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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Uranium (VI) Adsorbate Structures on Portlandite [Ca(OH)2] Type Surfaces Determined by Computational Modelling and X-ray Absorption Spectroscopy

Portlandite [Ca(OH) 2 ] is a potentially dominant solid phase in the high pH fluids expected within the cementitious engineered barriers of Geological Disposal Facilities (GDF). This study combined X-ray Absorption Spectroscopy with computational modelling in order to provide atomic-scale data which improves our understanding of how a critically important radionuclide (U) will be adsorbed onto this phase under conditions relevant to a GDF environment. Such data are fundamental for predicting radionuclide mass transfer. Surface coordination chemistry and speciation of uranium with portlandite [Ca(OH) 2 ] under alkaline groundwater conditions (ca. pH 12) were determined by both in situ and ex situ grazing incidence extended X-ray absorption fine structure analysis (EXAFS) and by computational modelling at the atomic level. Free energies of sorption of aqueous uranyl hydroxides, [UO 2 (OH) n ] 2–n (n = 0–5) with the (001), (100) and (203) or (101) surfaces of portlandite are predicted from the potential of mean force using classical molecular umbrella sampling simulation methods and the structural interactions are further explored using fully periodic density functional theory computations. Although uranyl is predicted to only weakly adsorb to the (001) and (100) clean surfaces, there should be significantly stronger interactions with the (203/101) surface or at hydroxyl vacancies, both prevalent under groundwater conditions. The uranyl surface complex is typically found to include four equatorially coordinated hydroxyl ligands, forming an inner-sphere sorbate by direct interaction of a uranyl oxygen with surface calcium ions in both the (001) and (203/101) cases. In contrast, on the (100) surface, uranyl is sorbed with its axis more parallel to the surface plane. The EXAFS data are largely consistent with a surface structural layer or film similar to calcium uranate, but also show distinct uranyl characteristics, with the uranyl ion exhibiting the classic dioxygenyl oxygens at 1.8 Å and between four and five equatorial oxygen atoms at distances between 2.28 and 2.35 Å from the central U absorber. These experimental data are wholly consistent with the adsorbate configuration predicted by the computational models. These findings suggest that, under the strongly alkaline conditions of a cementitious backfill engineered barrier, there would be significant uptake of uranyl by portlandite to inhibit the mobility of U(VI) from the near field of a geological disposal facility.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Powder satellite-reduction apparatus and method for gas atomization process

The broad applicability of at least certain aspects of the present invention derives from the ability to determine the critical location where secondary satellite formation occurs for any atomization system or design and allows for the rapid assessment of the effectiveness of various satellite reduction strategies, including but not limited to several embodiments detailed herein. Aspects of this invention can be utilized during initial atomization system design in order to evaluate effective chamber geometries and enabling strategies which reduce/eliminate satelliting, or can be retrofit to existing systems and allows for economic evaluation of effectiveness based off of initial capital expenditures versus increased operating requirements/expenses.

Anderson, Iver E.↗
DOE OSTI2024

Embedding Neural Thermal Scattering (NeTS) Modules in SERPENT for Higher Fidelity Advanced Reactor Analysis

When a neutron born in fission thermalizes to the order of $k$ $B$ $T$, it’s de-Broglie wavelength and energy approach the order of inter-atomic spacing and elementary lattice oscillations, respectively. $S$($a,β,t$) or the scattering law, uuantify these temperature-dependent crystallographic contributions to total cross section (or reaction rate). In a Monte Carlo analysis, cumulative distribution functions (CDFs) of $S$($a,β,t$) are loaded to memory from “A Compact ENDF” (ACE) files for stochastically selecting thermal scattered neutron trajectories. In this work, novel neural thermal scattering (NeTS) modules for $S$($a,β,t$) CDFs are designed, trained, serialized and embedded within SERPENT using Python’s limited C-API for on-the-fly deployment of crystalline graphite $S$($a,β,t$) sampling. Torchscript tracing and Numba just-in-time (JIT) compilation streamline neural inference on NVIDIA GPUs with CUDA libraries. Demonstrations of bare sphere thermalization of fast and thermal sources show excellent agreement between embedded NeTS in SERPENT and MCNP. With an explicit model of the reactor, NeTS can predict on-the-fly changes in TREAT neutron spectra as a function of local temperature, which can serve to improve transient and accident predictions in a multiphysics analysis framework. This framework can be further extended to account on-the-fly for changes in local graphitic microstructure to scattering cross sections, and outlines a novel coupling of modern machine learning with state-of-the-art reactor physics methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Violation of the T –1 Relationship in the Lattice Thermal Conductivity of Mg 3 Sb 2 with Locally Asymmetric Vibrations

