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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structure and properties of NdCuGa 3 single crystals

Here this manuscript reports on the structural and magnetic properties of NdCuGa 3 using powder and single crystal X-ray diffraction (XRD), zero-field single crystal neutron diffraction, magnetization, and specific heat measurements. Our XRD on a single crystal specimen of NdCuGa3 confirmed that it crystallizes in the tetragonal BaNiSi 3 -type structure. A magnetic phase transition at T N = 3.3 K is assessed using specific heat and ac magnetic susceptibility measurements. No additional anomaly below T N down to 50 mK was detected by performing specific heat measurements. Neutron single crystal diffraction data collected at T = 300 mK confirm the antiferromagnetic phase below T N = 3.3 K with the propagation vector $\vec{\tau}$ = (0.2, 0, 0). Possible magnetic structure solutions of NdCuGa 3 are discussed

36 MATERIALS SCIENCE↗
DOE OSTI2023

Towards the extraction of the crystal cell parameters from pair distribution function profiles

The approach based on atomic pair distribution function (PDF) has revolutionized structural investigations by X-ray/electron diffraction of nano or quasi-amorphous materials, opening up the possibility of exploring short-range order. However, the ab initio crystal structural solution by the PDF is far from being achieved due to the difficulty in determining the crystallographic properties of the unit cell. A method for estimating the crystal cell parameters directly from a PDF profile is presented, which is composed of two steps: first, the type of crystal cell is inferred using machine-learning approaches applied to the PDF profile; second, the crystal cell parameters are extracted by means of multivariate analysis combined with vector superposition techniques. The procedure has been validated on a large number of PDF profiles calculated from known crystal structures and on a small number of measured PDF profiles. The lattice determination step has been benchmarked by a comprehensive exploration of different classifiers and different input data. The highest performance is obtained using the k -nearest neighbours classifier applied to whole PDF profiles. Descriptors calculated from the PDF profiles by recurrence quantitative analysis produce results that can be interpreted in terms of PDF properties, and the significance of each descriptor in determining the prediction is evaluated. The cell parameter extraction step depends on the cell metric rather than its type. Monometric, dimetric and trimetric cells have top-1 estimates that are correct 40, 20 and 5% of the time, respectively. Promising results were obtained when analysing real nanocrystals, where unit cells close to the true ones are found within the top-1 ranked solution in the case of monometric cells and within the top-6 ranked solutions in the case of dimetric cells, even in the presence of a crystalline impurity with a weight fraction up to 40%.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidating metal–organic framework structures using synchrotron serial crystallography

Metal organic frameworks (MOFs) are porous crystalline materials that display a wide variety of physical and chemical properties. Their single crystal structure determination is often challenging because in most cases micro- or nano-sized crystals spontaneously form upon MOF synthesis, which cannot be recrystallized. The production of larger single crystals for structure determination involves optimizing, and thus modifying, the conditions of synthesis, in which success cannot be guaranteed. Failure to produce crystals suitable for single-crystal X-ray diffraction leaves the 3D structure of the MOF compound unknown, and scientists must resort to more challenging structure solution methods based on X-ray powder or electron diffraction data. These laborious tasks can be avoided by using serial crystallography techniques which merge data collected on many micro-crystals. Here, we report the application of three synchrotron serial crystallography methods. We call these “mesh”, “grid” and “mesh&collect” scans. “Still” images (no rotation) are collected in the mesh scan approach, whereas small rotational wedges are collected in the grid scan method. The third protocol, mesh&collect, combines the acquisition of still images and rotational wedges. Using these means, we determine the ab initio structure of benchmark MOFs, MIL-100(Fe) and ZIF-8, that differ largely in unit cell size. These methods are expected to be widely applicable and facilitate structure determination of many MOF microcrystalline systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effect of Solvent on the Interaction of Lignin with a Zeolite Nanosheet in the Condensed Phase

