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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Effect of Initial Structure on Performance of High-Entropy Oxide Anodes for Li-Ion Batteries

Two different high-entropy oxide materials were synthesized and studied as Li-ion battery anodes. The two materials have the same active metal constituents but different inactive elements which result in different initial crystalline structures: rock salt for (MgFeCoNiZn)O and spinel for (TiFeCoNiZn)3O4. Local structural studies of the metal elements in these two materials over extended electrochemical cycling reveal that the redox processes responsible for the electrode capacity are independent of the initial crystallographic structure and that the capacity is solely dependent on the initial random distribution of the metal atoms and the amount of active metals in the starting material.

25 ENERGY STORAGE↗
DOE OSTI2024

Effect of boron concentration on local structure and spontaneous polarization in AlBN thin films

The discovery of ferroelectricity in polar wurtzite-based ternary materials, such as Al 1–x B x N, has attracted attention due to their compatibility with complementary metal–oxide–semiconductor processes and potential use in integrated non-volatile memory devices. However, the origin of ferroelectricity and the fundamental control of the polarization switching in these materials are still under intensive investigation but appear to be related to local disorder induced from the alloying. In this work, we report the effect of boron alloying on the local structure of Al 1–x B x N films deposited by magnetron sputtering. Our results reveal a diminished crystalline order as a function of boron concentration, accompanied by a reduction in the spontaneous polarization. The film disorder is primarily associated with the dissimilar bond lengths between Al–N and B–N and the formation of threading dislocations induced by B incorporation in the structure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Altering Linear Scaling Relationships on Metal Catalysts via Ligand–Adsorbate Hydrogen Bonding

Linear scaling relationships for adsorption energies of related molecules provide a simple tool for the prediction of catalytic properties and also reveal inherent constraints in heterogeneous catalyst design. In an effort to predict materials that preferentially stabilize intermediates capable of forming hydrogen bonds (H-bonds) and thus reduce these constraints, scaling relations for thiolate-coated fcc (111) surfaces were developed. Here, we demonstrate how ligand–adsorbate H-bonds lead to the stabilization of certain adsorbates and how this affects the linear scaling of adsorption energies for similarly bound intermediates. For H-bonds that occur remote from the surface, ligand–adsorbate H-bond strength is independent of metal composition and instead depends only on the acidities of the H-bond-forming functional groups. As the distance of H-bond-accepting groups from the surface decreases and interactions with the metal strengthen, the effect of surface composition on H-bond strength increases while additional factors, such as conformational changes and steric hinderance, can offset the stabilizing effect of the ligands. In this work, these competing factors may influence both the slope and y-intercept of adsorption strength scaling. These findings aid the rational design of enhanced catalytic materials by enabling the screening of ligand- or spectator-modified materials that do not conform to the linear scaling relations of bare metal surfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Pressure-induced spin crossover in a Fe 78 Si 9 B 13 metallic glass

The pressure effect on structures and properties of a Fe 78 Si 9 B 13 metallic glass was investigated by in situ high-pressure synchrotron Fe Kβ x-ray emission spectroscopy and x-ray diffraction, and electrical resistivity measurements up to ~51 GPa. The study reveals a reversible and continuous pressure-induced high- to low-spin crossover of Fe atoms in an amorphous structure. The changes of the local spin moment can be scaled to match its average atomic distance shrinkage very well during compression. The crossover of electronic spin states in the Fe 78 Si 9 B 13 metallic glass resembles that of typical crystalline Fe-bearing materials but without a sharp atomic volume collapse and an abrupt electrical resistivity jump. Furthermore, these findings could help guide applications of Fe-based metallic glasses as a soft ferromagnetic material at extreme conditions and also improve our understanding of magnetism and coupling of its changes with disordered atomic structures and other properties in metallic glasses.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Heterometallic Actinide-Containing Photoresponsive Metal-Organic Frameworks: Dynamic and Static Tuning of Electronic Properties

