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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Anomalous absorption of electromagnetic waves by 2D transition metal carbonitride Ti 3 CNT x (MXene)

Lightweight, ultrathin, and flexible electromagnetic interference (EMI) shielding materials are needed to protect electronic circuits and portable telecommunication devices and to eliminate cross-talk between devices and device components. Here, we show that a two-dimensional (2D) transition metal carbonitride, Ti 3 CNT x MXene, with a moderate electrical conductivity, provides a higher shielding effectiveness compared with more conductive Ti 3 C 2 T x or metal foils of the same thickness. This exceptional shielding performance of Ti 3 CNT x was achieved by thermal annealing and is attributed to an anomalously high absorption of electromagnetic waves in its layered, metamaterial-like structure. These results provide guidance for designing advanced EMI shielding materials but also highlight the need for exploring fundamental mechanisms behind interaction of electromagnetic waves with 2D materials.

Science & Technology - Other Topics↗
DOE OSTI2022

Discrimination of xylene isomers in a stacked coordination polymer

The separation and purification of xylene isomers is an industrially important but challenging process. Developing highly efficient adsorbents is crucial for the implementation of simulated moving bed technology for industrial separation of these isomers. Herein, we report a stacked one-dimensional coordination polymer {[Mn(dhbq)(H 2 O) 2 ], H 2 dhbq = 2,5-dihydroxy-1,4-benzoquinone} that exhibits an ideal molecular recognition and sieving of xylene isomers. Its distinct temperature-adsorbate–dependent adsorption behavior enables full separation of p -, m -, and o -xylene isomers in both vapor and liquid phases. The delicate stimuli-responsive swelling of the structure imparts this porous material with exceptionally high flexibility and stability, well-balanced adsorption capacity, high selectivity, and fast kinetics at conditions mimicking industrial settings. This study may offer an alternative approach for energy-efficient and adsorption-based industrial xylene separation and purification processes.

Science & Technology - Other Topics↗
DOE OSTI2024

Multiplicity dependence of charged-particle intra-jet properties in pp collisions at $\sqrt{s}$ = 13 TeV

The first measurement of the multiplicity dependence of intra-jet properties of leading charged-particle jets in proton–proton (pp) collisions is reported. The mean charged particle multiplicity and jet fragmentation distributions are measured in minimum-bias and high-multiplicity pp collisions at center-of-mass energy $\sqrt{s}$ = 13 TeV using the ALICE detector. Jets are reconstructed from charged particles produced in the midrapidity region (|η| < 0.9) using the sequential recombination anti-k T algorithm with jet resolution parameters R = 0.2, 0.3, and 0.4 for the trans verse momentum (p T ) interval 5–110 GeV/c. The high multiplicity events are selected by the forward V0 scintilla tor detectors. The mean charged-particle multiplicity inside the leading jet cone rises monotonically with increasing jet p T in qualitative agreement with previous measurements at lower energies. The distributions of jet fragmentation function variables z ch and ξ ch are measured for different jet-p T intervals. Jet-p T independent fragmentation of leading jets is observed for wider jets except at high- and low-z ch values. The observed “hump-backed plateau” structure in the ξ ch distribution indicates suppression of low-p T particles. In high-multiplicity events, an enhancement of the fragmen tation probability of low-z ch particles accompanied by a suppression of high-zch particles is observed compared to minimum-bias events. This behavior becomes more promi nent for low-p T jets with larger jet radius. The results are compared with predictions of QCD-inspired event generators, PYTHIA 8 with Monash 2013 tune and EPOS LHC. It is found that PYTHIA 8 qualitatively reproduces the jet modification in high-multiplicity events except at high jet p T . These measurements provide important constraints to models of jet fragmentation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Potential Dependent Mn Oxidation and Its Role in Passivation of Ni 38 Fe 20 Cr 22 Mn 10 Co 10 Multi-Principal Element Alloy Using Multi-Element Resolved Atomic Emission Spectroelectrochemistry

