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108 records · Page 6

Visualizing Crystallization Dynamics and Transformation Pathways of Disordered Rocksalt Oxides During Thermally Activated Sol–Gel Synthesis

Sol–gel synthesis is a wet-chemical processing route for fabricating functional materials with control over composition and microstructure at relatively low temperatures compared to conventional solid-state synthesis. While sol–gel process initiates with intermixed molecular precursors, the early-stage nucleation pathways are insufficiently understood. Here, in this study, the chemical and structural transformation of ion disordered rocksalt (DRX) Li 1.2 Mn 0.4 Ti 0.4 O 2 (LMTO), a promising cathode material for lithium batteries, is studied by multiscale characterizations. In situ heating transmission electron microscopy (TEM) using a liquid cell visualizes and identifies crystallization pathways at the nanoscale. While some regions follow a classical multi-step transition through thermodynamically stable intermediates, others exhibit a kinetic shortcut via a localized amorphous matrix to directly form the DRX structure. Macroscale Fourier transform infrared spectroscopy corroborates the findings and reveals that transition metal ions are more strongly incorporated into the acetate-coordinated network than lithium. Although in situ heating TEM captures diverse local transformation pathways, in situ synchrotron X-ray diffraction indicates that the macroscopic transformation proceeds predominantly through spinel LMTO and lithium titanates toward DRX-LMTO. The findings uncover the spatiotemporal chemical and structural transformations in sol–gel derived DRX-LMTO materials, and call for fine-tuning of such sol–gel chemistries to manipulate the crystallization pathways and achieve target material homogeneity more efficiently.

cathode material↗

All hard X-ray transient grating spectroscopy

Optical-domain transient grating (TG) spectroscopy is the ideal tool to investigate transport phenomena in gases, liquids and solids, but it is limited to typically micron-size grating periods. Extreme-Ultraviolet TG has represented a major leap forward to access the mesoscopic scales. Hard X-ray TGs open access in principle to the nanoscale. Hard X-ray TGs were recently generated using the Talbot effect and probed by optical pulses, but these hinder exploiting the advantages of the nanoscale gratings. Here, we present an all-X-ray TG study, in which few-femtosecond hard X-ray pulses are used both for excitation and probing. Our experiment was performed on an amorphous film of an FeGd alloy and on a thin silicon single crystal. The results show a manifestation of the TG induced by the X-ray pump and probe pulses in the form of Talbot carpets, as well as temporal evolution of the grating in crystalline silicon showing coherent optical phonons. Ultrafast all-X-ray TG spectroscopy has the potential to study fundamental excitations with femtosecond time resolution and nanometer spatial sensitivity.

Ferrari, Eugenio [Deutsches Elektronen-Synchrotron↗

Time-Resolved X-ray Emission Spectroscopy and Resonant Inelastic X-ray Scattering Spectroscopy of Laser Irradiated Carbon

The existence of liquid carbon as an intermediate phase preceding the formation of novel carbon materials has been a point of contention for several decades. Experimental observation of such a liquid state requires nonthermal melting of solid carbon materials at various laser fluences and pulse properties. Reflectivity experiments performed in the mid-1980s reached opposing conclusions regarding the metallic or insulating properties of the purported liquid state. Time-resolved X-ray absorption studies showed shortening of C–C bonds and increasing diffraction densities, thought to evidence a liquid or glassy carbon state, respectively. Nevertheless, none of these experiments provided information on the electronic structure of the proposed liquid state. Herein, we report the results of time-resolved resonant inelastic X-ray scattering (RIXS) and time-resolved X-ray emission spectroscopy (XES) studies on amorphous carbon (a-C) and ultrananocrystalline diamond (UNCD) as a function of delay time between the irradiating pulse and X-ray probe. For both a-C and UNCD, we attribute decreases in RIXS or XES signals to transition blocking, relaxation, and finally, ablation. Increased signal at 20 ps following the irradiation of the UNCD is attributed to the probable formation of nanoscale structures in the ablation plume. Further, differences in the amount of signal observed between a-C and UNCD are explained by the difference in sample thickness and, specifically, incomplete melting of the UNCD film. Comparisons to spectral simulations based on MD trajectories at extreme conditions indicate that the carbon state in our experiments is crystalline. Normal mode analysis confirmed that symmetrical bending or stretching of the C–C bonds in the diamond lattice results in XES spectra with small intensity differences. Overall, we observed no evidence of melting to a liquid state, as determined by the lack of changes in the spectral properties for up to 100 ps delays following the melting pulses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quasicrystal stability and nucleation kinetics from density functional theory