Acquiring fundamental knowledge of properties of actinide-based materials is a necessary step to create new possibilities for addressing the current challenges in the nuclear energy and nuclear waste sectors. Here in this report, we established a photophysics–electronics correlation for actinide-containing metal-organic frameworks (An-MOFs) as a function of excitation wavelength, for the first time. A stepwise approach for dynamically modulating electronic properties was applied for the first time towards actinide-based heterometallic MOFs through integration of photochromic linkers. Optical cycling, modeling of density of states near the Fermi edge, conductivity measurements, and photoisomerization kinetics were employed to shed light on the process of tailoring optoelectronic properties of An-MOFs. Furthermore, the first photochromic MOF-based field-effect transistor, in which the field-effect response could be changed through light exposure, was constructed. As a demonstration, the change in current upon light exposure was sufficient to operate a two-LED fail-safe indicator circuit.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Examples of X-Ray Characterization Techniques in Energy Storage Research

Lithium-ion batteries have revolutionized the portable electronics and transportation sectors. Their performance is often critically dependent on the crystal structures of the anode and cathode electrode materials, which must enable the transport and reversible storage of lithium ions into and out of the lattice. Because lithium is a low-Z element, characterization of materials for lithium-ion batteries can be particularly challenging. Regardless, X-ray techniques enable analysis of material structures to better understand how battery materials perform and degrade, particularly when combined with other materials characterization and electrochemical characterization techniques. While X-ray techniques are most often used in battery research for phase identification of crystal structures, X-ray characterization techniques are also used for a wide variety of other purposes. I will discuss several examples from my research with various collaborators on several projects that highlight the impact that X-ray characterization techniques can have on battery research. The first example will focus on low-temperature microwave-assisted solvothermal synthesis of vanadium-doped LiFePO4 cathode materials for lithium-ion batteries. (1,2) Through a combination of electrochemical and materials characterization, we determined that low temperature synthesis resulted in metastable phases that enabled incorporation of higher dopant levels than resulting from high-temperature synthesis of thermodynamically stable phases. Rietveld refinement of X-ray diffraction data enabled understanding of how lattice parameters changed with doping levels and synthesis temperature. X-ray absorption near edge spectroscopy enabled understanding of the vanadium and iron oxidation states to confirm how vacancies in the structure caused by doping were charge compensated. This was important to understand because the literature suggests doping can improve LiFePO4 electrical conductivity, which improves battery charge and discharge rates. The second example will focus on understanding residual strain in lithium metal anodes. Lithium-ion batteries typically use graphite anodes, but the charge-storage capacity can be theoretically improved ~10x by using lithium metal as the anode material instead. However, lithium anodes suffer from growth of high-aspect-ratio features, such as dendrites, that can pierce nanoporous polymer separators and lead to short circuits and fires. External pressure is commonly applied to cells to enable better morphological control. We hypothesized that applied pressure may promote strain and possibly work hardening during electrochemical cycling, which motivated us to look for evidence of residual strain in lithium metal cycled under applied pressure using X-ray diffraction and sin2(..psi..) analysis. We found that lithium electrodeposited under high pressure exhibited in-plane compressive strain and that that lithium electrodeposited under low pressure did not. (3) The residual strain that accompanies electrodeposition under high pressure may lead to work hardening, which may explain how a soft metal like lithium can puncture separators and why higher pressure does not always decrease short circuits. (4-6) References: 1) Harrison, K. L.; Manthiram, A. Microwave-Assisted Solvothermal Synthesis and Characterization of Metastable LiFe1- x (VO) x PO4 Cathodes. Inorganic chemistry 2011, 50(8), 3613-3620. 2) Harrison, K. L.; Bridges, C. A.; Paranthaman, M. P.; Segre, C. U.; Katsoudas, J.; Maroni, V. A.; Idrobo, J. C.; Goodenough, J. B.; Manthiram, A. Temperature Dependence of Aliovalent-Vanadium Doping in LiFePO4 Cathodes. Chemistry of Materials 2013, 25(5), 768-781. 3) Rodriguez, M. A.; Harrison, K. L.; Goriparti, S.; Griego, J. J.; Boyce, B. L.; Perdue, B. R. Use of a Be-Dome Holder for Texture and Strain Characterization of Li Metal Thin Films via Sin2 (..psi..) Methodology. Powder Diffraction 2020, 35(2), 89-97. 4) Jungjohann, K. L.; Gannon, R. N.; Goriparti, S.; Randolph, S. J.; Merrill, L. C.; Johnson, D. C.; Zavadil, K. R.; Harris, S. J.; Harrison, K. L. Cryogenic Laser Ablation Reveals Short-Circuit Mechanism in Lithium Metal Batteries. ACS Energy Letters 2021, 6(6), 2138-2144. 5) Harrison, K. L.; Merrill, L. C.; Long, D. M.; Randolph, S. J.; Goriparti, S.; Christian, J.; Warren, B.; Roberts, S. A.; Harris, S. J.; Perry, D. L. Cryogenic Electron Microscopy Reveals That Applied Pressure Promotes Short Circuits in Li Batteries. Iscience 2021, 24(12). 6) Harrison, K. L.; Goriparti, S.; Merrill, L. C.; Long, D. M.; Warren, B.; Roberts, S. A.; Perdue, B. R.; Casias, Z.; Cuillier, P.; Boyce, B. L. Effects of Applied Interfacial Pressure on Li-Metal Cycling Performance and Morphology in 4 M LiFSI in DME. ACS Applied Materials & Interfaces 2021, 13(27), 31668-31679.

