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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Recovery of Oxidized Actinides, Np(VI), Pu(VI), and Am(VI), from Cocrystallized Uranyl Nitrate Hexahydrate: A Single Technology Approach to Used Nuclear Fuel Recycling

In this work, the utility of recovering cocrystallized Np, Pu, and Am from a uranyl nitrate hexahydrate crystalline phase has been examined. Progressive dissolution studies were carried out on samples of either Np(VI), Pu(VI), or Am(VI) cocrystallized with uranyl nitrate hexahydrate, resulting in a linear relationship between the amount of actinides dissolved as a function of volume of HNO 3 added, which indicates homogeneous distribution of the transuranic species throughout the crystalline solid. The ratio of the concentration of U to the heavier actinides was maintained over the entire dissolution and mimicked that of the starting cocrystallization solution. A series of five crystallization–dissolution–recrystallization cycles of uranyl nitrate hexahydrate from nitric acid have been achieved in the presence of Am(VI), where the behavior of Am(VI) followed that of U(VI) for each step of all five cycles. Negligible reduction of Am(VI) to Am(III) was observed between each recrystallization cycle. These results indicate the utility of a group hexavalent actinide cocrystallization approach toward used nuclear fuel recycling.

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

Homoleptic An(IV) Dimethyl Sulfoxide Complexes of Th–Pu Enable Insight into Solution Speciation and Redox

A family of 8- and 9- coordinate homoleptic dimethyl sulfoxide An(IV) complexes is used to evaluate the solvation properties of tetravalent actinide ions in dimethyl sulfoxide (DMSO) vs aqueous media. These compounds are prepared from aqueous mixtures of DMSO and yield crystalline solids, whose solid-state electronic absorption spectra are compared to solution phase spectra, providing insight into the solution speciation. The thermodynamics of the equilibria between the 8- and 9-coordinate compounds were determined experimentally and computationally, showing a trend that correlates with ionic radius. Cyclic voltammetry data for the +IV/+III couples of Np and Pu in the DMSO electrolyte indicate that the +IV ions are significantly stabilized compared to aqueous media due to the more donating nature of DMSO compared to water. As a result, computational studies of these systems indicate that further reactivity may take place upon reduction to the +III oxidation state.

Actinides↗
DOE OSTI2021

Davis Computational Spectroscopy Workflow—From Structure to Spectra

Here, we describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the atomic simulation environment (ASE) as an interface, we demonstrate the use of a selection of calculators, including density functional theory (DFT) and density functional tight binding (DFTB), to optimize the structures and calculate interatomic force constants. We present the use of our workflow to compute the phonon frequencies and eigenvectors, which are required to accurately simulate the INS spectra in crystalline solids like diamond and graphite as well as molecular solids like rubrene. We have also implemented a machine-learning force field based on Chebyshev polynomials called the Chebyshev interaction model for efficient simulation (ChIMES) to improve the accuracy of the DFTB simulations. We then explore the transferability of our DFTB/ChIMES models by comparing simulations derived from different training sets. We show that DFTB/ChIMES demonstrates ~100× reduction in computational expense while retaining most of the accuracy of DFT as well as yielding high accuracy for different materials outside of our training sets. The DFTB/ChIMES method within the workflow expands the possibilities to use simulations to accurately predict materials properties of increasingly complex structures that would be unfeasible with ab initio methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Role of Molecular Simulations in the Design of Metal–Organic Frameworks for Gas-Phase Thermocatalysis: A Perspective

Here, metal organic frameworks (MOFs) are highly tunable porous crystalline solids with spatially and electronically isolated catalytically active sites that have been demonstrated for a variety of thermo-, redox-, and photocatalytic reactions. Their tunable natures and relatively well-defined active sites make them advantageous for catalyst design, and molecular simulations have proven highly valuable in this endeavor. However, complexities in the MOF structure require advanced simulation strategies that accurately capture quantum chemistry at the strongly correlated transition metal cation active sites, compositional and structural changes caused by finite temperature and pressure reaction conditions, and transport effects in variously sized pore environments. Luckily, several groups have started using such simulation strategies, paving the way for rich opportunities to design MOF catalysts. Herein, we highlight such examples and provide a perspective on the needs for molecular simulations in the design of MOF catalysts moving forward.

