SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
Modifications in inverted Stepanov process improve heat transfer and energy efficiency in growing silicon ribbon crystals. Using system, silicon is directly heated by induction, minimizing heat transfer and contamination problems.
The magnitude of the photon-induced current in Ag-Al2O3-Al metal-oxide-metal junctions has been studied as a function of photon energy and angle of incident radiation. Photocurrents were theoretically analyzed on the basis of a modified vacuum photoemission model (Jain, 1975; Slayman et al., to be published). Optical constants previously reported in the literature (Irani et al., 1971; Ehnrereich et al., 1963) were used to calculate the true spatial generation rate in Ag and Al as a function of the angle, polarization of incident radiation, and film thickness. Results were found to be in very good agreement with experimentally determined values for a tunable dye laser with a KDP doubling crystal pumped by a Q-switched Nd:YAG laser with a LiIO3 doubling crystal. The system provided risetimes of 50 ns or less and peak powers of 10 W. Under short circuit conditions, the photoresponse to incident power was linear up to available power densities of 10 kW/sq cm. Quantum efficiencies of about 0.1% at zero-bias, near 3.8 eV under P polarization, were typically observed.
The objective of the low gravity crystal growth experiments is to develop a novel solute diffusion method for growing single crystals. The experiments will utilize specially designed reactors with three or more compartments separated by valves to keep the reactant solutions and solvent separated until the apparatus reaches low gravity. There will be a mechanism for opening the valves automatically to initiate the diffusion and growth processes. The reactant reservoirs will be large enough to take advantage of the time provided by the Long Duration Exposure Facility (LDEF) flight. An array of several reactors will be mounted in a 12-in.-deep end center tray located on the Earth-facing end of the LDEF. Several reactors operating simultaneously will allow experimentation with more than one crystal growth system and/or variations of conditions for each. The reactors will be enclosed in a vacuum tight container and will be surrounded by thermal insulation. The temperature (approximately 35 deg C) will be regulated and any departures from the desired temperature will be recorded. Power requirements will be provided by LiSO2 batteries.
This paper describes an isothermal dendritic growth experiment (IDGE), a microgravity-oriented spaceborne scientific experiment designed to obtain 'convection-free' dendritic growth and thereby provide a test of dendritic growth theory. The apparatus includes a controlled thermostatic bath capable of providing + or - 2 mK stability, a photographic data collection system, a crystal growth chamber ensuring 'free' dendritic growth, and an optical RAM camera for crystal growth detection. The experiment will be carried on essentially automatically aboard the Materials Science Laboratory in the cargo bay of the Space Shuttle. The results of preliminary ground-based studies are presented.
A three-axis accelerometer subsystem, developed as part of a get-away-special Ga-As crystal growth system for the Space Shuttle, is described. Each axis of this subsystem contains a quartz flexure accelerometer capable of dc measurements, custom-designed measurement circuitry, a programmable microcomputer for measurement control and data reduction, and memory for recording data. The subsystem was flown as a free float experiment aboard the NASA KC-135 microgravity research aircraft, yielding measurements of accelerations during free float at a resolution of 10 micro-g.
In the present evaluation of results from studies of the interfacial chemistry and morphology of a buried lubricant-substrate interface, specimens of increasing complexity that culminated with the effects of excess sulfur and defects were characterized by XPS and SEM, as well as conversion-electron Moessbauer spectroscopy (CEMS). In order to simulate sputtered systems, single crystals of MoS2 were damaged with Ar(+) bombardment and coated with Fe. Fe is found to react differently with MoS2 depending on surface treatments, surface defects, annealing treatments, and the presence of excess sulfur. The annealing temperature determines which compounds are formed, as well as the crystal habit and plane at the Fe-MoS2 interface.
The objective of the proposed research is to obtain further insight into the onset and development of the defect-causing instabilities that anise due to the coupling of the bulk transport and nonlinear-interfacial kinetics during growth in the mixed regime, utilizing the reduction of the convective contribution to the bulk transport under microgravity. These studies will build upon the data on the effects of quantitative variations of the forced convection velocity on the averaged and time-dependent kinetic behavior of protein crystal growth systems that have recently been obtained in our laboratory.
Bulk compositions of martian meteorite basalts suggest that they formed from a highly depleted mantle that was variably metasomatised and enriched in incompatible elements. These results are consistent with radio-isotope results. Bulk chemical compositions of basaltic rocks retain clues and tracers to their origins and histories. Interpretations of bulk compositions are not so straight-forward as once envisioned, because real-world magmatic processes can be far from theoretical simple models like one-stage partial melting or closed-system fractional crystallization. Yet, bulk chemistry can shed a broad (if dim) light on Martian basalt petrogenesis that complements the sharply focussed illumination of radio-isotope systematics.