Most crystalline materials follow the guidelines of T –1 temperature-dependent lattice thermal conductivity (κ L ) at elevated temperatures. Here, we observe a weak temperature dependence of κ L in Mg 3 Sb 2 , T –0.48 from theory and T –0.57 from measurements, based on a comprehensive study combining ab initio molecular dynamics calculations and experimental measurements on single crystal Mg 3 Sb 2 . These results can be understood in terms of the so-called “phonon renormalization” effects due to the strong temperature dependence of the interatomic force constants (IFCs). The increasing temperature leads to the frequency upshifting for those low-frequency phonons dominating heat transport, and more importantly, the phonon-phonon interactions are weakened. In-depth analysis reveals that the phenomenon is closely related to the temperature-induced asymmetric movements of Mg atoms within MgSb 4 tetrahedron. With increasing temperature, these Mg atoms tend to locate at the areas with relatively low force in the force profile, leading to reduced effective 3 rd -order IFCs. The locally asymmetrical atomic movements at elevated temperatures can be further treated as an indicator of temperature-induced variations of IFCs and thus relatively strong phonon renormalization. The present work sheds light on the fundamental origins of anomalous temperature dependence of κ L in thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ordering in GaAs co-doped with Bi and N

Introducing only a few atomic percent of Bi or N in GaAs has a large effect on the band gap of the material. Specifically Bi doped GaAs shows potential for local band gap engineering in optoelectronic applications. The incorporation of Bi and N into GaAs is difficult due to strain effects. In this work we study the ordering of these dopants at the atomic scale in order to get a better understanding of the behavior of these dopants in the host lattice. Cross-sectional scanning tunneling microscopy is used to find the exact position of Bi and N dopants in the GaAs matrix, allowing us to study both their nearest neighbor pair occurrences and pair correlation functions. An attractive interaction between Bi dopants at short ranges (1-2 nm) is found and a similar effect is observed between N dopants. Here, we find a repulsive interaction with a similar length scale between Bi and N dopants. A similar repulsion is found in the Bi-N nearest neighbor pairs. Density functional theory is used to calculate the different nearest neighbor pair energies and test these results to the experimental pair occurrences. It is concluded from the experimental and theoretical results that the growth conditions and N inclusion greatly affects the Bi distribution in GaAs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Field-tunable valley coupling in a dodecagonal semiconductor quasicrystal

Quasicrystals are characterized by atomic arrangements having long-range order without periodicity. Van der Waals bilayers provide an opportunity to controllably vary the atomic alignment between two layers from a periodic moiré crystal to an aperiodic quasicrystal. Here, in this work, we reveal that in a dodecagonal WSe 2 quasicrystal, two separate valleys in separate layers are brought arbitrarily close in momentum space through higher-order Umklapp scatterings. A modest perpendicular electric field is then sufficient to induce strong interlayer valley hybridization, manifested as another hybrid excitonic doublet. Concurrently, we observe the disappearance of the trion that exists at low field, which we attribute to a modified spatial distribution of the wavefunction due to the quasicrystal potential. This is possibly a precursor to localization. Our findings highlight the ability of incommensurate systems to bring any pair of momenta into close proximity, thereby introducing opportunities for valley engineering.

