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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ChargeX OCPI Recommendations

The Open Charge Point Interface (OCPI) is an open protocol that enables electric vehicle (EV) charging systems to work together across networks. It supports communication and data sharing between Charge Point Operators (CPOs), who manage charging stations, and e-Mobility Service Providers (eMSPs), who provide charging services to EV drivers. OCPI facilitates functions like user authorization, remote charge point control, charging session data exchange, and billing through Charge Detail Records (CDRs). This allows EV roaming, so drivers can charge at different networks without multiple accounts. As the EV market grows due to increased adoption and technological advancements, OCPI faces higher demands. This has revealed issues with CDR format consistency, timestamp standardization across regions, transmission of EV-side error codes for troubleshooting, and support for new use cases. These challenges can affect operations and user experience, particularly as the industry starts considering Vehicle-to-Grid (V2G) systems, where EVs supply energy to the grid, and Vehicle-to-Everything (V2X) technologies for broader energy interactions. Using feedback from the ChargeX Diagnostics taskforce discussions, industry 1-on-1 meetings, technical standards, and OCPI’s evolution through versions (e.g., OCPI 2.1.1, 2.2, and 2.2.1), this report identifies these issues and suggests practical recommendations. These aim to improve interoperability, streamline operations, and prepare OCPI for future trends in the EV charging ecosystem.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2025

Recommendations for Minimum Required Diagnostics Information

The rapid growth of electrified transportation, including light- and medium-duty electric vehicles (EVs) as a mobility solution requires a reliable EV-charging infrastructure. To advance charging reliability, the ChargeX Consortium reports “Recommendations for Minimum Required Error Codes for Electric Vehicle Charging Infrastructure” and “Implementation Guide for Minimum Required Error Codes in Electric Vehicle Charging Infrastructure” provided recommendations for a set of minimum required error codes (MRECs), their functional and responsibility classifications, and a guide for their implementation, using Open Charge Point Protocol (OCPP) versions 1.6J4 and 2.0.1.5 These reports outline a recommended practice for consistent error reporting and interpretation, which is essential for communicating issues uniformly across the complex and diverse EV-charging ecosystem. However, MRECs are just one part of diagnosing issues; another critical part is obtaining enough information about the current state and performance of the various charging components to identify root causes for each of the error codes. This additional diagnostics data can be used by technicians or automated systems to understand the context around an issue, allowing for timely resolution, decreased maintenance costs, and increased charging reliability. During everyday operations, data are regularly collected and analyzed across the ecosystem. Although sharing of all that available data would be great for diagnostics, concerns on data ownership, privacy, and original equipment manufacturer (OEM) intellectual property pose a challenge. To overcome this obstacle, this report proposes a set of minimum required diagnostic information (MRDI) and recommends that the industry implement these uniformly across the North American EV charging ecosystem. MRDI provides a means to exchange only data deemed necessary for root cause determination.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Recommendations for Minimum Required Diagnostics Information for Electric Vehicle Charging Infrastructure

The rapid growth of electrified transportation, including light- and medium-duty electric vehicles (EVs) as a mobility solution requires a reliable EV charging infrastructure. To advance charging reliability, the ChargeX Consortium reports “Recommendations for Minimum Required Error Codes for Electric Vehicle Charging Infrastructure” and “Implementation Guide for Minimum Required Error Codes in Electric Vehicle Charging Infrastructure” have provided recommendations for a set of minimum required error codes (MRECs), their functional and responsibility classifications, and a guide for their implementation using OCPP versions 1.6J and 2.0.1. These reports outline a recommended practice for consistent error reporting and interpretation, which is essential for communicating issues uniformly across the complex and diverse EV charging ecosystem. However, MRECs are just one part of diagnosing issues, another critical part is obtaining enough information about the current state and performance of the various charging components to identify root causes for each of the error codes. This additional diagnostics data can be used by technicians or automated systems to understand the context around an issue, allowing for timely resolution, decreased maintenance costs, and increased charging reliability. During everyday operations, data is regularly collected and analyzed across the ecosystem. Although sharing of all that available data would be great for diagnostics, concerns on data ownership, privacy, and OEM intellectual property pose a challenge. To overcome this obstacle, this report proposes a set of Minimum Required Diagnostic Information (MRDI) and recommends that the industry implement these uniformly across the North American EV charging ecosystem. MRDI provides a means to exchange only data deemed necessary for root cause determination.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
NASA NTRS1985

Potential of CCDs for UV and X-ray plasma diagnostics

A program is under way to develop charge-coupled device (CCD) sensors for space-based X-ray astronomy imaging spectrometers. To date, laboratory line-emission spectra have been acquired throughout the range of 277 to 8000 eV (carbon through copper K-alpha emission) and CCD sensitivity has been demonstrated throughout the range of 1.1 through 8000 eV. Image resolution is excellent, limited almost entirely by the 15 micron pixel size. These results are presented and specialized techniques are described which permit such low energy response, high spectral resolution, and efficient charge collection. Finally, analysis is presented of one particular CCD characteristic which currently limits UV and X-ray performance: charge diffusion.

