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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↗

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↗

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↗

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↗

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↗

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↗

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↗

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↗

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)↗

Transposable Elements versus the Fungal Genome: Impact on Whole-Genome Architecture and Transcriptional Profiles

Transposable elements (TEs) are exceptional contributors to eukaryotic genome diversity. Their ubiquitous presence impacts the genomes of nearly all species and mediates genome evolution by causing mutations and chromosomal rearrangements and by modulating gene expression. We performed an exhaustive analysis of the TE content in 18 fungal genomes, including strains of the same species and species of the same genera. Our results depicted a scenario of exceptional variability, with species having 0.02 to 29.8% of their genome consisting of transposable elements. A detailed analysis performed on two strains of Pleurotus ostreatus uncovered a genome that is populated mainly by Class I elements, especially LTR-retrotransposons amplified in recent bursts from 0 to 2 million years (My) ago. The preferential accumulation of TEs in clusters led to the presence of genomic regions that lacked intra- and inter-specific conservation. In addition, we investigated the effect of TE insertions on the expression of their nearby upstream and downstream genes. Our results showed that an important number of genes under TE influence are significantly repressed, with stronger repression when genes are localized within transposon clusters. Our transcriptional analysis performed in four additional fungal models revealed that this TE-mediated silencing was present only in species with active cytosine methylation machinery. We hypothesize that this phenomenon is related to epigenetic defense mechanisms that are aimed to suppress TE expression and control their proliferation.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

El Paso County Geothermal Project at Fort Bliss. Final Project Report

The El Paso County Geothermal Project at Fort Bliss was an effort to determine the scale and scope of geothermal resources previously identified on Fort Bliss’ McGregor Range in southern Otero County, New Mexico. The project was funded with a $5,000,000 grant to El Paso County from the U.S. Department of Energy (DOE) as part of the American Recovery and Reinvestment Act of 2009 and a $4,812,500 match provided by private sector partners. The project was administered through the DOE Golden Field Office to awardee El Paso County. The primary subcontractor to El Paso County and project Principal Investigator - Ruby Mountain Inc. (RMI) of Salt Lake City, Utah - assembled the project team consisting of Evergreen Clean Energy Management (ECEM) of Provo, Utah, and the Energy & Geoscience Institute at the University of Utah (EGI) in Salt Lake City, UT to complete the final phases of the project. The project formally began in May of 2010 and consisted of two preliminary phases of data collection and evaluation which culminated in the identification of a drilling site for a Resource Confirmation Well on McGregor Range. Well RMI 56-5 was drilled May and June 2013 to a depth of 3,030 ft. below ground level. A string of slotted 7 inch casing was set in 8.75 inch hole on bottom fill at 3,017 ft. to complete the well. The well was drilled using a technique called flooded reverse circulation, which is most common in mineral exploration. This technique produced an exceptionally large and complete cuttings record. An exciting development at the conclusion of drilling was the suspected discovery of a formation that has proven to be of exceptionally high permeability in three desalinization wells six miles to the south. Following drilling and preliminary testing and analysis, the project team has determined that the McGregor Range thermal anomaly is large and can probably support development in the tens of megawatts.

15 GEOTHERMAL ENERGY↗

Revised Heating Load Line Analysis: Addendum to ORNL/TM-2015/281

The original heating load line analysis of ORNL TM-2015/281 was modified to incorporate two adjustments of (1) removing mechanical ventilation and (2) resizing the heat pump units based on new criteria. This resulted in a lowering of the HLL slope factor from the originally rounded 1.3 level to 1.15 in DOE Region IV and V while leaving unchanged the zero-load ambient at a rounded value of 55 F. For the other four DOE regions, the zero-load ambients dropped by 1 to 2 F from those found earlier and the rounded HLL slope factors ranged from 1.05 to 1.3. The average rounded HLL slope factor over all six DOE regions is 1.15. Effects of the revised slope factor on rated HSPFs (Region IV) for single- and two-capacity units dropped from 16% in the original work to 12.6% in this report. For VS units, the HSPF reductions of 14 to 25% in the original report were lowered to a range of 9 to 21%. As in the original report, for VS units that do not limit minimum speed operation below 47 F ambient, the average HSPF reduction for the cases evaluated is approximately the same as for single- and two-capacity units. For VS units that do limit minimum speed operation below 47 F ambient, the lower 1.15 slope factor of this report generally results in small overpredictions of rated HSPF by 1 to 3% compared to functional HSPF. An exception is minimum-speed-limited VS units where the minimum speed COP at 47 F is higher than that at 62 F; one such unit was found to have an HSPF overprediction of over 14% with the 1.15 HLL slope factor level. For such VS exception cases, a default HSPF penalty should be considered. For the more typical VS units that limit minimum speed operation, use of a 1.15 slope factor for rated HSPF was found to still acceptably limit the HSPF error. If slope factors lower than 1.15 are used for HSPF ratings, some means should be considered to appropriately derate the HSPFs for VS units which limit minimum speed operation below 47 F ambient.