The identity of passivating oxides on multi-principal element alloys is of great interest as their optimization offers the potential for exceptional corrosion resistance in aqueous solutions over a broad range of potential and pH. This study focuses on a non-equiatomic Ni 38 Fe 20 Cr 22 Mn 10 Co 10 solid solution alloy and tracks the fate of each alloying element during linear sweep voltammetry, low and intermediate potential holds in the passive potential domain as well as during open circuit relaxation after anodic polarization in slightly acidified Cl − solution. Ni dissolves at all potentials investigated in this work, Fe and Co are incorporated into oxides or hydroxides in low concentrations whilst Cr and Mn are enriched at passive potentials. At low passivating potentials, Mn(II) dissolves and is incorporated in minor amounts in oxides containing large concentrations of Cr(III). Considerable enrichment in Mn(II)-species occurs relative to Cr(III) in the oxide at 0.1 V vs SCE. Electrochemical impedance spectroscopy suggests the presence of layered oxides with marginal passivation at high Mn(II) levels. The formation of these oxides depends on a combination of thermodynamic and kinetic factors as well as the sequence of passivation.

Han, Junsoo (ORCID:0000000192952954)↗
DOE OSTI2022

XScope

XScope finds inputs that trigger floating-point exceptions, such as NaN (not a number) and infinity, in CUDA functions using Bayesian optimization (BO). XScope assumes that the CUDA functions are a black box, i.e., the source code is not available. It searches the input space using several methods to guide BO into extreme cases. When an input is found to trigger an exception in the target CUDA function, the input is shown to the user.

Laguna Peralta, Ignacio↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part III: Variability

Abstract Daily expected wind power production from operating wind farms across North America are used to evaluate capacity factors (CF) computed using simulation output from the Weather Research and Forecasting (WRF) Model and to condition statistical models linking atmospheric conditions to electricity production. In Parts I and II of this work, we focus on making projections of annual energy production and the occurrence of electrical production drought. Here, we extend evaluation of the CF projections for sites in the Northeast, Midwest, southern Great Plains (SGP), and southwest U.S. coast (SWC) using statewide wind-generated electricity supply to the grid. We then quantify changes in the time scales of CF variability and the seasonality. Currently, wind-generated electricity is lowest in summer in each region except SWC, which causes a substantial mismatch with electricity demand. While electricity of residential heating may shift demand, research presented here suggests that summertime CF are likely to decline, potentially exacerbating the offset between seasonal peak power production and current load. The reduction in summertime CF is manifest for all regions except the SGP and appears to be linked to a reduction in synoptic-scale variability. Using fulfillment of 50% and 90% of annual energy production to quantify interannual variability, it is shown that wind power production exhibits higher (earlier fulfillment) or lower (later fulfillment) production for periods of over 10–30 years as a result of the action of internal climate modes. Significance Statement Electrical power system reassessment and redesign may be needed to aid efficient increased use of variable renewables in the generation of electricity. Currently wind-generated electricity in many regions of North America exhibits a minimum in summertime and hence is not well synchronized with electricity demand, which tends to be maximized in summer. Future projections indicate evidence of reductions in wind power during summer that would amplify this offset. However, electrification of heating may lead to increased wintertime demand, which would lead to greater synchronization.