Lignin is the essential building block of lignocellulosic biomass, an excellent renewable source of different aromatic monomers for the polymer and biofuel industry. The depolymerization of lignin into value-added chemicals and fuels through the catalytic process poses a significant challenge due to the complex structure of lignin. Understanding lignin’s conformational diversity and dynamics in the liquid phase is crucial to designing an effective depolymerization process. Here, we conducted all-atom molecular dynamics simulations to understand the conformation and dynamics of softwood lignin on the all-silica zeolite nanosheet based on the MFI topology in a binary mixture of water–methanol at three different molar compositions (0%, 50%, and 100% methanol). We observed that the methanol–surface interaction is stronger than the water–surface interaction, and methanol readily diffused into the MFI core. Lignin surface contacts decrease with increasing methanol composition due to higher solubility and dynamics. Lignin dynamics on the surface in neat water is an order of magnitude smaller than methanol. Here, we also found that lignin adopts a slightly extended conformation when it stays on the surface than in the bulk solution phase for the pure water case, whereas for pure methanol and the binary solution structures are statistically similar.

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

True molecular conformation and structure determination by three-dimensional electron diffraction of PAH by-products potentially useful for electronic applications

The true mol­ecular conformation and the crystal structure of benzo[e]di­naphtho­[2,3-a;1',2',3',4'-ghi]fluoranthene, 7,14-di­phenyl­naphtho­[1,2,3,4-cde]bis­anthene and 7,16-di­phenyl­naphtho­[1,2,3,4-cde]heli­anthrene were determined ab initio by 3D electron diffraction. All three mol­ecules are remarkable polycyclic aromatic hydro­carbons. The mol­ecular conformation of two of these com­pounds could not be determined via classical spectroscopic methods due to the large size of the mol­ecule and the occurrence of multiple and reciprocally connected aromatic rings. The mol­ecular structure of the third mol­ecule was previously considered provisional. These com­pounds were isolated as by-products in the synthesis of similar products and were at the same time nanocrystalline and available only in very limited amounts. 3D electron diffraction data, taken from submicrometric single crystals, allowed for direct ab initio structure solution and the unbiased determination of the inter­nal mol­ecular conformation. Detailed synthetic routes and spectroscopic analyses are also discussed. Based on many-body perturbation theory simulations, benzo[e]di­naphtho­[2,3-a;1',2',3',4'-ghi]fluoranthene may be a promising candidate for triplet–triplet annihilation and 7,14-di­phenyl­naphtho­[1,2,3,4-cde]bis­anthene may be a promising candidate for inter­molecular singlet fission in the solid state.

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 OSTI2023

A deep learning upscaling framework: Reactive transport and mineral precipitation in fracture-matrix systems

Pore-scale modeling has limited applicability at large scales due to its high computational cost. One common approach to upscale pore-scale models is the use of effective medium theories, which homogenize small-scale features in a porous structure and characterize the medium by macroscale properties (e.g., permeability) and equations (e.g., Darcy’s law). However, there are classes of physical processes for which effective medium approximations may become inaccurate, e.g., mineral precipitation and clogging during reactive transport. We have developed a deep learning upscaling framework, in which pore-scale modeling is directly employed in macroscale systems, without relying on effective medium approximations. The upscaling framework is first developed for general multiscale systems and then applied to modeling reactive transport with mineral precipitation in the altered layer in fracture-matrix structures. Solute transport from the fractures to the matrix is modeled as a wall boundary condition for the fractures, which, in turn, is predicted by recurrent neural networks using the concentration histories at the fracture-matrix boundary. Specifically, we consider a meter-scale fracture network embedded in sandstones, where the smallest feature is at the micron scale. Here the proposed framework allows us to span five orders of magnitude in length scales by capturing mineral precipitation in the altered layer of the rock matrix at the pore scale across the entire meter-scale fracture network.

42 ENGINEERING↗
DOE OSTI2023

Structural insights into protection against a SARS-CoV-2 spike variant by T cell receptor diversity