42 ENGINEERING↗

Financial Analysis of Experimental Releases Conducted at Glen Canyon Dam during Water Year 2015

This report examines the financial implications of experimental flows conducted at the Glen Canyon Dam (GCD) in water year (WY) 2015. It is the seventh report in a series examining the financial implications of experimental flows conducted since the Record of Decision (ROD) was adopted in February 1997 (Reclamation 1996). A report released in January 2011 examined WYs 1997 to 2005 (Veselka et al. 2011); a report released in August 2011 examined WYs 2006 to 2010 (Poch et al. 2011); a report released June 2012 examined WY 2011 (Poch et al. 2012); a report released April 2013 examined WY 2012 (Poch et al. 2013); a report released June 2014 examined WY 2013 (Graziano et al. 2014); and a report released September 2015 examined WY 2014 (Graziano et al. 2015). An experimental release may have either a positive or negative impact on the financial value of energy production. Only one experimental release was conducted at GCD in WY 2015; specifically, a high flow experimental (HFE) release conducted in November 2014. For this experimental release, financial costs of approximately $2.1 million were incurred because the HFE required sustained water releases that exceeded the powerplant’s maximum flow rate. In addition, during the month of the experiment, operators were not allowed to shape GCD power production to either follow firm power customer loads or to respond to market prices. This study identifies the main factors that contribute to HFE costs and examines the interdependencies among these factors. It applies an integrated set of tools to estimate financial impacts by simulating the GCD operations under two scenarios: (1) a baseline scenario that mimics both HFE operations during the experiment and during the rest of the year when it complies with the 1996 ROD operating criteria, and (2) a “without experiments” scenario that is identical to the baseline except it assumes that the HFE did not occur. The Generation and Transmission Maximization (GTMax) model was the main simulation tool used to simulate the dispatch of hydropower plants at GCD and other plants that comprise the Salt Lake City Area Integrated Projects (SLCA/IP). The research team used extensive data sets and historical information on SLCA/IP powerplant characteristics, hydrologic conditions, and Western Area Power Administration’s (WAPA’s) power purchase prices in the modeling process. In addition to estimating the financial impact of the HFE, the team used the GTMax model to gain insights into the interplay among ROD operating criteria, exceptions that were made to criteria to accommodate the experimental releases, and WAPA operating practices.

54 ENVIRONMENTAL SCIENCES↗

Data Validation Package November 2015 Groundwater and Surface Water Sampling at the Old and New Rifle, Colorado, Processing Sites February 2016