Coburn, Jacob↗
DOE OSTI2024

Tornadoes in Southeast South America: Mesoscale to Planetary-Scale Environments

Abstract A multiscale analysis of the environment supporting tornadoes in southeast South America (SESA) was conducted based on a self-constructed database of 74 reports. Composites of environmental and convective parameters from ERA5 were generated relative to tornado events. The distribution of the reported tornadoes maximizes over the Argentine plains, while events are rare close to the Andes and south of Sierras de Córdoba. Events are relatively common in all seasons except in winter. Proximity environment evolution shows enhanced instability, deep-layer vertical wind shear, storm-relative helicity, reduced convective inhibition, and a lowered lifting condensation level before or during the development of tornadic storms in SESA. No consistent signal in low-level wind shear is seen during tornado occurrence. However, a curved hodograph with counterclockwise rotation is present. The Significant Tornado Parameter (STP) is also maximized prior to tornadogenesis, most strongly associated with enhanced CAPE. Differences in the convective environment between tornadoes in SESA and the U.S. Great Plains are discussed. On the synoptic scale, tornado events are associated with a strong anomalous trough crossing the southern Andes that triggers lee cyclogenesis, subsequently enhancing the South American low-level jet (SALLJ) that increases moisture advection to support deep convection. This synoptic trough also enhances vertical shear that, along with enhanced instability, sustains organized convection capable of producing tornadic storms. At planetary scales, the tornadic environment is modulated by Rossby wave trains that appear to be forced by convection near northern Australia. Madden–Julian oscillation phase 3 preferentially occurs 1–2 weeks ahead of tornado occurrence. Significance Statement The main goal of this study is to describe what atmospheric conditions (from local to global scales) are present prior to and during tornadic storms impacting southeast South America (SESA). Increasing potential for deep convection, wind shear, and potential for rotating updrafts, as well as reducing convective inhibition and cloud-base height, are predominant a few hours before and during the events in connection to low-level northerly winds enhancing moisture transport to the region. Remote convective activity near northern Australia appears to influence large-scale atmospheric circulation that subsequently triggers convective storms supporting tornadogenesis 1–2 weeks later in SESA. Our findings highlight the importance of accounting for atmospheric processes occurring at different scales to understand and predict tornado occurrences.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

Numerical and experimental evaluation of mechanical performance of the multifunctional energy storage composites

This work presents numerical simulation methods to model the mechanical behavior of the multifunctional energy storage composites (MESCs), which consist of a stack of multiple thin battery layers reinforced with through-the-hole polymer rivets and embedded inside carbon fiber composite laminates. MESC has been demonstrated through earlier experiments on its exceptional behavior as a structural element as well as a battery. However, the inherent complex infrastructure of the MESC design has created significant challenges in simulation and modeling. A novel homogenization technique was adopted to characterize the multi-layer properties of battery material using physics-based constitutive equations combined with nonlinear deformation theories to handle the interface between the battery layers. Second, mechanical damage and failure modes among battery materials, polymer reinforcements, and carbon fiber-polymer interfaces were characterized through appropriate models and experiments. The model of MESCs has been implemented in a commercial finite element code in ABAQUS. A comparison of structural response and failure modes from numerical simulations and experimental tests are presented. The results of the study showed that the predictions of elastic and damage responses of MESCs at various loading conditions agreed well with the experimental data. © 2021

Materials Science↗
DOE OSTI2023

Lipoprotein subfraction patterns throughout gestation in The Gambia: changes in subfraction composition and their relationships with infant birth weights

Lipoprotein subfraction concentrations have been shown to change as gestation progresses in resource-rich settings. The objective of the current study was to evaluate the impact of pregnancy on different-sized lipoprotein particle concentrations and compositions in a resource-poor setting. Samples were collected from pregnant women in rural Gambia at enrollment (8–20 weeks), 20 weeks, and 30 weeks of gestation. Concentrations of different-sized high-density, low-density, and triglyceride-rich lipoprotein particles (HDL, LDL, and TRL, respectively) were measured by nuclear magnetic resonance in 126 pooled plasma samples from a subset of women. HDL was isolated and the HDL proteome evaluated using mass spectroscopy. Subfraction concentrations from women in The Gambia were also compared to concentrations in women in the U.S. in mid gestation. Total lipoprotein particles and all-sized TRL, LDL, and HDL particle concentrations increased during gestation, with the exception of medium-sized LDL and HDL particles which decreased. Subfraction concentrations were not associated with infant birth weights, though relationships were found between some lipoprotein subfraction concentrations in women with normal versus low birth weight infants (< 2500 kg). HDL’s proteome also changed during gestation, showing enrichment in proteins associated with metal ion binding, hemostasis, lipid metabolism, protease inhibitors, proteolysis, and complement activation. Compared to women in the U.S., Gambian women had lower large- and small-sized LDL and HDL concentrations, but similar medium-sized LDL and HDL concentrations. Most lipoprotein subfraction concentrations increase throughout pregnancy in Gambian women and are lower in Gambian vs U.S. women, the exception being medium-sized LDL and HDL particle concentrations which decrease during gestation and are similar in both cohorts of women. The proteomes of HDL also change in ways to support gestation. These changes warrant further study to determine how a lack of change or different changes could impact negative pregnancy outcomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Data for Protoplast Fusion as a Strategy to Increase Ploidy in Rhodotorula toruloides for Strain Development

