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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Laser-induced fluorescence measurements of ion fluctuations in electron and ion presheaths

Electrostatic flow-driven instabilities have been predicted in the presheath region of low-temperature plasmas for both ion and electron rich sheaths. The ion-acoustic fluctuations that arise from these instabilities can influence transport through an enhanced collision rate. In this work, ion fluctuation spectra were measured using laser-induced fluorescence (LIF) in the presheath region for both sheath polarities. Furthermore, the non-invasive nature of LIF compared to that of probes is particularly valuable for these measurements because the sheath and presheath around a probe may generate their own flow-driven instabilities, which obscure the measurement. Measurements were made using a recently implemented field programmable gate array-based system able to measure ion fluctuation spectra up to 1 MHz using a two-point correlation function technique. Narrow bandwidth ion fluctuations were observed near 0:46 f pi (460 kHz) for both sheath polarities, where f pi is the ion plasma frequency. The observed fluctuations were significantly stronger in the electron sheath case and were observed over a larger volume of plasma. Fluctuations were measured in the ion sheath case at locations far enough from the sheath that linear theory predicts stability, suggesting that ion-acoustic instabilities generated in the relatively small unstable region near the boundary reflect from the sheath and perturb a much larger volume of the plasma. This is expected to affect probes with both ion and electron rich sheaths, meaning any dc biased probe may effectively act as an ion-acoustic wave antenna. These measurements are consistent with the recent theory and particle-in-cell results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Comparison of edge turbulence characteristics between DIII-D and C-Mod simulations with XGC1

The physical processes taking place at the separatrix and scrape-off layer regions are crucial for the operation of tokamaks as they govern the interaction of hot plasma with the vessel walls. Numerical modeling of the edge with state-of-the-art codes attempts to elucidate the complex interactions between neoclassical drifts, turbulence, poloidal and parallel flows that control the physical set-up of the SOL region. Here, we present post-processing analysis of simulation results from the gyrokinetic code XGC1, comparing and contrasting edge turbulence characteristics from a simulation of the DIII-D tokamak against a simulation of the Alcator C-Mod tokamak. We find that the equilibrium ExB flux across the separatrix has a similar poloidal pattern in both discharges which can be explained by rB-drifts and trapped ion excursions. Furthermore, collisionality is noted to play a major role in the way that it prevents local charge accumulations from having more global effects in the C-Mod case. In both cases, turbulent electron heat flux is observed to be higher than the ion one and is possibly related to the need of electrons to maintain quasineutrality through the only channel available to them for exiting the confinement. By Fourier analysis, we identify turbulent frequencies and growth rates of the dominant mode in both simulations. In the case of C-Mod, these numbers point to the presence of a drift wave. In the DIII-D case, further linear simulations with the Gene code reveal a trapped electron mode. Furthermore, using a blob detection and tracking tool, we present the amplitude and size distributions of the blobs from both simulations. The amplitude distributions are in qualitative agreement with experimental observations while the size distributions are consistent with the fact that most of the blobs are not connecting to the divertor plates and suggest that they are generated by the shearing of the turbulent modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2015