Janesick, J. R.↗
NASA NTRS1979

Trigger, an active release experiment that stimulated auroral particle precipitation and wave emissions

The experiment design, including a description of the diagnostic and chemical release payload, and the general results are given for an auroral process simulation experiment. A drastic increase of the field aligned charged particle flux was observed over the approximate energy range 10 eV to more than 300 keV, starting about 150 ms after the release and lasting about one second. The is evidence of a second particle burst, starting one second after the release and lasting for tens of seconds, and evidence for a periodic train of particle bursts occurring with a 7.7 second period from 40 to 130 seconds after the release. A transient electric field pulse of 200 mv/m appeared just before the particle flux increase started. Electrostatic wave emissions around 2 kHz, as well as a delayed perturbation of the E-region below the plasma cloud were also observed. Some of the particle observations are interpreted in terms of field aligned electrostatic acceleration a few hundred kilometers above the injected plasma cloud. It is suggested that the acceleration electric field was created by an instability driven by field aligned currents originating in the plasma cloud.

Holmgren, G.↗
NASA NTRS1996

High-Power Ion Thruster Technology

Performance data are presented for the NASA/Hughes 30-cm-diam 'common' thruster operated over the power range from 600 W to 4.6 kW. At the 4.6-kW power level, the thruster produces 172 mN of thrust at a specific impulse of just under 4000 s. Xenon pressure and temperature measurements are presented for a 6.4-mm-diam hollow cathode operated at emission currents ranging from 5 to 30 A and flow rates of 4 sccm and 8 sccm. Highly reproducible results show that the cathode temperature is a linear function of emission current, ranging from approx. 1000 C to 1150 C over this same current range. Laser-induced fluorescence (LIF) measurements obtained from a 30-cm-diam thruster are presented, suggesting that LIF could be a valuable diagnostic for real-time assessment of accelerator-arid erosion. Calibration results of laminar-thin-film (LTF) erosion badges with bulk molybdenum are presented for 300-eV xenon, krypton, and argon sputtering ions. Facility-pressure effects on the charge-exchange ion current collected by 8-cm-diam and 30-cm-diam thrusters operated on xenon propellant are presented to show that accel current is nearly independent of facility pressure at low pressures, but increases rapidly under high-background-pressure conditions.

Beattie, J. R.↗
DOE OSTI2025

Hydrogen from low-density polyethylene via nonthermal plasma: Effects of energy density and process parameters

Nonthermal plasma processes are promising for the modular valorization of plastic waste, especially into hydrogen and carbon materials, due to their high intensity, lack of reliance on catalysts or consumables, and suitability to be directly powered by electricity. We investigate the production of hydrogen from low-density polyethylene (LDPE) as a plastic waste model using streamer Dielectric Barrier Discharge (sDBD) plasma in nitrogen at atmospheric pressure. Here, we examine the effects of process energy density (energy input per unit of feedstock mass), feedstock mass, and plasma intensity (electric voltage) on plasma properties, hydrogen yield and energy efficiency via gas chromatography, optical emission spectroscopy, and electrical diagnostics, together with reactor-scale and nonlinear electric circuit modeling. The characteristic temperature of free electrons in the sDBD plasma is approximately 15000 K (1.3 eV), and that of gas species 10 times lower, demonstrating strong thermal non-equilibrium that can lead to molecular bond scission via charged species impact rather than direct heating. Experimental results show that higher energy density leads to greater hydrogen production and diminishing energy efficiency, and that higher plasma intensity and larger feedstock mass lead to greater hydrogen yield due to higher plasma temperatures and enhanced energy fluxes to the feedstock.

08 HYDROGEN↗
NASA NTRS2004

Ground-Based Simulation of Low-Earth Orbit Plasma Conditions: Plasma Generation and Characterization

A 16-cm diameter plasma source operated on argon is described that is capable of producing a plasma environment that closely simulates the low Earth orbit (LEO) conditions experienced by satellites in the altitude range between 300 to 500 km. The plasma source uses a transverse-field magnetic filter, and has been successful in producing low electron temperature plasmas that contain streaming ion populations. Both of these characteristics are important because the plasma in LEO is relatively cold (e.g., Te approx. 0.1 eV) and the ram energy of the ions due to the motion of the satellite relative to the LEO plasma is high (e.g., 7,800 m/s which corresponds to approx. 5 eV for O+ ions). Plasma source operational conditions of flow rate and discharge power are presented that allow the electron temperature to be adjusted over a range from 0.14 to 0.4 eV. The expanding plasma flow field downstream of the source contains both low-energy, charge-exchange ions and streaming ions with energies that are adjustable over a range from 4 eV to 6 eV. At low flow rates and low facility pressures, the streaming ion component of the ion population comprises over 90% of the total plasma density. In the work described herein, a large area retarding potential analyzer was used to measure both electron and ion energy distribution functions in the low density, expanding plasma produced downstream of the plasma source. The benefits of using this type of plasma diagnostic tool in easily perturbed, low-density plasma are identified, and techniques are also discussed that can be used to perform real-time measurements of electron temperature. Finally, recommendations are made that may enable lower electron temperatures to be produced while simultaneously decreasing the plasma source flow rate below 1 to 2 sccm.