Rhodotorula toruloides is a red oleaginous yeast with growing commercial interest because of its hardiness and exceptional lipid production capacity. Because it is a basidiomycete yeast with a complex life cycle, many of the classical breeding methods used with ascomycetes are unavailable for strain improvement. However, we have been able to construct polyploid yeast by fusing protoplasts of parents with the same mating type. Fusing of Y-6985 (A2) and Y-48190 (A2), which had been transformed with complementary antibiotic markers, led to the recovery of two diploids and one triploid. The stability of the fusion yeasts was tested by plating them on non-selective medium after several growth cycles under antibiotics and then testing five colonies per strain for nuclear DNA contents using flow cytometry and standard cell cycle analysis: the triploid and one diploid were stable. Fusants inherited their mitochondria from a single parent, which was demonstrated using restriction fragment length polymorphism (RFLP) of mitochondrial DNA. The phenotypic properties of the parents and fusants were compared in glucose fed-batch bioreactor studies and cellulosic sugar batch cultures. The final lipid titers for the fed-batch cultures were 24.9–39.7 g/L with Y-6985 and the diploid and triploid performing the best and worst, respectively. The fusants demonstrated intermediate hardiness for growth on hydrolysate prepared with dilute-acid pretreated switchgrass and were outperformed by Y-48190. Unlike one of the haploid parents, the fusants grew in 70% v/v concentrated hydrolysate. However, they did not grow as fast as the other haploid. In this study, a modernized protoplast fusion method is resurrected a useful tool for strain development in this yeast, which is complementary with other available methods.

FOS: Biological sciences↗
DOE OSTI2026

Data for Clumping Index Estimation With 30°-tilted Cameras in Row Crops: Evaluation of Methods and Segment Size Effects

The clumping index (CI) quantifies the spatial distribution of foliage elements and is essential for accurately estimating the plant area index (PAI), canopy radiative transfer, and photosynthesis. Traditionally, the finite-length averaging method (LX), the gap size distribution method (CC), and a combined approach of CC and LX (CLX) have been applied to instruments like TRAC and digital hemispherical photography to estimate CI. However, a comprehensive evaluation of these methods in row crops remains limited, especially regarding the influence of segment size on CI. Meanwhile, digital cameras offer a cost-effective and user-friendly solution for canopy measurements in row crops, yet their application in this context remains underexplored. In this study, we employed a new approach using a 30°-tilted digital camera to estimate CI in corn and soybean fields, applying the LX, CC, and CLX methods. We systematically assessed the performance of these three methods by combining field measurements in real-world fields with simulations using the LESS 3D radiative transfer model. Our results showed that CLX applied to the whole image and 45° segment offered accurate estimation of CI (bias within ±0.1, RMSE < 0.2) and PAI (bias within ±0.4, RMSE < 1) in real-world fields and LESS simulations. The accuracy of the LX method was highly sensitive to segment size, with the best performance observed at the 15° segment (PAI bias within ±0.4). In contrast, the CC method remained stable across different segment sizes, and its performance was generally comparable to that of LX, except at the 15° segment. Across view zenith angles, CI derived from CC generally showed a continuous increase, while those from LX and CLX followed a rising trend at small zenith angles but began to decline at 68°, likely due to an increasing proportion of no-gap segments. Seasonally, LX tended to show decreasing CI during early growth stages but increased as the canopy matured, whereas CC and CLX showed gradually increasing CI before plateauing at peak PAI. The 30°-tilted camera effectively captured CI variations across different angles and growth stages, making it a practical and robust instrument for row crop canopy structure analysis. Applying these CI methods to digital cameras offers a low-cost and accessible CI estimation alternative, improving canopy structure monitoring accuracy in row crops.