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

Harnessing Neural Networks for Elucidating X-ray Absorption Structure–Spectrum Relationships in Amorphous Carbon

Improved understanding of structural and chemical properties through local experimental probes, such as X-ray absorption near-edge structure (XANES) spectroscopy, is crucial for the understanding and design of functional materials. In recent years, significant advancements have been made in the development of data science approaches for the automated interpretation of XANES structure–spectrum relationships. However, existing studies have primarily focused on crystalline solids and small molecules, while fewer efforts have been devoted to disordered systems. Thus, in this work, we demonstrate the development of neural network models for predicting and interpreting XANES spectra of amorphous carbon (a-C) from local structural descriptors. Comparison between different structural descriptors expectedly shows that the inclusion of both bond length and bond angle information is necessary for an accurate prediction of the spectra. Among the descriptors considered in this work, we find that the local many-body tensor representation yields the highest accuracy and greatest interpretability so that it can be leveraged to understand the importance of structural motifs in determining XANES spectra. Furthermore, we also discuss performance of neural network models for predicting both local structure features, such as bond lengths and bond angles, and global chemical composition, such as the sp:sp 2 :sp 3 ratio.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of Nanoconfinement on Polymer Chain Dynamics

Here, we report on a study of the effects of nanoconfinement on polymer chain dynamics within the framework developed by Muthukumar [Muthukumar, M. (1991). Journal of Non-Crystalline Solids, 131, 654-666.], who suggests that there is an entropically controlled dynamical regime between the Rouse and the reptation regimes that affects the power law dependence on molecular weight of the transport properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Pseudoelasticity of SrNi2P2 Micropillar via Double Lattice Collapse and Expansion

The maximum recoverable strain of most crystalline solids is less than 1% because plastic deformation or fracture usually occurs at a small strain. In this work, we show that a SrNi 2 P 2 micropillar exhibits pseudoelasticity with a large maximum recoverable strain of ~14% under uniaxial compression via unique reversible structural transformation, double lattice collapse–expansion that is repeatable under cyclic loading. Its high yield strength (~3.8 ± 0.5 GPa) and large maximum recoverable strain bring out the ultrahigh modulus of resilience (~146 ± 19 MJ/m 3 ), a few orders of magnitude higher than that of most engineering materials. The double lattice collapse–expansion mechanism shows stress–strain behaviors similar to that of conventional shape-memory alloys, such as hysteresis and thermo-mechanical actuation, even though the structural changes involved are completely different. Our work suggests that the discovery of a new class of high-performance ThCr 2 Si 2 -structured materials will open new research opportunities in the field of pseudoelasticity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Lone-Electron-Pair Micelles Strengthen Bond Anharmonicity in MnPb16Sb14S38 Complex Sulfosalt Leading to Ultra-Low Thermal Conductivity

Designing crystalline solids in which intrinsic extremely low lattice thermal conductivity mainly arises from its unique bonding nature rather than structure complexity and/or atomic disorder could promote thermal energy manipulation and utilization for applications ranging from thermoelectric energy conversion to thermal barrier coatings. Here, we report an extremely low lattice thermal conductivity of ~0.34 W m-1 K-1 at 300 K in the new complex sulfosalt MnPb16Sb14S38. We attribute the ultra-low lattice thermal conductivity to a synergistic combination of scattering mechanisms involving (1) strong bond anharmonicity in various structural building units, owing to the presence of stereoactive lone-electron-pair (LEP) micelles, and (2) phonon scattering at the interfaces between building units of increasing size and complexity. Remarkably, low-temperature heat capacity measurement revealed a Cp value of 0.206 J g-1 K-1 at T > 300 K, which is 22% lower than the Dulong-Petit value (0.274 J g-1 K-1). Further analysis of the Cp data and sound velocity (ν = 1834 m/s) measurement yielded Debye temperature values of 161 K and 187 K, respectively. Here, the resulting Grüneisen parameter, γ = 1.65, further supports strong bond anharmonicity as the dominant mechanism responsible for the observed extremely low lattice thermal conductivity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