The aperiodic order of quasicrystals bridges the amorphous and crystalline regime, so it has remained unclear whether quasicrystals are metastable or stable phases of matter. Density functional theory is often used to evaluate thermodynamic stability, but quasicrystals are long-range aperiodic and their energies cannot be calculated using conventional ab initio methods. Here, in this work, we perform first-principles calculations on quasicrystal nanoparticles of increasing size, from which we can directly extrapolate their bulk and surface energies. Using this technique, we determine with high confidence that the icosahedral quasicrystals ScZn 7.33 and YbCd 5.7 are ground-state phases, thus revealing that translational symmetry is not a necessary condition for the zero-temperature stability of inorganic solids. Although we found the ScZn 7.33 quasicrystal to be thermodynamically stable, we show on a mixed thermodynamic and kinetic phase diagram that its solidification from the melt is limited by nucleation, which illustrates why even stable materials may be kinetically challenging to grow. Our techniques broadly open the door to first-principles investigations into the structure–bonding–stability relationships of aperiodic materials.

density functional theory↗

Exploitation of Pore Structure for Increased CO 2 Selectivity in Type 3 Porous Liquids

CO 2 capture requires materials with high adsorption selectivity and an industrial ease of implementation. To address these needs, a new class of porous materials was recently developed that combines the fluidity of solvents with the porosity of solids. Type 3 porous liquids (PLs) composed of solvents and metal–organic frameworks (MOFs) offer a promising alternative to current liquid carbon capture methods due to the inherent tunability of the nanoporous MOFs. However, the effects of MOF structural features and solvent properties on CO 2 –MOF interactions within PLs are not well understood. Herein experimental and computational data of CO 2 gas adsorption isotherms were used to elucidate both solvent and pore structure influences on ZIF-based PLs. The roles of the pore structure including solvent size exclusion, structural environment, and MOF porosity on PL CO 2 uptake were examined. A comparison of the pore structure and pore aperture was performed using ZIF-8, ZIF-L, and amorphous-ZIF-8. Adsorption experiments here have verified our previously proposed solvent size design principle for ZIF-based PLs (1.8× ZIF pore aperture). Furthermore, the CO 2 adsorption isotherms of the ZIF-based PLs indicated that judicious selection of the pore environment allows for an increase in CO 2 selectivity greater than expected from the individual PL components or their combination. This nonlinear increase in the CO 2 selectivity is an emergent behavior resulting from the complex mixture of components specific to the ZIF-L + 2'-hydroxyacetophenone-based PL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of pitch carbon coating properties affecting the electrochemical behavior of silicon nanoparticle lithium-ion battery anodes

Silicon is an exciting material for next-generation lithium-ion battery anodes, due to its high theoretical capacity and availability, but its widespread implementation has been limited by extensive volume changes during cycling that causes mechanical damage and limits cycle life. One approach to mitigating these deleterious effects while still maintaining silicon's benefits is the addition of a pitch carbon coating to nanometer-sized silicon particles. Here, in this study, we present characterization of pitch-coated silicon electrodes without annealing and annealed at 700 °C and 1000 °C to determine the optimum temperature treatment, as well as pitch-only and silicon-only electrodes with and without annealing to elucidate the impacts of each component on early electrochemical behavior. Using Fourier transform infrared and Raman spectroscopies, atomic force and scanning spreading resistance microscopy, and electrochemical analysis, we find 700 °C to be the optimal annealing temperature, as amorphous carbon is created, which improves conductivity prior to cycling and facilitates ion storage during cycling that increases capacity. We also present in situ Raman spectroscopy data demonstrating the heterogeneous aging that occurs across the electrode surface during cycling.