Modeling↗
DOE OSTI2023

NbTa_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-tantalum (Nb-Ta). 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. For Ta, p semi-core states as valence were chosen. 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 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 ternary alloys is AXBYCZ, where A, B, and C refer to the constituents, and X, Y, and Z 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. Subdirectories with name case-N, where N ranges between 1 and 10 (extremes included) contain all the files listed above except 'vaspout.h5'. Subdirectories with name case-N, where N ranges between 41 and 60 (extremes included), contain a duplicate copy of the files listed above except for KPOINTS. The names of the duplicate files end with -bis, and correspond to a second VASP calculation that has converged to a different optimized geometry. 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. and Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. and 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. and 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. and 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. and Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2023

TaV_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-vanadium (Tanu-V). 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. 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 element V. For Ta, p semi-core states as valence were chosen. 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. Subdirectories with name case-N, where N ranges between 1 and 10 (extremes included) contain all the files listed above except 'vaspout.h5'. Subdirectories with name case-N, where N ranges between 41 and 60 (extremes included), contain a duplicate copy of the files listed above except for KPOINTS. The names of the duplicate files end with -bis, and correspond to a second VASP calculation that has converged to a different optimized geometry. 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. and Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. and 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. and Furthmuller, 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. and Furthmuller, 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. and Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2023

NbV_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-vanadium (Nb-V). 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 V. 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. Subdirectories with name case-N, where N ranges between 1 and 10 (extremes included) contain all the files listed above except 'vaspout.h5'. Subdirectories with name case-N, where N ranges between 41 and 60 (extremes included), contain a duplicate copy of the files listed above except for KPOINTS. The names of the duplicate files end with -bis, and correspond to a second VASP calculation that has converged to a different optimized geometry. 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. and Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. review B 47, 558 (1993). (2) Kresse, G. and 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. and 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. and 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. and Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. review b 59, 1758 (1999)

36 MATERIALS SCIENCE↗
DOE OSTI2023

Adaptive methods of generating complex light arrays

Structured light arrays of various shapes have been a cornerstone in optical science, driven by the complexities of precise and adaptable generation. This study introduces an approach using a spatial light modulator (SLM) as a generator for these arrays. By projecting a holographic mask onto the SLM, it functions simultaneously as an optical convolution device, focusing mechanism, and structured light beam mask. Our approach offers unmatched versatility, allowing for the experimental fabrication of traditional beam arrays like azimuthal Laguerre–Gaussian (LG), Bessel–Gaussian (BG), and Hermite–Gauss (HG) in the far-field. Notably, it has enabled a method of generating Ince–Gauss (IG) and LG radial mode beam arrays using a convolution solution. Our system provides exceptional control over array periodicity and intensity distribution, bypassing the Talbot self-imaging phenomenon seen in traditional setups. We provide an in-depth theoretical discussion, supported by empirical evidence, of our far-field results. This method has vast potential for applications in optical communication, data processing, and multi-particle manipulation. It paves the way for rapid generation of structured light with high spatial frequencies and complex shapes, promising transformative advances in these domains.

Optics↗
DOE OSTI2024

Giant optical second- and third-order nonlinearities at a telecom wavelength

A material platform that excels in both optical second- and third-order nonlinearities at a telecom wavelength is theoretically and experimentally demonstrated. In this TiN-based coupled metallic quantum well structure, electronic subbands are engineered to support doubly resonant inter-subband transitions for an exceptionally high second-order nonlinearity and provide single-photon transitions for a remarkable third-order nonlinearity within the 1400–1600 nm bandwidth. The second-order susceptibility χ (2) reaches 2840 pm/V at 1440 nm, while the Kerr coefficient n 2 arrives at 2.8 × 10 −10 cm 2 /W at 1460 nm. The achievement of simultaneous strong second- and third-order nonlinearities in one material at a telecom wavelength creates opportunities for multi-functional advanced applications in the field of nonlinear optics.

Chen, Ching-Fu (ORCID:0000000262510722)↗
DOE OSTI2021

Heavy Oil Polymer EOR in the Challenging Alaskan Arctic - It Works!