T cells play a crucial role in combatting SARS-CoV-2 and forming long-term memory responses to this coronavirus. The emergence of SARS-CoV-2 variants that can evade T cell immunity has raised concerns about vaccine efficacy and the risk of reinfection. Some SARS-CoV-2 T cell epitopes elicit clonally restricted CD8 + T cell responses characterized by T cell receptors (TCRs) that lack structural diversity. Mutations in such epitopes can lead to loss of recognition by most T cells specific for that epitope, facilitating viral escape. Here, we studied an HLA-A2–restricted spike protein epitope (RLQ) that elicits CD8 + T cell responses in COVID-19 convalescent patients characterized by highly diverse TCRs. We previously reported the structure of an RLQ-specific TCR (RLQ3) with greatly reduced recognition of the most common natural variant of the RLQ epitope (T1006I). Opposite to RLQ3, TCR RLQ7 recognizes T1006I with even higher functional avidity than the WT epitope. To explain the ability of RLQ7, but not RLQ3, to tolerate the T1006I mutation, we determined structures of RLQ7 bound to RLQ–HLA-A2 and T1006I–HLA-A2. These complexes show that there are multiple structural solutions to recognizing RLQ and thereby generating a clonally diverse T cell response to this epitope that assures protection against viral escape and T cell clonal loss.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Solving high-dimensional partial integral differential equations: The finite expression method

Partial integro-differential equations (PIDEs) have broad applications in the sciences, from electro-magnetism to options pricing. Here, in this paper, we introduce a new finite expression method (FEX) to solve PIDEs. This approach builds upon the original FEX and its inherent advantages with new advances: 1) A novel method of parameter grouping is proposed to reduce the number of coefficients in high-dimensional function approximation; 2) A Taylor series approximation method is implemented to significantly improve the computational efficiency and accuracy of the evaluation of the integral terms of PIDEs. The new FEX based method, denoted FEX-PG to indicate the addition of the parameter grouping (PG) step to the algorithm, provides both high accuracy and interpretable numerical solutions, with the outcome being an explicit equation that facilitates intuitive understanding of the underlying solution structures. These features are often absent in traditional methods, such as finite element methods (FEM) and finite difference methods, as well as in deep learning-based approaches. To benchmark our method against recent advances, we apply the new FEX-PG to solve benchmark PIDEs in the literature. In high-dimensional settings, FEX-PG exhibits strong and robust performance, achieving relative errors on the order of single precision machine epsilon, significantly outperforming existing approaches based on neural networks.

Combinatorial optimization↗
DOE OSTI2025

Spontaneous sodium ion storage behaviors of reduced graphene oxide anodes exceeding 100% Coulombic efficiency by modulated ion solvation

Rechargeable batteries are essential energy storage devices that power portable devices and electrical vehicles throughout the world. In general, it is thought that the electrochemical performance of rechargeable batteries is mostly determined by the electrodes within them and that the electrolyte plays a relatively passive role. However, ion transport and storage can be greatly influenced by the electrolyte solution structure, specifically, ion solvation within the bulk and ion desolvation across the electrode/electrolyte interfaces. Herein, we studied the role of the electrolyte as an active component of electrochemical energy storage devices. We found that with an appropriate electrolyte formulation, ion storage in disordered carbonaceous anode materials can occur spontaneously without externally supplied electrical energy. Reduced graphene oxide (RGO) in an ether-based electrolyte demonstrates ‘spontaneous' ion storage behaviors of adsorbing and inserting the solvated ions utilizing facilitated permeability and wettability of RGO, which results in Coulombic efficiency of ~145% due to additional charging capacity of ~180 mAh g -1 during electrochemical processes. The unexpected spontaneous ion storage behavior was extensively investigated using a combination of electrochemical analyses and diagnostics, advanced characterizations, and computational simulation. In conclusion, we believe the spontaneous ion storage behavior offers a new way to further improve the energy efficiency of practical rechargeable batteries.

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

Reactions of Studtite UO 4 ·4H 2 O in Alkali Hydroxides: Isolation of Single-Crystal Uranate Phases under Mild Hydrothermal Conditions