batteries↗
DOE OSTI2022

Infrared nanospectroscopy characterization of metal oxide photoresists

Implementation of extreme ultraviolet (EUV) lithography in high-volume semiconductor manufacturing requires a reliable and scalable EUV resist platform. A mechanistic understanding of the pros and cons of different EUV resist materials is critically important. However, most material characterization methods with nanometer resolution use an x-ray photon or electron beam as the probe, which often cause damage to the photoresist film during measurement. Here, we illustrated the use of non-destructive infrared nanospectroscopy [or nano-Fourier-Transform infrared spectroscopy (nano-FTIR)] to obtain spatially resolved composition information in patterned photoresist films. Further, clear evidence of exposure-induced chemical modification was observed at a spatial resolution down to 40 nm, well below the diffraction limit of infrared light. With improvements, such a nano-FTIR technique with nanoscale spatial resolution, chemical sensitivity, and minimal radiation damage can be a promising candidate for the fundamental study of material properties relevant to EUV lithography.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ingeniously enhanced ferromagnetism in chemically-reduced 2D Ti 3 C 2 T X MXene

Chemical reduction is a facile and cost-effective technique for the modulation of the physical and chemical properties of nanomaterials. In this work, we demonstrate an enhancement of the magnetic behavior of Ti 3 C 2 T x MXene after its chemical reduction via l-ascorbic acid treatment. Small ferromagnetic loops have been observed below 50 K for Ti 3 C 2 T x prepared by hydrofluoric acid (HF) etching of Al layers from Ti 3 AlC 2 . Such a ferromagnetic ordering of spins was significantly enhanced via a chemical reduction of Ti 3 C 2 T x with l-ascorbic acid. Ferromagnetic hysteresis loops were observed for reduced Ti 3 C 2 T x (r-Ti 3 C 2 T x ) up to 150 K indicating a significant upshift of the paramagnetic to the ferromagnetic transition temperature, pushing towards room temperature. The enhancement of ferromagnetism and upshift of the ferromagnetic transition temperature could be attributed to the localized unpaired electron in Ti-3d orbital of the r-Ti 3 C 2 T x crystal and increase in the number of unsaturated Ti atoms upon l-ascorbic acid treatment. Chemical reduction via l-ascorbic acid treatment shows a promising pathway towards the modulation and enhancement of magnetism in various MXene materials for the development of 2D metallic soft ferromagnets and spintronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Unconventional polaronic ground state in superconducting LiTi 2 O 4