Williams, John D.↗
NASA NTRS1981

Artificial particle and wave stimulation in the Trigger experiment

The Trigger experiment, designed to test the response of the auroral ionosphere to an impulsive release of a hot, dense plasma, and consisting of a sounding rocket payload (launched on February 11, 1977) divided into two parts, an instrumented diagnostic section and a cesium-doped high-explosive canister, is described. When the two sections were separated by about 1 km, the cesium high-explosive was ignited and the plasma around the payload was observed to increase briefly by a factor of 4 in density and a factor of 2 in temperature, upon which various particle and field phenomena occurred in rapid succession. A large increase in the field-aligned charged particle flux was observed over the approximate energy range of 10 eV to more than 300 keV, starting about 150 ms after the release and lasting about 1 second. A second particle burst started one second after the release and lasted for tens of seconds. A transient electric field pulse of 200 mV/m appeared just before the particle flux increase began.

Holmgren, G.↗
NASA NTRS1982

Studies of beam plasma interactions in a space simulation chamber using prototype Space Shuttle instruments

In March, 1981, electron beam experiments were conducted in a large space simulation chamber using equipment destined to be flown aboard NASA's Office of Space Science-1 pallet (OSS-1). Two major flight experiments were involved. They include the Vehicle Charging and Potential (VCAP) experiment and the Plasma Diagnostics Package (PDP). Apparatus connected with VCAP included a Fast Pulse Electron Gun (FPEG), and a Charge and Current Probe (CCP). A preliminary view is provided of the results obtained when the electron emissions were held steady over relatively long periods of time such that steady state conditions could be obtained with respect to the electron beam interaction with the neutral gases and plasma of the vacuum chamber. Of particular interest was the plasma instability feature known as the Beam Plasma Discharge. For the present experiments the FPEG was used in a dc mode with a range of currents of 2 to 80 mA at a beam energy of 970 eV. Attention is given to the emissions of VLF and HF noise associated with the dc beam.

Banks, P. M.↗
DOE OSTI2026

Toward the origins of binding energy shifts and “satellites” formation during plasma-XPS measurements

In-plasma x-ray photoelectron spectroscopy (plasma-XPS) emerges as a powerful platform for real-time, in situ chemical analysis under conditions relevant to semiconductor processing and other plasma-enabled technologies. This study investigates the origins of binding energy (BE) shifts and the formation of “satellite” peaks observed during plasma-XPS measurements across conductive, dielectric, and gas-phase systems. Using a standard laboratory-based ambient pressure XPS apparatus coupled with an alternating current (AC)-driven capacitively coupled plasma source, we demonstrate that metastable surface species, such as transient Au oxides, can be detected during plasma exposure, revealing chemical states that are hardly accessible using conventional ultrahigh vacuum (UHV) XPS. In dielectric samples (e.g., undoped diamond, sapphire), we observe pressure- and plasma-type-dependent BE shifts of more than 50 eV, attributed to x-ray-induced and plasma-mediated surface charging. These shifts are mitigated at higher pressures/plasmas or in electronegative plasmas (e.g., O 2 ), the latter due to enhanced charge compensation mechanisms involving slow negative ions. For gas-phase species, AC-plasma excitation leads to spectral broadening and the emergence of “satellite” peaks with energy separations of a few electron volts, linked to oscillating local plasma potentials in the probing volume. Furthermore, these findings highlight the complex and important interplay between plasma parameters, surface charging, and local electric fields in shaping XPS spectra. Overall, plasma-XPS emerges as a critical metrological tool for probing transient surface chemistry, with implications for semiconductor processing, material synthesis, and plasma diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

High Current Hollow Cathode Plasma Plume Measurements

Plasma plume measurements are reported for a hollow cathode assembly (HCA) oper-ated at discharge currents of 50, 70, and 100 A at xenon ow rates between 19 - 46 sccm.The HCA was centrally mounted in the annulus of the NASA-300MS Hall Thruster andwas operated in the spot and plume modes with additional data taken with an appliedmagnetic eld. Langmuir probes, retarding potential analyzers, and optical emission spec-troscopy were employed to measure plasma properties near the orice of the HCA and toassess the charge state of the near-eld plasma. Electron temperatures (2-6 eV) and plasmapotentials are consistent with probe-measured values in previous investigations. Operationwith an applied-eld yields higher discharge voltages, increased Xe III production, andincreased signals from the 833.5 nm C I line. While operating in plume mode and with anapplied eld, ion energy distribution measurements yield ions with energies signicantlyexceeding the applied discharge voltage. These ndings are correlated with high-frequencyoscillations associated with each mode.