Uranyl peroxide complexes, particularly studtite (UO 4 ·4H 2 O), are important phases within the nuclear fuel cycle, forming through radiolysis-induced reactions on the surfaces of spent fuel and in waste environments. Studtite has been identified in Hanford’s irradiated fuel storage basins, Chornobyl’s corium lavas, and is anticipated on Fukushima’s fuel debris. While its formation and stability have been extensively studied, the reactivity of UO 4 ·4H 2 O in highly alkaline environments such as those encountered in high-level nuclear waste remains underexplored. These environments contain molar concentrations of [OH - ] and present a chemically dynamic and reactive environment where actinide behavior is not well understood. Reported here are investigations of uranium reactions in concentrated alkali hydroxides under mild hydrothermal conditions (<200 °C) that have resulted in the isolation of the alkali metal uranates Li 2 UO 4 , α-Na 2 UO 4 , γ-Na 2 U 2 O 7 , and K 2 U 2 O 7 . In contrast to conventional solid-state methods (>800 °C) that typically yield polycrystalline powders, our approach enables the isolation of these uranates as single crystals, allowing us to provide single-crystal structure solutions of certain uranates for the first time. Our findings match the results of high-level waste tank sampling, confirming that sodium diuranate (Na 2 U 2 O 7 ) is the most persistent uranium phase, potentially forming through reactions of uranyl peroxide intermediates with NaOH under radiolytic and highly alkaline conditions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Determining the Three-Dimensional Structures of Silica-Supported Metal Complexes from the Ground Up

The immobilization of molecularly precise metal complexes to substrates, such as silica, provides an attractive platform for the design of active sites in heterogeneous catalysts. Specific steric and electronic variations of the ligand environment enable the development of structure–activity relationships and the knowledge-driven design of catalysts. At present, however, the three-dimensional environment of the precatalyst, much less the active site, is generally not known for heterogeneous single-site catalysts. We explored the degree to which NMR-based surface-to-complex interatomic distances could be used to solve the three-dimensional structures of three silica-supported metal complexes. Furthermore, the structure solution revealed unexpected features related to the environment around the metal that would be difficult to discern otherwise. This approach appears to be highly robust and, due to its simplicity, is readily applied to most single-site catalysts with little extra effort.

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

Permittivity Threshold and Thermodynamics of Integer Charge-Transfer Complexation for an Organic Donor–Acceptor Pair

Molecular or chemical-based charge doping provides a means to change the properties (e.g. conductivity) of a material through a complete or partial transfer of charge between its constituents. Understanding how local material environment impacts this process is thus important for controlling the properties of organic materials. This paper presents spectroscopic investigations of molecular charge transfer interactions between a pair of common charge-doping and -transporting materials (2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane, F4TCNQ, and N,N’-Diphenyl-N-N’-di-p-tolylbenzene-1,4-diamine, MPDA). Equilibrium constants associated with charge transfer were determined for donor-acceptor pairs dissolved in a series of solvents covering a range of values of permittivity. A threshold for highly favorable charge separation was observed to occur at a permittivity of ~8-9, with more and less favorable charge separation observed in solvents of higher and lower permittivity, respectively, but with chloroform (permittivity=4.81) exhibiting an anomalously favorable charge separation. Temperature-dependent studies were undertaken to assess the thermodynamics of charge separation. In 1,2- dichloroethane (permittivity=10.36) and chlorobenzene (permittivity=5.62), charge transfer was observed to be both enthalpically and entropically favorable. Charge separation in chloroform is exothermic and entropically disfavored, indicating that specific, inner-shell solvent-solute interactions stabilize the charge-separated complex and result in a net increase in local solution structure. Furthermore, our results provide insight on how modification to the chemical environment may be utilized to support stable charge transfer for molecular doping applications and requiring only modest changes in local permittivity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Localized Hydrophobicity in Aqueous Zinc Electrolytes Improves Zinc Metal Reversibility

The rechargeability of aqueous zinc metal batteries is plagued by parasitic reactions of the zinc metal anode and detrimental morphologies such as dendritic or dead zinc. To improve the zinc metal reversibility, hereby we report a new solution structure of aqueous electrolyte with hydroxyl-ions scavengers and hydrophobicity localized in solvent clusters. In this work we show that although hydrophobicity sounds counterintuitive for an aqueous system, hydrophilic pockets may be encapsulated inside a hydrophobic outer layer and a hydrophobic anode-electrolyte interface can be generated through the addition of a cation-philic, strongly anion-phobic, and OH - -reactive diluent. The localized hydrophobicity enables less active water and less absorbed water on the Zn anode surface, which suppresses the parasitic water reductions; while the hydroxyl-ion-scavenging functionality further minimizes undesired passivation layer formation, thus leading to superior reversibility (an average Zn plating/stripping efficiency of 99.72% for 1000 cycles) and lifetime (80.6% capacity retention after 5000 cycles) of zinc batteries.