25 ENERGY STORAGE↗

Diffraction Measurement of Reaction Products in Shock Compressed TATB on the NIF

The shock-induced reaction of high explosives to gaseous and solid reaction products is a rapid, complex process. Understanding solid reaction product structure and formation kinetics is essential in determining the high-pressure equation of state of these multicomponent systems. We use the National Ignition Facility (NIF) to shock compress ~500-µm thick pressed powder high-explosive TATB samples to 70-135 GPa and collect in situ structural data on detonation byproducts using the TARDIS X-ray diffraction diagnostic. Velocimetry is used to record the transmitted compression wave profile, which is well described by Cheetah hydrocode simulations coupled with a reactive flow model, providing strong evidence of reaction in the TATB sample. While an unambiguous determination of the product phases was not possible owing to the low signal-to-noise quality of the diffraction signal, X-ray diffraction data of the product phases formed within the first 50 ns of the reaction is most consistent with a mixture of amorphous products and crystalline hexagonal diamond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Recovery of value-added compounds through fast pyrolysis of apple pomace hydrochar

The environmental challenges associated with food production can be addressed via the thermochemical upcycling of agro-industrial biomass. Two such methods, hydrothermal carbonization (HTC) and pyrolysis, can be coupled to first reduce the water content of wet biomass wastes by producing a hydrochar (HC) via HTC and then a bio-oil via pyrolysis of the HC. However, HTC of biomass results in the formation of secondary char (SC), an amorphous tar-like mixture resulting from organic compounds released into the aqueous phase that adsorb, recondense and polymerize on the parent biomass. This study investigated how HTC temperature impacts the formation of SC from apple pomace and the SC’s subsequent impact on fast pyrolysis products. HCs were produced at temperatures of 175°C, 200°C, and 250°C. Lower HTC temperatures favor the formation of biorefinery platform chemicals such as 5-hydroxymethylfurfural and levulinic acid, while higher temperatures result in increased lignin degradation products (i.e., phenolics). HCs were subjected to fast pyrolysis before and after SC extraction in two analytical pyrolysis instruments. Fast pyrolysis of HC produced compounds similar to those found in SC, but with variations in CO and CO 2 emissions. In conclusion, the combination of SC extraction and fast pyrolysis demonstrates promise for recovering value-added compounds from agro-industrial waste biomass while retaining a solid char for fuel and carbon management.

09 BIOMASS FUELS↗

Porous and Amorphous Mn x Mo 3 S 13 Chalcogel Electrode for High-Capacity Conversion-Based Lithium-Ion Batteries

While Li-ion batteries (LIBs) are a leading energy storage technology, their energy densities are limited by the low capacity of conventional intercalation cathodes, driving interest in high energy-density Li–S batteries that make use of conversion chemistry. Achieving high capacity, reversibility, and cycle stability, and controlling volume changes in conversion batteries during the charge–discharge process, however, remains challenging. Here, in this study, we present a porous, amorphous, sulfide-based Mn x Mo 3 S 13 chalcogel, which concurrently offers high capacity and cycle stability. The solution-processable room temperature synthesized Mn x Mo 3 S 13 (x = 0.25) chalcogel exhibits a local structure that resembles the Mo 3 S 13 cluster with Mn 2+ distributed across the Mo 3 S 13 matrix, as determined by synchrotron X-ray pair distribution function (PDF) and extended X-ray absorption fine structure (EXAFS). Ab initio molecular dynamics (AIMD) simulations reveal that Mn 2+ incorporation shortens the polysulfide chain in the gel matrix compared to the Mo 3 S 13 chalcogel, while forming a coordination environment with disulfide groups, analogous to the experimental findings. A Li/Mn 0.25 Mo 3 S 13 half-cell delivers 897 mAh g –1 capacity during the first discharge and retains 571 mAh g –1 capacity after 100 cycles at a C/3 rate. Distribution of relaxation time (DRT) unveils a stable solid–electrolyte interphase (SEI) formation upon cycling that enables charge–discharge reversibility. Here, the enhanced capacity retention and cycle stability compared to those of the Li/Mo 3 S 13 cell are attributed to the reduced dissolution of active mass into the electrolyte, facilitated by the formation of shorter polysulfide chains within the Mn 0.25 Mo 3 S 13 structure and the strong affinity of Lewis-acidic Mn 2+ for polysulfide anions generated during the charge–discharge process of the Li/Mn 0.25 Mo 3 S 13 cell. Thus, this work illustrates a design principle of material for high-capacity and cycle-stable Li-metal sulfide batteries.