Geometrically frustrated lattices can display a range of correlated phenomena, ranging from spin frustration and charge order to dispersionless flat bands due to quantum interference. One particularly compelling family of such materials is the half-valence spinel LiB 2 O 4 materials. On the B-site frustrated pyrochlore sublattice, the interplay of correlated metallic behavior and charge frustration leads to a superconducting state in LiTi 2 O 4 and heavy fermion behavior in LiV 2 O 4 . To date, however, LiTi 2 O 4 has primarily been understood as a conventional BCS superconductor despite a lattice structure that could host more exotic ground states. Here, we present a multimodal investigation of LiTi 2 O 4 , combining ARPES, RIXS, proximate magnetic probes, and ab-initio many-body theoretical calculations. Our data reveals a novel mobile polaronic ground state with spectroscopic signatures that underlie co-dominant electron-phonon coupling and electron-electron correlations also found in the lightly doped cuprates. The cooperation between the two interaction scales distinguishes LiTi 2 O 4 from other superconducting titanates, suggesting an unconventional origin to superconductivity in LiTi 2 O 4 . Our work deepens our understanding of the rare interplay of electron-electron correlations and electron-phonon coupling in unconventional superconducting systems. In particular, our work identifies the geometrically frustrated, mixed-valence spinel family as an under-explored platform for discovering unconventional, correlated ground states.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nanoscale Mg–B via Surfactant Ball Milling of MgB 2 : Morphology, Composition, and Improved Hydrogen Storage Properties

Metal borides have attracted the attention of researchers due to their useful physical properties and unique ability to form high hydrogen-capacity metal borohydrides. We demonstrate improved hydrogen storage properties of a nanoscale Mg–B material made by surfactant ball milling MgB 2 in a mixture of heptane, oleic acid, and oleylamine. Transmission electron microscopy data show that Mg–B nanoplatelets are produced with sizes ranging from 5 to 50 nm, which agglomerate upon ethanol washing to produce an agglomerated nanoscale Mg–B material of micron-sized particles with some surfactant still remaining. X-ray diffraction measurements reveal a two-component material where 32% of the solid is a strained crystalline solid maintaining the hexagonal structure with the remainder being amorphous. Fourier transform infrared shows that the oleate binds in a “bridge-bonding” fashion preferentially to magnesium rather than boron, which is confirmed by density functional theory calculations. The Mg–B nanoscale material is deficient in boron relative to bulk MgB 2 with a Mg–B ratio of ~1:0.75. The nanoscale MgB 0.75 material has a disrupted B–B ring network as indicated by X-ray absorption measurements. Hydrogenation experiments at 700 bar and 280 °C show that it partially hydrogenates at temperatures 100 °C below the threshold for bulk MgB 2 hydrogenation. In addition, upon heating to 200 °C, the H–H bond-breaking ability increases ~10-fold according to hydrogen–deuterium exchange experiments due to desorption of oleate at the surface. This behavior would make the nanoscale Mg–B material useful as an additive where rapid H–H bond breaking is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Noncollinear spin structure with weak ferromagnetism in NbMnP

NbMnP is a metallic material, which consists of the zigzag chains of Mn moments along the b axis. The magnetic susceptibility as well as the resistivity shows an anomaly at 233 K, which indicates an antiferromagnetic phase transition. Our neutron powder diffraction experiment reveals that the magnetic structure is a Q=0 structure and noncollinear with an easy plane anisotropy perpendicular to the b axis, and the a- and c-axis magnetic components align antiferromagnetically and ferromagnetically along the zigzag chain direction, respectively. The ordered moment is 1.2μ B , which is reduced probably due to the itineracy of the Mn moments. A localized picture model suggests that the Q=0 magnetic structure is formed by the frustration among several exchange couplings. A weak ferromagnetic component is also present in the antiferromagnetic phase, which is considered to be caused by a Dzyaloshinskii-Moriya interaction.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Surface treatment for lithium battery electrode materials