On Possible Arc Inception on Low Voltage Solar Array

Recent analysis of spacecraft failures during the period of 1990-2013 demonstrated clearly that electrostatic discharges caused more than 8 of all registered failures and anomalies, and comprised the most costly losses (25) for operating companies and agencies. The electrostatic discharges on spacecraft surfaces are the results of differential charging above some critical (threshold) voltages. The mechanisms of differential charging are well known, and various methods have been developed to prevent a generation of significant electric fields in areas of triple junctions. For example, low bus voltages in Low Earth Orbit plasma environment and slightly conducting layer over coverglass (ITO) in Geosynchronous Orbit surroundings are believed to be quite reliable measures to prevent discharges on respective surfaces. In most cases, the vulnerable elements of spacecraft (solar arrays, diode boards, etc.) go through comprehensive ground tests in vacuum chambers. However, tests articles contain the miniscule fragments of spacecraft components such as 10-30 solar cells of many thousands deployed on spacecraft in orbit. This is one reason why manufacturing defects may not be revealed in ground tests but expose themselves in arcing on array surface in space. The other reason for ineffectiveness of discharge preventive measures is aging of all materials in harsh orbital environments. The expected life time of modern spacecraft varies within the range of five-fifteen years, and thermal cycling, radiation damages, and mechanical stresses can result in surface erosion on conductive layers and microscopic cracks in coverglass sheets and adhesive films. These possible damages may cause significant increases in local electric field strengths and subsequent discharges. The primary discharges may or may not be detrimental to spacecraft operation, but they can produce the necessary conditions for sustained arcs initiation. Multiple measures were developed to prevent sustained discharges between adjacent strings, and many ground tests were performed to determine threshold parameters (voltage and current) for sustained arcs. And again, manufacturing defects and aging in space environments may result in considerable decrease of critical threshold parameters. This paper is devoted to the analysis of possible reasons behind arcing on spacecraft with low bus voltages.

plasma interaction↗
DOE OSTI2019

Active Measurement of Plasma Parameters in Over-Dense MFE Reactor Plasma Using High Frequency Beat-Wave Resonantly Generated Thermal Bernstein Waves

UC Davis was funded to explore the combination of beat-wave excitation and laser scattering to make completely non-invasive determination of local plasma conditions. This involves the use of two high frequency mm-wave sources of differing frequencies (the pump waves) to excite plasma waves at the difference of the frequencies, which is known as the beat frequency. The difference frequency or the frequency of the beat wave is chosen so that we produce plasma waves whose fluctuating electron density is a sensitive function of plasma parameters at the location where the source waves overlap. This fluctuation can be detected from outside the plasma, by measuring the deflection of a probe beam directed at the overlap region between the two pump waves (i.e., collective scattering). This work is an extension of mm-wave frequencies of a 10 GHz beat-wave experiment conducted on the DDT toroidal device (see Fig. 1) in a magnetized plasma where the excited Langmuir wave is replaced by the magnetized upper hybrid wave. Here, two high power (> 1 kW) ~94 GHz pump sources will be employed to match the upper hybrid resonance. The primary envisioned experiment is to drive the electron Bernstein wave (EBW) in the interior of a magnetized plasma. The EBW is a hot-plasma electrostatic wave, which cannot propagate in vacuum. Roots of the EBW dispersion relation occur at frequencies slightly higher than harmonics of the electron cyclotron frequency. Use of the EBW has particular advantages for measuring plasma magnetic field in plasmas with relatively high density and low magnetic field, as is the case in spherical tokamaks. This is the “over dense” condition of future efficient high beta magnetic confinement fusion reactors such as the spherical tokamak (STs). The overarching goal of the proposed project is to demonstrate beat wave EBW excitation in low density and temperature parameters that are directly scalable to over-dense spherical tokamaks such as NSTX or MAST, where measurement of magnetic field by electron cyclotron emission (ECE) is experimentally complex, and requires models of plasma profiles in order to interpret results. In such experiments, availability of point measurements of magnetic field strength provided by a beat-wave diagnostic would serve as a powerful independent check on the ECE results, serving to validate the assumed profiles and wave-propagation models used. The first step was to assemble/modify the target chamber in which the beat-wave plasma experiments will take place. Here, the target chamber of the CTIX compact-toroid (spheromak) injector was chosen. At the time that the proposal was submitted, the aim was to conduct the experiments in the CTIX experimental facilities located at the Livermore campus of UC Davis using microwave/mm-wave equipment brought from the main campus., However, by the time DoE funds for this project were awarded, the CTIX experimental facilities located at the Livermore campus of UC Davis were in the process of being shut down due to the closure of the Livermore campus by Lawrence Livermore National Laboratory (LLNL). Consequently, the equipment needed for this project was crated up and shipped from Livermore to Davis as part of the laboratory shutdown after space on campus was secured and College of Engineering approval secured. Once it arrived in Davis on December 20, 2018, work on the project began in earnest with the initial efforts directed toward developing a new plasma target source. Because of the shutdown of the CTIX facility, the scope of the project thus had to be reduced due to the abbreviated amount of time allocated to the project once the shutdown/move had been completed. Chamber modifications have been completed, including the fabrication and installation of a 38 GHz interferometer, as described in Sec. 3. The thermionic plasma source has been tested and characterized. The magnetic field required for the EBW experiments will be generated by permanent magnets mounted on plates positioned above and below the chamber. Magnetic simulations have been performed, and show that a 3-ring magnet arrangement on each plate, with a plate separation of 50 cm, is required to achieve the ~100 G uniform magnetic field in the interaction region that we feel is necessary to ensure good EBW coupling. We proved unable to successfully revive either of Prof. Luhmann’s two high power (≥20 kW) 94 GHz millimeter-wave sources after their extended time in storage and decided to postpone further efforts and concentrate on slightly lower power sources. Consequently, we were successful in reviving a ~2 kW extended klystron amplifier (EIK), which together with a ~2 kW extended interaction oscillator (EIO) will provide the two pump sources required for the project. Safe operation of the EIO requires extensive modifications to one of Prof. Luhmann’s pulse modulators - these modulator modifications are ongoing, which has unfortunately delayed the planned beat-wave experiments. Details of this work are provided in Sec. 3. Even though project funding has now ended, we still plan to proceed to complete the EIO pulse modulator modifications, install the two ~94 GHz pump wave sources on the target chamber, and conduct unmagnetized tests of the beat-wave concept which involve coupling to unmagnetized electron plasma waves rather than magnetized EBWs. Should these experiments prove successful, we plan to submit a follow-up proposal for additional funding which would allow us to undertake the magnetized EBW experiments.