Plasma diagnostics↗
NASA NTRS2004

Removing Spectral Diagnostics of Galactic and Stellar X-Ray Emission from Charged Exchange Recombination

Our research uses the electron beam ion trap (EBIT) at the Lawrence Livermore National Laboratory to study X-ray emission from the charge exchange (CX) of highly charged ions with neutral gases. The resulting data help to fill a void in existing experimental and theoretical understanding of this atomic physics process, and are needed to explain all or part of the observed X-ray emission from the soft X-ray background, stellar winds, the Galactic Center and Galactic Ridge, supernova ejecta, and photoionized nebulae. Appreciation of the astrophysical relevance of our work continues to grow with the publication of roughly a dozen papers in the past four years describing Chandra and XMM observations of geocoronal and heliospheric CX emission, the temporal variation of such emission and correlation with X-ray emission enhancements observed by ROSAT, the theoretical spatial distribution of that emission, and CX emission around other stars. A similar number of papers were also published during that time describing CX emission from planets and comets. We expect that the launch of ASTRSE2, with its second-generation XRS microcalo- (with 6-eV resolution), will reveal even more clearly the contributions of CX to astrophysical emission. In our EBIT work we collected CX spectra from such ions as H-like and He-like Ne, Ar, and Fe. Our early measurements were made with a high-purity Ge detector, but during the second year we began operation of the first-generation XRS microcalorimeter (a twin of the XRS on ASTRO-E) and greatly improved the resolution of our measurements from roughly 150 eV (FWHM) with the Ge detectors to 10 eV with the XRS. We found that saturation of the XRS counting apparatus, which we described in our proposal as a potential concern, is not a problem for studying CX. During the course of our research, we expanded the number of injection gases permitted by the LLNL safety team, purchased and eventually operated an atomic H source, and clearly demonstrated the feasibility of our longer-range plan. For example, we successfully injected He into EBIT (not a small feat because of the difficulty of maintaining a good vacuum with He and avoiding electrical breakdown) to collect a H-like oxygen CX spectrum. The highest energy CX spectrum recorded with the XRS to date is that of the Ar K-shell emission. These measurements provided the first observation of the relative intensity ratios of resolved He-like singlet and triplet n=2->1 lines. We also carried out measurements of He-like Ne as a function of collision energy (i.e., ion temperature). Significant differences in the resulting x-ray spectra were noted. In all cases, the intensity of high-n H-like Lyman lines is significantly higher than current theoretical CX models predict.

Wargelin, Brad↗
NASA NTRS2007

The Spatial Variation of Polar Rain Electrons and its Cause

It is generally accepted that field aligned electrons in the solar wind can follow field lines connected to Earth and precipitate in the polar ionosphere where they are known as polar rain. Few-hundred eV, field-aligned electrons of the solar wind "strahl" carry the interplanetary heat flux moving out from the sun and these electrons precipitate in either the northern or southern hemisphere depending on the magnetic field direction. These electrons produce enhanced polar rain in one hemisphere or the other although weaker polar rain is usually produced in the opposite hemisphere by whatever electrons are moving in the opposite direction. Although much evidence exists for this simple free entry mechanism, it has also long been known that there are spatial variations in the energies and intensities of the precipitating electrons. The present work compares electron distribution functions measured by the ACE spacecraft in the solar wind with those measured by the DMSP spacecraft at 800 km altitude over the polar cap. It is found that shifting the DMSP distribution functions in energy by amounts ranging from 10's to a few hundred eV produces quite good agreement with simultaneous ACE measurements. Over most of the polar cap this DMSP energy shift must be positive to achieve this agreement, suggesting the electrons have been decelerated by a field aligned potential as they move from the solar wind to low altitudes. The largest shifts occur on the nightside and on the dawn or dusk side, with the latter depending on the plasma convection pattern which is controlled by the orientation of the IMF. Nearer the cusp the shift is smaller or even negative. Since more massive tailward flowing magnetosheath ions are unable io follow the field lines into the magnetotail like the electrons, a field aligned potential is expected to develop to exclude low energy electrons and prevent an excessive charge imbalance. Such a potential would also produce the deceleration of those electrons that reach low altitudes. This improved understanding of polar rain should increase the utility of polar rain measurements as a diagnostic of the magnetosphere magnetic field configuration.

Fairfield, D. H.↗
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)

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