Under co-sponsorship of the US Department of Energy and Hilcorp Alaska LLC the first ever polymer field pilot commenced on 8/28/2018 in the Schrader Bluff heavy oil reservoir at the Milne Point Field on Alaska North Slope (ANS). The primary objective of the pilot is to prove the efficacy of polymer Enhanced Oil Recovery (EOR) to unlock the vast heavy oil resources on ANS. More than two and half years after startup, the polymer injection, supporting laboratory experiments and simulation studies steadily continue. The pilot started injecting hydrolyzed polyacrylamide (HPAM), at a concentration of 1,750 ppm to achieve a target viscosity of 45 cP, into the two horizontal injectors in the flood pattern. Production is monitored in the two horizontal producers. Based on laboratory measurements of polymer viscosity at reservoir conditions, the team decided to reduce polymer concentration to 1,200 ppm since July 2020 in an effort to control injection pressure and optimize polymer utilization. Quality control (QC) on the field ensures uniform polymer solution properties. Representative rock and fluid systems and test conditions are utilized in the corefloods on polymer retention, effect of injection water salinity, polymer loading, and their combinations on oil recovery. A history matched reservoir simulation model for forecasting oil recovery was developed on the basis of all the available field data. Field concerns related to the post-polymer breakthrough impact on flow assurance is addressed via specialized laboratory tests. Notwithstanding early operational disruptions and hydration issues, continuous polymer injection in both injectors has been achieved. To date, 950,000 lbs of polymer or 2 million barrels of polymer solution, equating to 13% of total pore volume (PV), has been placed in the flood pattern, serving as an effective indicator of adequate polymer injectivity. So far, the success of polymer EOR is evident from drastically reduced water cut in the producers, an estimated incremental 1,000 bopd over waterflood, and a favorable polymer utilization of 1.7 lbs/barrel of incremental oil. Polymer breakthrough was observed 26 months after the start of polymer injection. Main observations from corefloods are unusually high polymer retention values in some cases and a positive response to low salinity water. Although the heterogeneity in the flood pattern and exceptionally low water cut pose some challenges, persistent novel and justifiable simulation approaches have resulted in a robust history matched model. Experimental results on produced fluids treatment provide operational guidance for improved oil-water separation and mitigation of heater tube fouling. The ongoing success of the pilot is a key indicator of bringing the team ever closer to meeting the project’s primary objective. The encouraging results of the pilot is one of the drivers that has provided the impetus to apply polymer EOR throughout the Milne Point Field, which would increase oil recovery and extend the economic life of the Trans Alaska Pipeline System. The scientific knowledge, including the many lessons learned from this pilot also has referential value for other potential heavy oil EOR projects throughout the world. The collected data, operational lessons learned, and the overall success of the pilot are summarized in the paper.

None, None↗
DOE OSTI2020

Hydraulic Properties Data Package for the E-Area Soils, Cementitious Materials, and Waste Zones–Update

Hydraulic property estimates for the soils, cementitious materials, and waste zones associated with the E-Area low-level radioactive waste disposal units have been provided to support the Performance Assessments (PA) for the E-Area Low-Level Waste Facility (LLWF). Nominal or “best estimate” hydraulic property values for use in the deterministic modeling are provided along with representations of the hydraulic property value uncertainty for use in sensitivity and uncertainty modeling. The hydraulic properties provided for each of the E-Area materials include: porosity ( η ), dry bulk density ( ρ b ), particle density (ρ p ), saturated hydraulic conductivity ( K sat ), characteristic curves (suction head, saturation, and relative permeability), and effective diffusion coefficient ( D e ). A representation of the uncertainty associated with each property, except for the characteristic curves, is provided for each material, except for the E-Area waste zones. These nominal parameter values for each of the E-Area soils, cementitious materials, and waste zones, and, where indicated, parameter uncertainty representations, are based upon the following in order of priority: Site-specific field data, Site-specific laboratory data, Similarity to material with site-specific field or laboratory data, and Literature data. Additionally, a methodology to represent long-term concrete degradation is provided. Finally, because much of the nominal hydraulic property values and uncertainty representations for the E-Area soils, cementitious materials, and waste zones are based on similarity to other materials or literature data, a methodology to prioritize additional work to better define these values and representations is outlined. Prioritization should be based on the importance of the material and/or property to the results of deterministic, sensitivity, and uncertainty modeling. This prioritization should be established through a process of sensitivity modeling. This report supersedes the previous hydraulic properties data package. Revision 1 contains clarifications, updates and corrections to text, figures and tables in a number of places in the report along with some minor editing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