Water samples were collected from 36 locations at New Rifle and Old Rifle, Colorado, Processing Sites. Duplicate samples were collected from New Rifle locations 0659 and 0855, and Old Rifle location 0304. One equipment blank was collected after decontamination of non-dedicated equipment used to collect one surface water sample. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated). New Rifle Site Samples were collected at the New Rifle site from 16 monitoring wells and 7 surface locations in compliance with the December 2008 Groundwater Compliance Action Plan [GCAP] for the New Rifle, Colorado, Processing Site (LMS/RFN/S01920), with one exception: New Rifle location 0635 could not be sampled because it was inaccessible; a fence installed by the Colorado Department of Transportation prevents access to this location. DOE is currently negotiating access with the Colorado Department of Transportation. Analytes measured at the New Rifle site included contaminants of concern (COCs) (arsenic, molybdenum, nitrate + nitrite as nitrogen, selenium, uranium, and vanadium) ammonia as nitrogen, major cations, and major anions. Field measurements of total alkalinity, oxidation- reduction potential, pH, specific conductance, turbidity, and temperature were made at each location, and the water level was measured at each sampled well. A proposed alternate concentration limit (ACL) for vanadium of 50 milligrams per liter (mg/L), specific to the compliance (POC) wells (RFN-0217, -0659, -0664, and -0669) is included in the New Rifle GCAP. Vanadium concentrations in the POC wells were below the proposed ACL as shown in the time-concentration graphs in the Data Presentation section (Attachment 2). Time-concentration graphs from all other locations sampled are also included in Attachment 2. Sampling location RFN-0195 was misidentified for the June/August 2014 and November 2014 sampling events. (Well RFN-0609 was inadvertently sampled instead of RFN-0195 in 2014.) The results for RFN-0195 have been corrected, and are included in associated time-concentration graphs for this location. Recent results for RFN-0195 are consistent with established trends with the possible exception of vanadium. The most recent result for vanadium showed an increase over recent values. Vanadium concentrations at RFN-0195 and other locations will continue to be evaluated in the future to determine the potential for deviations from established trends. The surface water locations were sampled to monitor the impact of groundwater discharge. COC concentrations at Colorado River surface water locations RFN-0324 and RFN-0326, downgradient of the site, remained low and were consistent with historical results, as shown in the time-concentration graphs. COC concentrations did not indicate there are any impacts related to groundwater discharge to the river. In many cases, elevated COC concentrations at the New Rifle site pond locations were observed, as shown in the time-versus concentration graphs. As noted in the GCAP, this indicates impacts from groundwater discharge to the ponds. Old Rifle Site Samples were collected at the Old Rifle site from eight monitoring wells and five surface locations in compliance with the December 2001 Groundwater Compliance Action Plan for the Old Rifle, Colorado, UMTRA Project Site (GJ0-2000-177-TAR). Analytes measured at the Old Rifle site included COCs (selenium, uranium, and vanadium), major cations, and major anions. Field measurements of total alkalinity, oxidation-reduction potential, pH, specific conductance, turbidity, temperature, were made at each location, and the water level was measured at each sampled well. The monitoring strategy described in the GCAP is designed to determine progress of the natural flushing process in meeting compliance standards for site COCs. Standards for selenium and vanadium are the proposed ACLs of0.05 mg/L and 1.0 mg/L, respectively. For uranium the cleanup goal is the UMTRA standard of 0.044 mg/L or background, whichever is higher. As shown in the time concentration graphs, the uranium concentration exceeds the cleanup goal at groundwater monitoring locations RF0-0304, -0305, -0310, -0655, and -0656. The surface water locations were sampled to monitor the impact of groundwater discharge at Colorado River surface water locations adjacent to (RF0-0396) and downgradient of the site (RF0-0741). COC concentrations remain low and consistent with historical concentrations as shown in the time-concentration graphs (Attachment 2), which indicate no impacts from groundwater discharge to the river.

2015 Old and New Rifle↗

Management Observation Facility Fume Hoods

I reviewed all the hoods used for AS&I work in buildings 253, 254, and 255. All have had the minimum annual surveys conducted and some have had semi-annual reviews. The operating parameter labels are posted consistent to the right or above right (with the only exception the perchloric acid hood in 1734- on the left) which facilitates users knowing where to check for information. All hoods with sash doors (except the SE one in 1734 have a note on the Operating Parameters label to "keep sash doors closed". Again, this was checking consistency. No surveys were missed.

61 RADIATION PROTECTION AND DOSIMETRY↗

Completion Report for Well ER-4-1 Corrective Action Unit 97: Yucca Flat/Climax Mine, Revision 0