42 ENGINEERING↗
NASA NTRS2015

On Possible Arc Inception on Low Voltage Solar Array

Recent analysis of spacecraft failures during the period of 1990-2013 demonstrated clearly that electrostatic discharges caused more than 8 percent of all registered failures and anomalies, and comprised the most costly losses (25 percent) for operating companies and agencies. The electrostatic discharges on spacecraft surfaces are the results of differential charging above some critical (threshold) voltages. The mechanisms of differential charging are well known, and various methods have been developed to prevent a generation of significant electric fields in areas of triple junctions. For example, low bus voltages in Low Earth Orbit plasma environment and slightly conducting layer over cover-glass (ITO) in Geosynchronous Orbit surroundings are believed to be quite reliable measures to prevent discharges on respective surfaces. In most cases, the vulnerable elements of spacecraft (solar arrays, diode boards, etc.) go through comprehensive ground tests in vacuum chambers. However, tests articles contain the miniscule fragments of spacecraft components such as 10-30 solar cells of many thousands deployed on spacecraft in orbit. This is one reason why manufacturing defects may not be revealed in ground tests but expose themselves in arcing on array surface in space. The other reason for ineffectiveness of discharge preventive measures is aging of all materials in harsh orbital environments. The expected life time of modern spacecraft varies within the range of five-fifteen years, and thermal cycling, radiation damages, and mechanical stresses can result in surface erosion on conductive layers and microscopic cracks in cover-glass sheets and adhesive films. These possible damages may cause significant increases in local electric field strengths and subsequent discharges. The primary discharges may or may not be detrimental to spacecraft operation, but they can produce the necessary conditions for sustained arcs initiation. Multiple measures were developed to prevent sustained discharges between adjacent strings, and many ground tests were performed to determine threshold parameters (voltage and current) for sustained arcs. And again, manufacturing defects and aging in space environments may result in considerable decrease of critical threshold parameters. This paper is devoted to the analysis of possible reasons behind arcing on spacecraft with low bus voltages.

low voltage solar array↗
DOE OSTI2024

NbZr_BCC_SolidSolution_128atoms_VASP6

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

36 MATERIALS SCIENCE↗
DOE OSTI2024

TaZr_BCC_SolidSolution_128atoms_VASP6

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

36 MATERIALS SCIENCE↗