An Atom-Precise Approach to Damp First-Order Phase Transitions and Its Implications for Neuromorphic Signal Processing

Neuromorphic computing inspired by mammalian intelligence aims to emulate the nonlinear dynamics of biological neurons and synapses to achieve fast, low-energy, and highly efficient information processing. Brain-inspired computing relies on the design and discovery of materials exhibiting nonlinear current–voltage profiles, frequently underpinned by electronic state transitions, to achieve spiking neurons and dynamically tunable synapses. A signature challenge in the design of artificial neurons is controlling the steepness of first-order transitions in active elements, as abrupt transitions are at risk of driving unstable voltage and temperature oscillations, which result in catastrophic device failure. A critical knowledge gap is the lack of structure–function correlations mapping the composition and atomistic structure of crystalline solids to nonlinear dynamical response characteristics. Here, we address the key question of how modification of atomistic structure correlates with alteration of neuron-like functionality. Constructing oscillator circuits from millimeter-scale single crystals enables high-resolution atomic structure solutions, which we use to demonstrate that the selective positioning of Pb cations modifies charge ordering along a one-dimensional CuxV2O5 framework even at low insertion stoichiometries, thereby providing an atom-precise design parameter for damping first-order transitions. We use temperature-variant X-ray diffraction and X-ray spectroscopy to elucidate the suppression of Cu-ion shuttling based on the precise positioning of Pb ions in seven-coordinated tunnel interstitial sites as the mechanistic basis for transition broadening, thus bridging a critical gap between statistical mechanics and quantum chemical descriptions of phase transitions. Such mechanistic understanding thus paves the way to site-selective modification strategies for modulating the sharpness of first-order transitions, with an exemplary demonstration here in tuning neuronal signal processing.

Crystal structure↗
DOE OSTI2020

Structure and properties of densified silica glass: characterizing the order within disorder

The broken symmetry in the atomic-scale ordering of glassy versus crystalline solids leads to a daunting challenge to provide suitable metrics for describing the order within disorder, especially on length scales beyond the nearest neighbor that are characterized by rich structural complexity. Here, we address this challenge for silica, a canonical network-forming glass, by using hot versus cold compression to (i) systematically increase the structural ordering after densification and (ii) prepare two glasses with the same high-density but contrasting structures. The structure was measured by high-energy X-ray and neutron diffraction, and atomistic models were generated that reproduce the experimental results. The vibrational and thermodynamic properties of the glasses were probed by using inelastic neutron scattering and calorimetry, respectively. Traditional measures of amorphous structures show relatively subtle changes upon compacting the glass. The method of persistent homology identifies, however, distinct features in the network topology that change as the initially open structure of the glass is collapsed. The results for the same high-density glasses show that the nature of structural disorder does impact the heat capacity and boson peak in the low-frequency dynamical spectra. Densification is discussed in terms of the loss of locally favored tetrahedral structures comprising oxygen-decorated SiSi 4<:sub> tetrahedra.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Giant topological longitudinal circular photo-galvanic effect in the chiral multifold semimetal CoSi

The absence of mirror symmetry, or chirality, is behind striking natural phenomena found in systems as diverse as DNA and crystalline solids. A remarkable example occurs when chiral semimetals with topologically protected band degeneracies are illuminated with circularly polarized light. Under the right conditions, the part of the generated photocurrent that switches sign upon reversal of the light’s polarization, known as the circular photo-galvanic effect, is predicted to depend only on fundamental constants. The conditions to observe quantization are non-universal, and depend on material parameters and the incident frequency. In this work, we perform terahertz emission spectroscopy with tunable photon energy from 0.2 –1.1 eV in the chiral topological semimetal CoSi. We identify a large longitudinal photocurrent peaked at 0.4 eV reaching ~550 μ A/V 2 , which is much larger than the photocurrent in any chiral crystal reported in the literature. Using first-principles calculations we establish that the peak originates only from topological band crossings, reaching 3.3 ± 0.3 in units of the quantization constant. Our calculations indicate that the quantized circular photo-galvanic effect is within reach in CoSi upon doping and increase of the hot-carrier lifetime. The large photo-conductivity suggests that topological semimetals could potentially be used as novel mid-infrared detectors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Rapid and efficient hydrogen clathrate hydrate formation in confined nanospace