electronic properties and materials↗
DOE OSTI2023

High-fidelity trapped-ion qubit operations with scalable photonic modulators

Abstract Experiments with trapped ions and neutral atoms typically employ optical modulators in order to control the phase, frequency, and amplitude of light directed to individual atoms. These elements are expensive, bulky, consume substantial power, and often rely on free-space I/O channels, all of which pose scaling challenges. To support many-ion systems like trapped-ion quantum computers or miniaturized deployable devices like clocks and sensors, these elements must ultimately be microfabricated, ideally monolithically with the trap to avoid losses associated with optical coupling between physically separate components. In this work we design, fabricate, and test an optical modulator capable of monolithic integration with a surface-electrode ion trap. These devices consist of piezo-optomechanical photonic integrated circuits configured as multi-stage Mach-Zehnder modulators that are used to control the intensity of light delivered to a single trapped ion on a separate chip. We use quantum tomography employing hundreds of multi-gate sequences to enhance the sensitivity of the fidelity to the types and magnitudes of gate errors relevant to quantum computing and better characterize the performance of the modulators, ultimately measuring single qubit gate fidelities that exceed 99.7%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Atomic imprinting in the absence of an intrinsic length scale

Bulk metallic glasses (BMGs) have successfully been used to replicate molds that are structured at the nano- and even atomic scale through thermoplastic forming (TPF), an ability that was speculated to be rooted in the glass’ featureless atomic structure. These previous demonstrations of atomically precise imprinting, however, were performed under conditions where mold atomic feature dimensions coincided with the unit cell size of constituents in the BMG. In order to evaluate if accurate atomic-scale replication is possible in general, i.e., independent of the accidental presence of favorable constituent size/feature size relationships, we have used Pt 57.5 Cu 14.7 Ni 5.3 P 22.5 to replicate three different crystalline facets of LaAlO 3 single crystals, each exposing distinct atomic step heights. We find that in all cases, the terraced surface termination can be copied with remarkable fidelity, corroborating that BMGs when thermoplastic formed are capable of adapting to any externally imposed confinement with sub-angstrom precision without being limited by factors related to the specifics of their internal structure. This unprecedented capability of quasi-limitless replication fidelity reveals that the deformation mechanism in the supercooled liquid state of BMGs is essentially homogeneous and suggests TPF of BMGs to be a versatile toolbox for atomic and precision nanoscale imprinting.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Atomically sharp domain walls in an antiferromagnet

The interest in understanding scaling limits of magnetic textures such as domain walls spans the entire field of magnetism from its physical fundamentals to applications in information technologies. Here, we explore antiferromagnetic CuMnAs in which imaging by x-ray photoemission reveals the presence of magnetic textures down to nanoscale, reaching the detection limit of this established microscopy in antiferromagnets. We achieve atomic resolution by using differential phase-contrast imaging within aberration-corrected scanning transmission electron microscopy. We identify abrupt domain walls in the antiferromagnetic film corresponding to the Néel order reversal between two neighboring atomic planes. Our work stimulates research of magnetic textures at the ultimate atomic scale and sheds light on electrical and ultrafast optical antiferromagnetic devices with magnetic field–insensitive neuromorphic functionalities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Confinement Reconstruction Unlocks Stable Ru Single Atom-Doped IrO x Anodes for Long-Term High-Rate CO 2 Electrolysis