25 ENERGY STORAGE↗
DOE OSTI2026

Site-Selective Modification of Lanthanum Oxychloride to Modulate Halide-Ion Conduction

Design principles for solid-state halide-ion conduction remain poorly defined despite the increasing importance of halide ions as charge carriers in a variety of energy storage and electrochemical computing technologies. Here, we employ a siteselective modification strategy in which aliovalent cations are preferentially introduced at the La 3+ crystallographic site of LaOCl in the 2c Wyckoff position, enabling controlled generation of chloride vacancies and modification of lattice dynamics to enhance chloride-ion conductivity. Aliovalent substitution of La 3+ with Mg 2+ , Ca 2+ , and Sr 2+ generates charge-compensating Cl vacancies while preserving the matlockite crystal structure. X-ray excited optical luminescence measurements with Dy 3+ as a reporter chromophore evidence vacancy-derived midgap electronic states and an extended energy range of radiation-less Auger electron emission corresponding to substantial modification of electronic structure and local electrostatic potentials. Ca alloying at 8−10 at. % increases the chloride-ion conductivity by three- to 4 orders of magnitude as compared to unalloyed LaOCl, whereas comparable amounts of Sr- and Mg-alloying in LaOCl imbue less pronounced conductivity enhancements. Temperature-dependent Raman spectroscopy measurements reveal that Ca- and Sr-alloying substantially soften the La−Cl sublattice and yield a more compliant crystal lattice that can deform to accommodate Cl-ion migration. Structure solutions derived from Rietveld refinements to powder Xray diffraction reveal larger O−La−Cl bond-angle deviations and enhanced out-of-plane cation displacements for Ca- and Sr-alloyed compositions as compared to Mg-alloyed LaOCl. Such local distortions enhance chloride-ion mobility by reshaping and flattening vacancy migration energy landscapes and by modulating lattice dynamics governing anion conduction. We further illustrate that coalloying of Ca with Mg and Sr induces a nonmonotonic conductivity−defect stoichiometry relationship that can be rationalized based on cooperative interactions. Together, these results establish site-selective aliovalent alloying of LaOCl as an effective route to halide-ion solid electrolytes and provide broadly generalizable design principles for site-selective modification to induce vacancy formation and lattice softening to engender facile anion transport

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

Powder diffraction

Powder diffraction is a non-destructive technique, which is experimentally simple in principle. Because the physics behind diffraction is well understood, an exceptionally large amount of information can be obtained from a single measurement. The positions and relative intensities of the peaks yield a fingerprint that can be used for qualitative phase analysis. Quantitative phase analysis can be obtained by detailed analysis of the intensities. Unit cells can be derived from the peak positions. Crystal structures can be solved using powder diffraction data and refined by the Rietveld method. The peak profiles contain information about crystallite size, strain and nanostructure. Non-idealities in the intensities give information on texture. Abandoning the crystallographic model provides information about local structure, by pair distribution function analysis. For powder diffraction, everything is a sample; the technique is commonly applied to characterize minerals, ceramics, metals and alloys, catalysts, polymers, pharmaceuticals, organic compounds, environmental and forensic samples, among others. The major features of contemporary laboratory powder diffractometers are described. Methods for obtaining suitable powder specimens are summarized. Major applications of qualitative and quantitative phase analysis, structure solution, size/strain/nanostructure analysis using peak profiles, texture analysis and pair distribution function analysis are introduced.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Cation coordination polyhedra lead to multiple lengthscale organization in aqueous electrolytes

Understanding multiple lengthscale correlations in the pair distribution functions (PDFs) of aq. electrolytes is a persistent challenge. Here, the coordination chemistry of polyoxoanions supports an ion-network of cation-coordination polyhedra in NaNO 3(aq) and NaNO 2(aq) that induce long-range solution structure. Further, oxygen correlations associated with Na + -coordination polyhedra have two characteristics lengthscales; 3.5–5.5 Å and 5.5–7.5 Å, the latter solely associated oligomers. The PDF contraction between 5.5–7.5 Å observed in many electrolytes is attributed to the distinct O···O correlation found in dimers and dimer subunits within oligomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