Clathrate hydrates are crystalline solids characterized by their ability to accommodate large quantities of guest molecules. Although CH 4 and CO 2 are the traditional guests found in natural systems, incorporating smaller molecules (e.g., H 2 ) is challenging due to the need to apply higher pressures to stabilize the hydrogen-bonded network. Another critical limitation of hydrates is the slow nucleation and growth kinetics. Here, we show that specially designed activated carbon materials can surpass these obstacles by acting as nanoreactors promoting the nucleation and growth of H 2 hydrates. The confinement effects in the inner cavities promote the massive growth of hydrogen hydrates at moderate temperatures, using pure water, with extremely fast kinetics and much lower pressures than the bulk system.

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

Unveiling the orbital texture of 1T-TiTe 2 using intrinsic linear dichroism in multidimensional photoemission spectroscopy

The momentum-dependent orbital character in crystalline solids, referred to as orbital texture, is of capital importance in the emergence of symmetry-broken collective phases, such as charge density waves as well as superconducting and topological states of matter. By performing extreme ultraviolet multidimensional angle-resolved photoemission spectroscopy for two different crystal orientations linked to each other by mirror symmetry, we isolate and identify the role of orbital texture in photoemission from the transition metal dichalcogenide 1T-TiTe 2 . By comparing our experimental results with theoretical calculations based on both a quantitative one-step model of photoemission and an intuitive tight-binding model, we unambiguously demonstrate the link between the momentum-dependent orbital orientation and the emergence of strong intrinsic linear dichroism in the photoelectron angular distributions. Our results represent an important step towards going beyond band structure (eigenvalues) mapping and learning about electronic wavefunction and orbital texture of solids by exploiting matrix element effects in photoemission spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PAH101: A GW+BSE Dataset of 101 Polycyclic Aromatic Hydrocarbon (PAH) Molecular Crystals

Abstract The excited-state properties of molecular crystals are important for applications in organic electronic devices. TheGWapproximation and Bethe-Salpeter equation (GW+BSE) is the state-of-the-art method for calculating the excited-state properties of crystalline solids with periodic boundary conditions. We present the PAH101 dataset ofGW+BSE calculations for 101 molecular crystals of polycyclic aromatic hydrocarbons (PAHs) with up to ~500 atoms in the unit cell. To the best of our knowledge, this is the firstGW+BSE dataset for molecular crystals. The data records include theGWquasiparticle band structure, the fundamental band gap, the static dielectric constant, the first singlet exciton energy (optical gap), the first triplet exciton energy, the dielectric function, and optical absorption spectra for light polarized along the three lattice vectors. The dataset can be used to (i) discover materials with desired electronic/optical properties, (ii) identify correlations between DFT andGW+BSE quantities, and (iii) train machine learned models to help in materials discovery efforts.

Science & Technology - Other Topics↗
DOE OSTI2023

An analytic and complete equation of state for condensed phase materials

Analytic equations of state (EOS) are intended to reproduce theoretical and experimental data in a single phase portion of the thermodynamic space. We devise a complete and thermodynamically consistent model with four distinct features: (1) a reference isotherm that remains thermodynamically stable, (2) a flexible specific heat model based on a fourth-order rational polynomial, (3) a Grüneisen parameter that depends on specific volume and temperature, and (4) pressure and internal energy functions that can be inverted analytically in temperature. The model aims to improve the accuracy of existing equations of state while remaining computationally efficient. To demonstrate its features, we include calibrations for single-crystal pentaerythritol tetranitrate (PETN), liquid nitromethane (NM), and hexagonal close-packed beryllium (Be) metal. The parameter optimization uses the specific heat capacity, Grüneisen parameter, and static compression curves obtained from density functional theory for the crystalline solids and molecular dynamics simulations for liquid NM. We also present a velocity autocorrelation function that yields accurate phonon densities of states for the EOS calibration from the molecular dynamics trajectories. Each of the three calibrations is constrained to enforce the ambient state from experimental measurements and validated against experimental Hugoniot data from multiple sources. We also include one-dimensional hydrodynamic simulations of the isentropic compression experiments for beryllium conducted at the Z facility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Prediction of vacancy defect diffusion paths in high entropy alloys via machine learning on molecular dynamics data