25 ENERGY STORAGE↗

Rational design of heterogeneous single-site catalysts via surface organometallic chemistry

Single-site heterogeneous catalysts offer an attractive route to unite the molecular precision of homogeneous catalysis with the durability and practical advantages of solids. Surface organometallic chemistry (SOMC) provides a particularly powerful strategy for this purpose by grafting molecular precursors onto tailored surfaces and converting support functionalities into ligand environments for isolated metal centers. As a result, SOMC brings the language and logic of coordination chemistry to heterogeneous catalysis, where the support becomes an integral part of the active site coordination sphere. This Review surveys recent progress in the rational design of SOMC-derived single-site catalysts, with emphasis on synthetic routes, post synthetic transformations, and the deliberate tuning of catalytic behavior through metal-support interactions. Discussions are made on how support identity, hydroxyl topology, acidity, and redox activity shape the geometry, electronic structure, and oxidation state of supported metal sites, as well as how these factors determine activity, selectivity, and stability. We also examine a central limitation of these systems: despite their molecularly informed design, supported single sites often exist as structurally distributed ensembles rather than uniform species, particularly on amorphous supports. This site heterogeneity, along with catalyst dynamics under operating conditions, remains a major barrier to definitive structure-activity relationships. Therefore, emerging approaches that combine advanced characterization, first-principles modeling, ensemble kinetics, and machine learning to resolve active-site structure and guide catalyst development are highlighted. Together, these advances position SOMC as a versatile coordination chemistry framework for the predictive design of heterogeneous catalysts with well-defined molecularly tailored active sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗

TaZr_BCC_SolidSolution_128atoms_VASP6

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

36 MATERIALS SCIENCE↗

Importance of gas heating in capacitively coupled radiofrequency plasma-assisted synthesis of carbon nanomaterials

In pursuit of diamond nanoparticles, a capacitively-coupled radio frequency flow-through plasma reactor was operated with methane-argon gas mixtures. Signatures of the final product obtained microscopically and spectroscopically indicated that the product was an amorphous form of graphite. This result was consistent irrespective of combinations of the macroscopic reactor settings. To explain the observed synthesis output, measurements of C 2 and gas properties were carried out by laser-induced fluorescence and optical emission spectroscopy. Strikingly, the results indicated a strong gas temperature gradient of 100 K per mm from the center of the reactor to the wall. Based on additional plasma imaging, a model of hot constricted region (filamentation region) was then formulated. It illustrated that, while the hot constricted region was present, the bulk of the gas was not hot enough to facilitate diamond sp 3 formation: characterized by much lower reaction rates, when compared to sp 2 , sp 3 formation kinetics are expected to become exponentially slow. This result was further confirmed by experiments under identical conditions but with a H 2 /CH 4 mixture, where no output material was detected: if graphitic sp 2 formation was expected as the main output material from the methane feedstock, atomic hydrogen would then be expected to etch it away in situ, such that the net production of that sp 2 -hybridized solid material is nearly a zero. Finally, the crucial importance of gas heating was corroborated by replacing RF with microwave source whereby facile sp 3 production was attained with H 2 /CH 4 gas mixture.