Electrode materials for electrochemical cells and batteries and methods of producing such materials are disclosed herein. A method of preparing an active lithium metal oxide material suitable for use in an electrode for a lithium electrochemical cell comprises the steps of: (a) contacting the lithium metal oxide material with an aqueous acidic solution containing one or more metal cations; and (b) heating the so-contacted lithium metal oxide from step (a) to dryness at a temperature below 200° C. The metal cations in the aqueous acidic solution comprise one or more metal cations selected from the group consisting of an alkaline earth metal ion, a transition metal ion, and a main group metal ion.

25 ENERGY STORAGE↗
DOE OSTI2022

Lithium battery electrodes

Electrode materials for electrochemical cells and batteries and methods of producing such materials are disclosed herein. The electrode materials comprise an active lithium metal oxide material prepared by: (a) contacting the lithium metal oxide material with an aqueous acidic solution containing one or more metal cations; and (b) heating the so-contacted lithium metal oxide from step (a) to dryness at a temperature below 200° C. The metal cations in the aqueous acidic solution comprise one or more metal cations selected from the group consisting of an alkaline earth metal ion, a transition metal ion, and a main group metal ion.

25 ENERGY STORAGE↗
DOE OSTI2021

Computational Modeling Demonstrates the Joint Clearance Effect on the Tensile Strength of Solder Joints.

Soldered joints can be made with a wide range of base materials and filler metals that allow the assembly to meet its performance and reliability requirements. Structural solder joints have, as their foremost requirement, to provide mechanical attachment between base material structures. The joint is typically subjected to one, or a combination of, three loading configurations: (a) tensile or compressive force, (b) shear force, or (c) peel force. Solder filler metals and in particular, the so-called “soft solders” based on tin (Sn), lead (Pb), and indium (In), generally have a bulk strength that is less than that of the base materials. Finally, deformation occurs largely in the solder when the joint is subjected to an applied force.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Surface Modified Fly Ash for Value Added Products (SuMo Fly Ash)

The objective of this project is to develop a technology to encapsulate coal fly ash particles in sulfurized vegetable oil, enhancing physical and mechanical properties of the fly ash as a filler material when applied in commercial products. This project significantly advances the knowledge base and technology for synthesizing coated fly ash particles for application in different polymer matrices to increase cross-linking, compatibility, air-entrainment and to decrease the leaching potential of metals of concern. Specifically, the project focuses on (a) collection, and characterization of fly ash material from coal power plants; (b) development of Sulfurized Vegetable Oil (SVO) modified (SuMo) fly ash and their detailed characterization; (c) evaluation of the mechanical properties of the SuMo fly ash incorporated plastic and rubber composites for potential replacement of CaCO 3 or carbon black as filler materials with SuMo fly ash in plastic and rubber composites; (d) leaching potential of SuMo fly ash and SuMo fly ash-incorporated plastic and rubber composites to determine the rate of release of trace metals. The major findings of this project are: i) Sulfurized Vegetable Oil coated fly ash (SuMo fly ash) was successfully prepared with a particle size of ≤ 45 micron which exhibited hydrophobicity of contact angle > 90°; ii) the coating reduces leaching of metals (e.g., B, Cr) from fly ash when exposed to water; iii) incorporation of SuMo fly ash increases thermal stability and yield strength of plastics; iv) SuMo coating helps disperse fly ash particles into cured rubbers, natural rubber; (v) SuMo fly ash-incorporated plastic/cured rubbers compounds protects against leaching of toxic elements.

20 FOSSIL-FUELED POWER PLANTS↗
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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