IrO 2 is a commonly employed anode catalyst for CO 2 electrolysis in membrane electrode assembly (MEA) systems. However, under high current densities, its structural reconstruction leads to activity loss and stability degradation, limiting the industrial viability of CO 2 electrolysis. In this work, we demonstrated a confinement reconstruction strategy to precisely regulate the structural evolution during electrolysis. Ethylene glycol serves as a structural modulator, protecting the catalyst surface, suppressing soluble species formation, and promoting ordered structural evolution. Single-atom Ru acts as a stability enhancer, forming robust Ir–O–Ru bridging structures that facilitate an ordered transformation from a 4-fold [RuO 4 ]/[IrO 4 ] to a 6-fold symmetry [RuO 6 ]/[IrO 6 ] octahedral framework, thereby enhancing structural rigidity and long-term stability. As a result, in MEA-based CO 2 electrolysis, the catalyst achieves a stable operation at 200 mA cm –2 for 480 h, maintaining a CO selectivity above 80%. Theoretical calculations further elucidate that the enhanced stability originates from the suppression of oxygen vacancy formation, making the lattice-oxygen-mediated mechanism (LOM) potentially less favorable. This work provides insights into the structural evolution of the OER catalysts under high-current-density conditions, paving the way for large-scale CO 2 electrolysis commercialization.

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

Ultranarrow TaS 2 Nanoribbons

Imposing additional confinement in two-dimensional (2D) materials can yield further control over the associated electronic, optical, and topological properties. However, synthesis of ultra-narrow nanoribbons (NRs) remains a challenge, particularly for the transition metal dichalcogenides (TMDs), and synthesizing TMD NRs narrower than 50 nm has remained elusive. In this paper, we report the vapor-phase synthesis of ultra-narrow TaS 2 NRs. The NRs are grown within the hollow cavity of carbon nanotubes, thereby limiting their lateral dimensions and layer number, while simultaneously stabilizing them against the environment. The NRs reach the monolayer (ML) limit and exhibit widths as low as 2.5 nm. Atomic-resolution scanning transmission electron microscopy (STEM) reveals the detailed atomic structure of the ultra-narrow NRs and we observe a hitherto unseen atomic structure supermodulation phenomenon of ordered defect arrays within the NRs. First-principles calculations based on density functional theory (DFT) show the presence of flat bands, as well as edge- and boundary-localized states, and help identify the atomic configuration of the supermodulation. Nanotube-templated synthesis represents a unique, transferable, and broadly deployable route toward ultra-narrow TMD NR growth.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Micro‐ and Nanoscale Heterogeneities in Zeolite Beta as Measured by Atom Probe Tomography and Confocal Fluorescence Microscopy

Micro- and nanoscale information on the activating and deactivating coking behaviour of zeolite catalyst materials increases our current understanding of many industrially applied processes, such as the methanol-to-hydrocarbon (MTH) reaction. Atom probe tomography (APT) was used to reveal the link between framework and coke elemental distributions in 3D with sub-nanometre resolution. APT revealed 10–20 nanometre-sized Al-rich regions and short-range ordering (within nanometres) between Al atoms. With confocal fluorescence microscopy, it was found that the morphology of the zeolite crystal as well as the secondary mesoporous structures have a great effect on the microscale coke distribution throughout individual zeolite crystals over time. Additionally, a nanoscale heterogeneous distribution of carbon as residue from the MTH reaction was determined with carbon-rich areas of tens of nanometres within the zeolite crystals. Finally, a short length-scale affinity between C and Al atoms, as revealed by APT, indicates the formation of carbon-containing molecules next to the acidic sites in the zeolite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

OFraMP: a fragment-based tool to facilitate the parametrization of large molecules

Abstract An Online tool for Fragment-based Molecule Parametrization (OFraMP) is described. OFraMP is a web application for assigning atomic interaction parameters to large molecules by matching sub-fragments within the target molecule to equivalent sub-fragments within the Automated Topology Builder (ATB, atb.uq.edu.au) database. OFraMP identifies and compares alternative molecular fragments from the ATB database, which contains over 890,000 pre-parameterized molecules, using a novel hierarchical matching procedure. Atoms are considered within the context of an extended local environment (buffer region) with the degree of similarity between an atom in the target molecule and that in the proposed match controlled by varying the size of the buffer region. Adjacent matching atoms are combined into progressively larger matched sub-structures. The user then selects the most appropriate match. OFraMP also allows users to manually alter interaction parameters and automates the submission of missing substructures to the ATB in order to generate parameters for atoms in environments not represented in the existing database. The utility of OFraMP is illustrated using the anti-cancer agent paclitaxel and a dendrimer used in organic semiconductor devices. Graphical abstract OFraMP applied to paclitaxel (ATB ID 35922).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Altermagnetism in the layered intercalated transition metal dichalcogenide CoNb 4 Se 8