This presentation shows results from an initial study of the fundamental physics of ice-crystal ice accretion using the NASA Propulsion Systems Lab (PSL). Ice accretion due to the ingestion of ice-crystals is being attributed to numerous jet-engine power-loss events. The NASA PSL is an altitude jet-engine test facility which has recently added a capability to inject ice particles into the flow. NASA is evaluating whether this facility, in addition to full-engine and motor-driven-rig tests, can be used for more fundamental ice-accretion studies that simulate the different mixed-phase icing conditions along the core flow passage of a turbo-fan engine compressor. The data from such fundamental accretion tests will be used to help develop and validate models of the accretion process. The present study utilized a NACA0012 airfoil. The mixed-phase conditions were generated by partially freezing the liquid-water droplets ejected from the spray bars. This presentation shows data regarding (1) the freeze out characteristics of the cloud, (2) changes in aerothermal conditions due to the presence of the cloud, and (3) the ice accretion characteristics observed on the airfoil model. The primary variable in this test was the PSL plenum humidity which was systematically varied for two duct-exit-plane velocities (85 and 135 ms) as well as two particle size clouds (15 and 50 m MVDi). The observed clouds ranged from fully glaciated to fully liquid, where the liquid clouds were at least partially supercooled. The air total temperature decreased at the test section when the cloud was activated due to evaporation. The ice accretions observed ranged from sharp arrow-like accretions, characteristic of ice-crystal erosion, to cases with double-horn shapes, characteristic of supercooled water accretions.
This paper presents results from an initial study of the fundamental physics of ice-crystal ice accretion using the NASA Propulsion Systems Lab (PSL). Ice accretion due to the ingestion of ice-crystals is being attributed to numerous jet-engine power-loss events. The NASA PSL is an altitude jet-engine test facility which has recently added a capability to inject ice particles into the flow. NASA is evaluating whether this facility, in addition to full-engine and motor-driven-rig tests, can be used for more fundamental ice-accretion studies that simulate the different mixed-phase icing conditions along the core flow passage of a turbo-fan engine compressor. The data from such fundamental accretion tests will be used to help develop and validate models of the accretion process. The present study utilized a NACA0012 airfoil. The mixed-phase conditions were generated by partially freezing the liquid-water droplets ejected from the spray bars. This paper presents data regarding (1) the freeze out characteristics of the cloud, (2) changes in aerothermal conditions due to the presence of the cloud, and (3) the ice accretion characteristics observed on the airfoil model. The primary variable in this test was the PSL plenum humidity which was systematically varied for two duct-exit-plane velocities (85 and 135 ms) as well as two particle size clouds (15 and 50 m MVDi). The observed clouds ranged from fully glaciated to fully liquid, where the liquid clouds were at least partially supercooled. The air total temperature decreased at the test section when the cloud was activated due to evaporation. The ice accretions observed ranged from sharp arrow-like accretions, characteristic of ice-crystal erosion, to cases with double-horn shapes, characteristic of supercooled water accretions.
Using ice slurry produced from supercooled water with an in-stream crystallizer opens a new path for solarice systems, increasing efficiency and reducing investment cost compared to ice-on-coil systems. Power needs are decoupled from the stored energy since the heat exchangers are not evenly distributed in the ice storage vessel but directly placed as the heat pump evaporator, which depends on the heat pump capacity and not on the ice storage volume. The novel ice storage design can serve as a heat source for a heat pump, where its evaporator is used to supercool water below 0 °C, or for refrigeration. The supercooled water at a temperature around −2 °C, maintained in a meta-stable liquid state, is triggered to nucleate in an in-stream crystallizer. The current design of the ice crystallizer allows for continuous operation of the system and scalability. Experimental results obtained with a gasketed plate heat exchanger used to supercool water and an in-stream crystallizer operated at a power of up to 6.5 kW are presented.
Hard-sphere colloidal systems serve as model systems for aggregation, nucleation, crystallization and gelation as well as interesting systems in their own right. Similar colloidal systems have important technological uses such as paints and pharmaceuticals. There is a strong current interest in using colloidal systems to form photonic crystals. A number of colloidal experiments have flown on the space shuttle and a suite of experiments is currently active on the ISS A major scientific thrust of NASA's microgravity research is the crystallization of proteins for structural determination. The crystallization of proteins is a complicated process that requires a great deal of trial and error experimentation. In spite of a great deal of work, "better" protein crystals cannot always be grown in microgravity and conditions for crystallization are not well understood. Crystallization of colloidal systems interacting as hard spheres and with an attractive potential induced by entropic forces have been studied in a series of static light scattering experiments. Additionally, aggregation of a protein as a function of pH has been studied using dynamic light scattering.
MnSe-CdSe mixed crystals growth investigation by elements, binary compounds and solid solutions vapor transport properties
Flow, heat and mass transfer in a two-layer liquid system is investigated when the layers are subjected to a static magnetic field. The physical system consists of two immiscible liquids in a layer configuration with a free surface and an interfacial layer simulating two crystal growth configurations, namely, floating zone and horizontal zone melting. Mass transfer effects due to crystallization of one of the layers is also considered. The resulting flows are categorized into three types depending on: (a) the dominance of the free surface effect top layer, (b) a balance between the thermocapillary effect on the free surface and the interface effect between the two layers, or (c) the dominance of interfacial effects, in determining the system thermo-fluid characteristics. The use of an additional liquid layer atop the crystallizing layer leads to a reduction of the radial dopant inhomogeneity in comparison to the one-layer case. The effect an externally imposed magnetic field on dopant distribution in this two-layer configuration is rather ambiguous and depends on its direction and intensity resulting in the necessity of optimizing the applied magnetic field for a specific situation. In case of electrically non-conducting melts, the calculations show that some measure of flow control can be achieved by using an electrically conducting encapsulant layer of the desired thickness.
Glass composition preparation and research on crystallization kinetics of molten binary and ternary oxide systems of glass
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)
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)