radio bands during this period. We noticed a possible hint of steepening of the radio spectrum with an increase in percentage polarization, which suggests that the radio polarization variations could be simply due to a spectral change. In a simple scenario, the correlated optical/γ-ray flares could be caused by the same population of emitting particles. The coincidence of the increase in radio polarization with the X-ray flux supports the picture that X-rays are produced via inverse-Compton scattering of radio photons. Finally, the observed fractional variability for the γ-ray flare ~0.23 does not exceed that in the optical regime, which is inconsistent with what we usually observe for 3C 279; it could be due to different dependencies of the magnetic field and the external radiation field energy density profiles along the jet.

3C 279, gamma-rays↗
DOE OSTI2021

Crack tip microplasticity mediated by microstructure gradients

Abstract Traditional fracture theories infer damage at cracks (local field) by surveying loading conditions away from cracks (far field). This approach has been successful in predicting ductile fracture, but it normally assumes isotropic and homogeneous materials. However, myriads of manufacturing procedures induce heterogeneous microstructural gradients that can affect the accuracy of traditional fracture models. This work presents a microstructure‐sensitive finite element approach to explore the shielding effects of grain size and crystallographic orientation gradients on crack tip microplasticity and blunting. A dislocation density‐based crystal plasticity model conveys texture evolution, grain size effects, and directional hardening by computing the constraint from dislocation structures. The results demonstrate that the microstructure can act as a buffer between the local and far fields that affects the crack tip microplasticity variability. For nominal opening loading, grain size and texture affect the local ductility and induce a non‐negligible multiaxial plastic deformation. Furthermore, driving forces based on measuring displacements away from the crack tip are less affected by the microstructure, which suggests that traditional experimental methods smear out important crack tip variability.

Castelluccio, Gustavo M.↗
DOE OSTI2016

The stellar population structure of the galactic disk

The spatial structure of stellar populations with different chemical abundances in the Milky Way (MW) contains a wealth of information on Galactic evolution over cosmic time. We use data on 14,699 red-clump stars from the APOGEE survey, covering 4 kpc≲R≲15 kpc, to determine the structure of mono-abundance populations (MAPs)—stars in narrow bins in [α/Fe] and [Fe/H]—accounting for the complex effects of the APOGEE selection function and the spatially variable dust obscuration. We determine that all MAPs with enhanced [α/Fe] are centrally concentrated and are well-described as exponentials with a scale length of 2.2±0.2 kpc over the whole radial range of the disk. We discover that the surface-density profiles of low-[α/Fe] MAPs are complex: they do not monotonically decrease outwards, but rather display a peak radius ranging from ≈5 to ≈13 kpc at low [Fe/H]. The extensive radial coverage of the data allows us to measure radial trends in the thickness of each MAP. While high-[α/Fe] MAPs have constant scale heights, low-[α/Fe] MAPs flare. We confirm, now with high-precision abundances, previous results that each MAP contains only a single vertical scale height and that low-[Fe/H], low-[α/Fe] and high-[Fe/H], high-[α/Fe] MAPs have intermediate (h{sub Z}≈300--600 pc) scale heights that smoothly bridge the traditional thin- and thick-disk divide. That the high-[α/Fe], thick disk components do not flare is strong evidence against their thickness being caused by radial migration. The correspondence between the radial structure and chemical-enrichment age of stellar populations is clear confirmation of the inside-out growth of galactic disks. The details of these relations will constrain the variety of physical conditions under which stars form throughout the MW disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Stabilizing laser energy density on a target during pulsed laser deposition of thin films

A process for stabilizing laser energy density on a target surface during pulsed laser deposition of thin films controls the focused laser spot on the target. The process involves imaging an image-aperture positioned in the beamline. This eliminates changes in the beam dimensions of the laser. A continuously variable attenuator located in between the output of the laser and the imaged image-aperture adjusts the energy to a desired level by running the laser in a "constant voltage" mode. The process provides reproducibility and controllability for deposition of electronic thin films by pulsed laser deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Vacuum arcing behavior between transverse magnetic field contacts subjected to variable axial magnetic field