36 MATERIALS SCIENCE↗

Modeling Analysis of Ball-Milling Process for Battery-Electrode Synthesis

The mechanical alloying process is a promising method for synthesizing electrode materials for batteries owing to its benefits such as the ability to produce nanostructured, high-performing electrode alloys, no adverse effects on the solid electrolyte for solid-state batteries, stable production of thick electrodes, simple processing steps, and low processing costs. It is gaining intensive attention in the battery industry as one of the best methods to replace the conventional wet-slurry-solvent method, and its application is rapidly increasing these days. However, the operation is currently conducted purely based on trial-and-error methods without fully utilizing the features of its functions. Here, this may be attributed to a lack of understanding of the effect of operating parameters on the alloying process and final products. Surprisingly, there is a scarcity of the literature conducting fundamental research to comprehend the underlying physics of the entire mechanical alloying process, resulting in a significant knowledge gap. To address this knowledge gap, extensive research was conducted. The existing literature on mechanical alloying was reviewed to comprehend the current state of understanding and to discuss the direction for future research. Mathematical expressions were developed to create physics-based models capable of capturing the entire mechanical alloying process, including milling kinetics and defect-enhanced phase evolution. These methods were then applied to investigate the impact of operating parameters such as milling frequency, initial mole ratio of the alloyed materials, density of grinding balls, and energy required for the powders to become amorphous (i.e., the amorphization energy threshold). This research aimed not only to comprehend the direct effects of these operating parameters but also to unveil the physics underlying the ball-milling process. The results of our study can serve as crucial information for the battery industry in designing or operating the ball-milling process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Time-Temperature-Transformation (TTT) Diagram for a Sludge Batch 9 Glass Composition Based on Coupled-Operation with the Salt Waste Processing Facility

The amorphous structure of a glass waste form has the potential to rearrange into crystalline phases at temperatures between the liquidus temperature and the glass transition temperature (Tg). Certain phases that can form will be detrimental to the durability of the glass and it is important to know the conditions that promote devitrification. The canister-centerline-cooling (CCC) profile is used to replicate the area within the center of the Defense Waste Processing Facility (DWPF) canister with the slowest cooling during the initial cool down after pouring, which has the greatest potential for crystallization. Other time-temperature conditions that cause significant changes in either phase structure or phase composition are identified by a time-temperature-transformation (TTT) study. The phase stability of a waste form must be determined as a part of the Waste Acceptance Product Specifications (WAPS) if it is to eventually be stored in a geologic repository. This requires the creation of a TTT diagram and analysis of the Tg, as defined by the Department of Energy (DOE). The previous TTT study for a DWPF glass waste form was completed in 2010 prior to coupled operation with the Salt Waste Processing Facility (SWPF). SWPF transfers two high activity waste streams to DWPF for vitrification: a cesium-containing strip effluent and a stream containing monosodium titanate/sludge solids. These SWPF streams were first transferred to DWPF for vitrification during Sludge Batch 9 (SB9) in 2021. The impact of these SWPF streams on crystallization behavior was not determined in previous studies and the need for data to satisfy WAPS Specification 1.4 for SB9 was identified.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Structural Heterogeneity in Medium-Entropy AgMnSbPbTe 4 for Glassy Thermal Transport and High Thermoelectric Performance