Identifying the diffusion path of point defects is a critical step in understanding their evolution and the mechanisms of related phenomena. Defect diffusion occurs at small length and time scales, with impacts on material properties that may continue to evolve over ns to μs, ms, and the continuum scale (s, min, etc., and cm, m, etc.). The time scale accessible to molecular dynamics (MD) simulations is limited by small step sizes, typically in the fs range. Thus, surrogate models of MD simulations through machine learning (ML)-based algorithms are of great interest, especially for complex systems such as high entropy alloys (HEAs). In this work, dynamics governing vacancy migration in HEA were approximated with graph convolutional network (GCN) models as ansatzes for kinetic Monte Carlo (KMC) rate catalogs. Network design considered that diffusion in crystalline solids generally depends on interactions between defects and their immediate neighbor atoms. Graphs represented the vacancy surroundings, MD-generated trajectories provided training and comparison datasets, and unsupervised GCN models approximated interatomic dynamics governing vacancy migration in HEAs as ansatzes for KMC. A proof-of-concept model trained on MD data for the Fe, Ni, Cr, Co, and Cu HEA environment was used with two different neighbor interactions to assess the feasibility of training a GCN to predict vacancy defect transition rates in the HEA environment. The resulting setup rapidly generated MD-formatted synthetic trajectories based on dynamics learned from the MD training set, with a time acceleration of roughly two orders of magnitude and a similar diffusion coefficient to MD observations. Additionally, Nudged Elastic Band (NEB) calculations were performed on randomly generated FeNiCrCoCu HEA structures to determine vacancy migration barriers across nearest-neighbor sites. Transition probabilities for each jump, categorized by atomic type, were extracted from these calculations. NEB-based and GCN-based approaches led to similar outcomes.

Reimer, C↗
DOE OSTI2023

Stress-dependent activation entropy in thermally activated cross-slip of dislocations

Cross-slip of screw dislocations in crystalline solids is a stress-driven thermally activated process essential to many phenomena during plastic deformation, including dislocation pattern formation, strain hardening, and dynamic recovery. Molecular dynamics (MD) simulation has played an important role in determining the microscopic mechanisms of cross-slip. However, due to its limited timescale, MD can only predict cross-slip rates in high-stress or high-temperature conditions. The transition state theory can predict the cross-slip rate over a broad range of stress and temperature conditions, but its predictions have been found to be several orders of magnitude too low in comparison to MD results. This discrepancy can be expressed as an anomalously large activation entropy whose physical origin remains unclear. Here, we resolve this discrepancy by showing that the large activation entropy results from anharmonic effects, including thermal softening, thermal expansion, and soft vibrational modes of the dislocation. We expect these anharmonic effects to be significant in a wide range of stress-driven thermally activated processes in solids.

Science & Technology - Other Topics↗
DOE OSTI2020

Review of Ion Exchange Technologies for Cesium Removal from Caustic Tank Waste

This article reviews the historical uses of and current research into ion exchange for the removal of cesium (Cs) from defense-related nuclear waste streams. Emphasis is placed on key attributes of the two current leading ion exchangers for Cs removal: spherical resorcinol-formaldehyde, an elutable organic resin, and crystalline silicotitanate, a non-elutable crystalline solid. An understanding of the successes, issues, and limitations of past ion exchange experience may be helpful in better understanding current ion exchanger use. Emphasis is placed on Cs capacity, exchange kinetics, stability, and column hydrodynamics for processing alkaline wastes as well as the final waste forms of the ion exchangers.

Fiskum, Sandra K.↗