The objective of this work is to reveal the effects of an axial magnetic field (AMF) on the vacuum arc characteristics between transverse magnetic field (TMF) contacts. These vacuum arc characteristics include the vacuum arcing behavior and the arc voltage waveform. In the experiments, an external AMF was applied to a pair of TMF contacts. The external AMF flux density B{sub AMF} can be adjusted from 0 to 110 mT. The arc current in the tests varied over a range from 0 to 20 kA rms at 45 Hz. The contact material was CuCr25 (25% Cr). A high-speed charge-coupled device video camera was used to record the vacuum arc evolution. The experimental results show that the application of the AMF effectively reduces the TMF arc voltage noise component and reduces the formation of liquid metal drops between the contacts. The diffuse arc duration increases linearly with increasing AMF flux density, but it also decreases linearly with increasing arc current under application of the external AMF. The results also indicate that the diffuse arc duration before the current zero is usually more than 1 ms under the condition that the value of the AMF per kiloampere is more than 2.0 mT/kA. Finally, under application of the AMF, the arc column of the TMF contacts may constrict and remain in the center region without transverse rotation. Therefore, the combined TMF–AMF contacts should be designed such that they guarantee that the AMF is not so strong as to oppose transverse rotation of the arc column.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

First Report and Molecular Variability of Belonolaimus longicaudatus Associated with Turfgrass in Maryland

Abstract Turfgrass is a crop used extensively in athletic fields and golf courses in Maryland. A soil sample collected in July 2023 from an athletic field in Baltimore County, Maryland, part of a turfgrass nematode survey, containedBelonolaimus longicaudatus. In the southeastern United States,B. longicaudatusis an economically important pathogen of warm season turfgrass. The density was four individuals/100 cm 3 of soil, and no visual symptoms were observed in the bermudagrass field. Morphological features and morphometrics of males and females were consistent withB. longicaudatusand placed the Maryland population in a subclade that was geographically represented by populations from north and west Florida, Texas, and South Carolina. Sequencing of the internal transcribed spacer region ITS1 and ITS2 and 28S large ribosomal subunit D2-23 expansion region confirmed the species' identity. Phylogenetic trees and parsimony network analysis placed the Maryland isolate in a large grouping ofB. longicaudatuspopulations including those from Alabama, Delaware, Florida, Indiana, Mississippi, South Carolina, and Texas. To our knowledge, this is the first report ofB. longicaudatusin Maryland.

Zoology↗
DOE OSTI2024

NbZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys niobium-zirconium (Nb-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Nb and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name "case-N" where N ranges between 11 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system FILES contained in each subdirectory with name "case-N" where N ranges between 1 and 10, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. {ID}.POSCAR: input file that defines the atomic structure of a system at the beginning of ID execution of geometry optimization with PREC=LOW 4. {ID}.CONTCAR: output file that provides the atomic positions and cell parameters at the end of ID execution of geometry optimization with PREC=LOW in the INCAR file 5. {ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of geometry optimization that has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.{ID}.out: file with diagnostic information about the execution of the ID execution of the geometry optimization with precision variable set to PREC=Low in the INCAR file 7. N{ID}.POSCAR: input file that defines the atomic structure of a system after the geometry optimization run at low precision. This represents the input for the ID execution of the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. N{ID}.CONTCAR: output file that provides the atomic positions and cell parameters after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 9. N{ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.{ID}.out: file with diagnostic information about the ID execution of geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15–50 (1996) (4) Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2019

Experimental Investigation of the Impact of Cathode Grade on Sludge Formation at the Cathode Block-Aluminum Interface of Hall–Héroult Cells

The presence of resistive sludge on the cathode surface in Hall–Héroult cells can increase the aluminum production costs and reduces cell lifetime. Modern cells with graphitized cathode blocks generally operate satisfactorily but some are exhibiting excessive deposit formation, thus lower performances. Little attention has ever been given to the role of the cathode grade and its properties on sludge formation. In this investigation, five graphitized industrial cathode grades with varying properties are tested on a bench scale aluminum electrolysis setup with cathodic current density of 0.9 A/cm{sup 2}, under a nitrogen atmosphere at 1233 K (960 °C) for 8 hours with initial bath composition of 10 pct alumina, cryolite ratio of 2.2, 5 pct CaF{sub 2} and no point feeding. Postmortem characterization includes Rietveld refinement of deposits, optical microscopy and SEM-EDS observations of the carbon-aluminum interface. Sludge located near the center of the cathode surface was generated during the experiments despite the absence of point feeding. The sludge profile was variable among grades and could be related to the horizontal and vertical thermal conductivities of the blocks. This study has pushed further the understanding of the mechanisms of sludge formation and dissolution concerning the cathode grade properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

TaZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys tantalum-zirconium (Ta-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach \cite{PAW}. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Ta and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions. The calculations have been collected on NERSC-Perlmutter and OLCF-Summit using the VASP 6.3.2. The VASP calculations for every atomic structure have been performed in 2 main steps: 1. Starting from an ideal body-centered-cubic (BCC) structure, geometry optimization with low precision has been executed to perform a preliminary optimization of the atomic structure. The output for this calculations is available in the files 0.CONTCAR, 0.OUTCAR, rlx1.out. 2. Using the atomic structure resulting from the preliminary geometry optimization, a second geometry optimization has been performed using normal precision. The output for this calculations is available in the files CONTCAR, OUTCAR, rlx2.out, vaspout.h5, and vasprun.xml. Cases 1-10 have been run without generating the file 'vaspout.h5'. Every chemical composition sampled across the composition range in the dataset has its own directory. The convention used to name the directories for binary alloys is AXBY, where A and B refer to the constituents, whereas X and Y are positive integers that represent the number of atoms for each constituent and their values still sum up to 128. Each atomic structure associated with a specific chemical composition has its own sub-directory within the directory of the corresponding chemical composition. The sub-directories for each atomic structure for each chemical composition are named 'case-*', where * is a positive integer that spans all the values from 1 through 100, extremes included. The files contained in each sub-directory 'case-*' for each atomic structure are as follows: FILES contained in each subdirectory with name "case-N" where N ranges between 11 and 80, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. 0.POSCAR: input file that defines the atomic structure of a system 4. 0.CONTCAR: output file that provides the atomic positions and cell parameters after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 5. 0.OUTCAR: output file that contains detailed information about the progress of a calculation after the first geometry optimization has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.out: file with diagnostic information about the execution of the first geometry optimization with precision variable set to PREC=Low in the INCAR file 7. POSCAR: input file that defines the atomic structure of a system after the first geometry optimization has been run at low precision. This represents the input for the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. CONTCAR: output file that provides the atomic positions and cell parameters after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 9. OUTCAR: output file that contains detailed information about the progress of a calculation after the second geometry optimization has been run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.out: file with diagnostic information about the execution of the second geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system FILES contained in each subdirectory with name "case-N" where N ranges between 1 and 10 and between 81 and 100, extremes included: 1. INCAR: input file that contains various parameters and settings for controlling the behavior of the electronic structure calculations 2. KPOINTS: input file that specifies the Bloch vectors (k points) used to sample the Brillouin zone 3. {ID}.POSCAR: input file that defines the atomic structure of a system at the beginning of ID execution of geometry optimization with PREC=LOW 4. {ID}.CONTCAR: output file that provides the atomic positions and cell parameters at the end of ID execution of geometry optimization with PREC=LOW in the INCAR file 5. {ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of geometry optimization that has been run with the precision variable set to PREC=Low in the INCAR file 6. rlx1.{ID}.out: file with diagnostic information about the execution of the ID execution of the geometry optimization with precision variable set to PREC=Low in the INCAR file 7. N{ID}.POSCAR: input file that defines the atomic structure of a system after the geometry optimization run at low precision. This represents the input for the ID execution of the second geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 8. N{ID}.CONTCAR: output file that provides the atomic positions and cell parameters after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 9. N{ID}.OUTCAR: output file that contains detailed information about the progress of a calculation after the ID execution of the geometry optimization run with the precision variable set to PREC=Normal in the INCAR file 10. rlx2.{ID}.out: file with diagnostic information about the ID execution of geometry optimization with precision variable set to PREC=Normal in the INCAR file 11. vaspout.h5: hierarchical HDF5 file containing the inputs and outputs of a VASP calculation. To analyze the data in this file we recommend using py4vasp. This file is only produced if the VASP version used is compiled with HDF5 support 12. vasprun.xml: contains similar information to OUTCAR, but in an xml format. 13. CHGCAR: contains the charge density data of a system. This data is crucial for analyzing electronic structures, calculating electrostatic potential, and studying the distribution of charge in a crystal or molecular system This research is sponsored by the Artificial Intelligence Initiative as part of the Laboratory Directed Research and Development (LDRD) Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy under contract DE-AC05-00OR22725. This work used resources of the Oak Ridge Leadership Computing Facility, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725, under Directorate Discretionary awards MAT025 (Materials Science) and LRN026 (Machine Learning), and INCITE award MAT201. This work also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, under award ERCAP0025216. REFERENCES (1) Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251 (1994) (3) Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. materials science 6, 15–50 (1996) (4) Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. review B 54, 11169 (1996) (5) Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring interlayer coupling in the twisted bilayer PtTe 2