Medium-entropy semiconductors represent a unique category of entropy-engineered materials. They possess a considerable level of randomness in atomic mixing, although this is not sufficient to conclusively achieve single-phase structure stabilization, in contrast to high-entropy materials. This introduces strong competition between the formation of different phases, which can potentially lead to structural heterogeneity. Here, in this work, we uncover endotaxial nanoprecipitates in the microscopically identified homogeneous medium-entropy semiconductor AgMnSbPbTe 4 . These nanoprecipitates initially crystallize in a cubic phase $(Fm\bar{3}m)$ within kinetically stabilized AgMnSbPbTe 4 , subsequently evolving into a thermodynamically stable monoclinic phase $(P2_1/c)$ during thermal annealing while maintaining an endotaxial relationship with the matrix lattice. This nanophase segregation and the resultant lattice mismatch at interfaces introduce strain fluctuations up to 5% at intervals of 20 nm across the entire microstructure. Within the matrix phase, atomic displacement of up to 23 pm was observed. This structural heterogeneity results in glass-like thermal transport behavior, achieving an ultralow lattice thermal conductivity κ L = 0.312 Wm –1 K –1 at 800 K, which is in accordance with the amorphous limit predicted by the Cahill model. The synergy of band convergence effect and well-maintained carrier mobility leads to a maximum ZT of 1.72 at 800 K and an average ZT avg of 1.02 over the temperature range of 300–825 K. This study highlights that the underexplored structural heterogeneity in medium-entropy semiconductors can potentially yield beneficial phenomena, such as the phonon-glass electron-crystal transport behavior in this case, which holds promise for advancing thermoelectric applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanisms and stability of Li dynamics in amorphous Li-Ti-P-S-based mixed ionic–electronic conductors: A machine learning molecular dynamics study

Mixed ionic–electronic conductors (MIECs) exhibit both high ionic and electronic conductivity to improve the battery performance. In this work, we investigate the mechanism and stability of transport channels in our recently developed MIEC material, amorphous Ti-doped lithium phosphorus sulfide (LPS), using molecular dynamics (MD) simulations with a 99% accurate machine-learning force field (MLFF) trained on ab initio MD data. The achieved MLFF helps efficient large-scale MD simulations on LPS with three Ti concentrations (10%, 20%, and 30%) and six temperatures (25°C to 225°C) to calculate ionic conductivity, activation energy, Li-ion transport mechanism, and configurational entropy. Results show that ionic conductivities and activation energies are consistent with our recent experimental values. Moreover, Li-ion transport occurs via free-volume diffusion facilitated by the formation of disordered Li-S polyhedra. The enhanced stability of transport channels at 10% and 20% Ti doping, compared to 0% and 30%, is observed by analyzing the vibrational and configurational entropy of these disordered Li-S polyhedra. Overall, this study highlights the utility of MLFF-based large-scale MD simulations in explaining the transport mechanism and the stability of Li-ion in Ti-doped LPS electrolyte with significant computational efficiency.

And configuration entropy↗

Molecular Imaging of Microbially Induced Corrosion of Synthetic Archeological Glasses by a Rhizosphere Bacterium

Microbially induced corrosion (MIC) focuses on the degradation of solid materials, such as glass or metal. Soil microbes are often associated with the corrosion of foreign objects in the rhizosphere. Paenibacillus polymyxa SCE2, a facultative anaerobic bacterium in soil, is of the same genus as bacteria found near nuclear waste disposal sites. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used for imaging surface changes induced by P. polymyxa SCE2 cultured on two synthetic glass coupons to represent natural analogs of materials that were studied in relation to the vitrification of nuclear waste. Multimodal imaging was used to verify bacterial coverage across the glass surface after long-term growth. ToF-SIMS spectral analysis showed detection of glass component ions, such as silicon oxide (m/z – 59.96 SiO 2 – ) and aluminum oxide (m/z – 101.95 Al 2 O 3 – ), and biofilm’s extracellular polymeric substance (EPS) components, such as pentadecanoic acid (m/z – 241.22 C 15 H 29 O 2 – ) and sterol lipids (m/z – 311.16 C 20 H 23 O 3 – ). ToF-SIMS spectral, imaging, and depth profiling analyses showed that the glass rich in silica and other light elements (“granite glass”) had more “corrosion related” peaks than the glass that was less silica-rich and contained more iron (“dike glass”). Furthermore, these surface and interface compositional and spatial differences observed in the mass spectra and imaging were attributed to bacterial metabolism and an electron transfer mechanism influenced by morphological and compositional differences between the two types of glasses. ToF-SIMS is effective in studying microbial effects, bringing new molecular insights into MIC in a broader context of materials degradation.

Amorphous materials↗