Altermagnets (AMs) are a new class of magnetic materials that combine the beneficial spintronics properties of ferromagnets and antiferromagnets, garnering significant attention recently. Here, we have identified altermagnetism in a layered intercalated transition metal diselenide, CoNb 4 Se 8 , which crystallizes with an ordered sublattice of intercalated Co atoms between NbSe 2 layers. Single crystals are synthesized, and the structural characterizations are performed using single crystal diffraction and scanning tunneling microscopy. Magnetic measurements reveal easy-axis antiferromagnetism below 168 K. Density functional theory (DFT) calculations indicate that A-type antiferromagnetic ordering with easy-axis spin direction is the ground state, which is verified through single crystal neutron diffraction experiments. Electronic band structure calculations in this magnetic state display spin-split bands, confirming altermagnetism in this compound. The layered structure of CoNb 4 Se 8 presents a promising platform for testing various predicted properties associated with altermagnetism.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Self-Assembly of Atomically Aligned Nanoparticle Superlattices from Pt–Fe 3 O 4 Heterodimer Nanoparticles

Multicomponent nanoparticle superlattices (SLs) promise the integration of nanoparticles (NPs) with remarkable electronic, magnetic, and optical properties into a single structure. Here, we demonstrate that heterodimers consisting of two conjoined NPs can self-assemble into novel multicomponent SLs with a high degree of alignment between the atomic lattices of individual NPs, which has been theorized to lead to a wide variety of remarkable properties. Specifically, by using simulations and experiments, we show that heterodimers composed of larger Fe 3 O 4 domains decorated with a Pt domain at one vertex can self-assemble into an SL with long-range atomic alignment between the Fe 3 O 4 domains of different NPs across the SL. The SLs show an unanticipated decreased coercivity relative to nonassembled NPs. In situ scattering of the self-assembly reveals a two-stage mechanism of self-assembly: translational ordering between NPs develops before atomic alignment. Here our experiments and simulation indicate that atomic alignment requires selective epitaxial growth of the smaller domain during heterodimer synthesis and specific size ratios of the heterodimer domains as opposed to specific chemical composition. This composition independence makes the self-assembly principles elucidated here applicable to the future preparation of multicomponent materials with fine structural control.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Organizing Chaos: Boosting Thermoelectric Properties by Ordering the Clathrate Framework of Ba 8 Cu 16 As 30

The type I clathrate, Ba 8 Cu 16 As 30 , is reinvestigated and found to have a low-temperature polymorph mP 108-Ba 8 Cu 16 As 30 with ordered Cu and As sites. In situ temperature-dependent powder X-ray diffraction experiments guided synthetic efforts toward the synthesis of the ordered monoclinic ( mP 108) and disordered cubic ( cP 54) polymorphs with high phase purity. While a transition from mP 108-Ba 8 Cu 16 As 30 to cP 54-Ba 8 Cu 16 As 30 is not directly observed, cP 54-Ba 8 Cu 16 As 30 is stabilized through quenching from high temperatures and is confirmed through high-resolution synchrotron powder X-ray diffraction. Further, combined theoretical predictions and experimental observations of the thermoelectric properties of both polymorphs reveal that the ordering of Cu and As atoms in the clathrate framework simultaneously enhances the Seebeck coefficient and electronic conductivity by increasing the hole effective mass and reducing the electronic scattering events. Consequently, the zT of mP 108-Ba 8 Cu 16 As 30 reaches a maximum of 0.2 at 575 K, an order of magnitude higher than that of cP 54-Ba 8 Cu 16 As 30 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