We have investigated interlayer interactions in the bilayer PtTe 2 system, which influence the electronic energy bands near the Fermi level. Our diffusion Monte Carlo (DMC) calculations for the high-symmetry bilayer stackings (AA, AB, AC) manifest distinct interlayer binding characteristics among the stacking modes by revealing significantly different interlayer separations depending on the stacking, which is critical to understanding the interlayer coupling of the twisted bilayers consisting of various local stacking arrangements. Furthermore, a comparison between the interlayer separations obtained from DMC and density functional theory (DFT) shows that meta-generalized gradient approximation (GGA)-based van der Waals–DFT results agree with DMC for different layer stackings, including twisted bilayers, but only the ground-state AA stacking matches well with GGA-based DFT predictions. This underscores the importance of accurate exchange-correlation potentials even for capturing the stacking-dependent interlayer binding properties. We further show that the variability in DFT-predicted interlayer separations is responsible for the large discrepancy of band structures in the 21 . 79 ∘ twisted bilayer PtTe 2 , affecting its classification as metallic or insulating. These results demonstrate the importance of obtaining a correct description of stacking-dependent interlayer coupling in modeling delicate bilayer systems at finite twists. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2019

Efficient Multiscale Optoelectronic Prediction for Conjugated Polymers

Conjugated polymers represent a high-potential material class due to the tunability of their optoelectronic properties via straightforward processing protocols. However, to in silico tailor these optoelectronic properties, one must compute the conformationally dependent electronic structure over mesoscopic length and time scales. This task represents a challenging multiscale computational problem in which quantum chemistry and atomistic or coarse-grained molecular dynamics must be integrated. Recently, we introduced a methodology, called electronic coarse graining (ECG), that utilizes artificial neural networks to compute ab initio quality electronic structures using only the reduced degrees of freedom of coarse-grained models. Here, we adapt ECG to variable-molecular weight conjugated oligomers by casting the problem in the framework of sequence detection. A machine-learning (ML) architecture employing one-dimensional convolutional neural networks and long short-term memory networks is utilized to compute ground-state orbital energies, charge density distributions, and optical spectra solely from the coarse-grained model's configurational degrees of freedom. Robust molecular weight transferability for ECG is established via a A-ML approach that leverages model electronic Hamiltonians for ground and excited-state property determination. The accuracy and transferability of the ECG methodology opens the door for scalable optoelectronic property prediction in conjugated polymers directly from coarse-grained degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Diagnosing the origin and impact of low-mode asymmetries in ignition experiments at the National Ignition Facility

Inertial confinement fusion ignition requires high inflight shell velocity, good energy coupling between the hotspot and shell, and high areal density at peak compression. Three-dimensional asymmetries caused by imperfections in the drive symmetry or target can grow and damage the coupling and confinement. Recent high-yield experiments have shown that low-mode asymmetries are a key degradation mechanism and contribute to variability. Here we show the experimental signatures and impacts of asymmetry change with increasing implosion yield given the same initial cause. This letter has implications for improving robustness to a key degradation in ignition experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