Well ER-4-1 was drilled for the U.S. Department of Energy, Nevada National Security Administration Nevada Field Office in support of the Underground Test Area (UGTA) Activity. The well was drilled and completed from March 23 to April 13, 2016, as part of the Corrective Action Investigation Plan (CAIP) for Yucca Flat/Climax Mine Corrective Action Unit (CAU) 97. The primary purpose of the well was to collect hydrogeologic data to assist in validating concepts of the groundwater flow system within the Yucca Flat/Climax Mine CAU, and to test for potential radionuclides in groundwater from the STRAIT (U4a) underground test. The completed well includes one piezometer (p1), to a depth of 663.16 meters (m) (2,175.71 feet [ft]) below ground surface (bgs) and open from the Alluvial aquifer (AA3) to the Oak Spring Butte confining unit (OSBCU) hydrostratigraphic units; and a main completion (m1), which includes 6.625-inch (in.) casing with slotted interval (m1) installed to 906.80 m (2,975.05 ft) bgs in the Lower carbonate aquifer (LCA). A 13.375-in. diameter surface casing was installed from the surface to a depth of 809.00 m (2,654.21 ft) bgs. Well ER-4-1 experienced a number of technical issues during drilling, including borehole instability and sloughing conditions. An intermediate, 10.75-in./9.625-in. casing string was installed to 856.94 m (2,811.48 ft) bgs to control these issues. Borehole stability and erosion problems appear to be associated with the Tunnel Formation (Tn) and the Older tunnel beds (Ton). Overall efforts to stabilize the borehole were successful. Data collected during borehole construction include composite drill cutting samples collected every 3.0 m (10 ft), a partial suite of geophysical logs to a maximum depth of 766.57 m (2,515 ft) bgs, water-quality measurements (including tritium), water-level measurements, and two depth-discrete bailer samples collected at 538.89 m and 646.18 m (1,768 ft and 2,120 ft) bgs respectively. The well penetrated 187.45 m (615 ft) of Quaternary/Tertiary alluvium (QTa), 671.47 m (2,203 ft) of Tertiary Volcanic rocks (Tv), and 66.20 m (217.19 ft) of Paleozoic rocks (|). The stratigraphy and lithology were generally as expected with some exceptions. The top of Paleozoic rocks (|) was predicted to occur at 822.35 m (2,698 ft) bgs and was intercepted at 858.93 m (2,818 ft), a difference of 36.58 m (120 ft). As expected, the Paleozoic rocks (|) are the principal water producing formation in Well ER-4-1. Depth to water was measured after drilling as follows: In the piezometers: p1 at 320.39 m (1,051.16 ft) bgs, (measured January 4, 2017); and in the main production casing interval: m1 at 539.17 m (1,768.92 ft) bgs, (measured December 12, 2016) Geophysical logs and depth-discrete bailer sample analytical results suggest likely zones of prompt injection (underground-test-related) fission products from 472.44 to 481.48 m (1,550 to 1,580 ft) bgs and at approximately 539.50 m (1,770 ft) bgs. Subsequent work at Well ER-4-1 will be included in future reports. Field measurements for tritium were mostly below the Safe Drinking Water Act limit (20,000 picocuries per liter) with the exception of two zones showing elevated tritium concentrations. The first zone is located at approximately 365.76 to 390.14 m (1,200 to 1,280 ft) bgs and a second zone at approximately 542.54 to 566.93 m (1,780 to 1,860 ft) bgs. All Fluid Management Plan requirements were met.

54 ENVIRONMENTAL SCIENCES↗

Assessment of commercially available energy-efficient room air conditioners including models with low global warming potential (GWP) refrigerants

Improving the energy efficiency of room air conditioners (RACs) while transitioning to low global-warming-potential (GWP) refrigerants will be a critical step toward reducing the energy, peak load, and emissions impacts of RACs while keeping costs low. Previous research quantified the benefits of leapfrogging to high efficiency in tandem with the transition to low-GWP refrigerants for RACs (Shah et al., 2015) and identified opportunities for initial action to coordinate energy efficiency with refrigerant transition in economies constituting about 65% of the global RAC market (Shah et al., 2017). This report describes further research performed to identify the best-performing (i.e., most efficient and low-GWP-refrigerant using) RACs on the market, to support an understanding of the best available technology (BAT). Understanding BAT can help support market-transformation programs for high-efficiency and low-GWP equipment such as minimum energy performance standards (MEPS), labeling, procurement, and incentive programs. We studied RACs available in six economies—China, Europe, India, Japan, South Korea, and the United States—that together account for about 70% of global RAC demand, as well as other emerging economies. The following are our key findings: • Highly efficient RACs using low-GWP refrigerants, e.g., HFC-32 (R-32) and HC-290 (R-290), are commercially available today at prices comparable to similar RACs using high-GWP HCFC-22 (R-22) or HFC-410A (R-410A). • High efficiency is typically a feature of high-end products. However, highly efficient, cost-competitive (less than 1,000 or 1,500 U.S. dollars in retail price, depending on size) RACs are available. • Where R-22 is being phased out, high GWP R-410A still dominates RAC sales in most mature markets except Japan, where R-32 dominates. • In all of the economies studied except Japan, only a few models are energy efficient and use low-GWP refrigerants. For example, in Europe, India, and Indonesia, the highest-efficiency RAC models employ the low-GWP refrigerants R-32 or R-290. • RACs are available in most regions and worldwide that surpass the highest efficiency levels recognized by labeling programs. • Fixed-speed RACs using high-GWP and ozone-depleting R-22 refrigerant still dominate the market in many emerging economies. There is significant scope to improve RAC efficiency and transition to low-GWP refrigerants using commercially available technology and to design market-transformation programs for high-efficiency, low-GWP equipment including standards, labeling, procurement, and incentive programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