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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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BaMn 3 Ti 4 O 14+δ ( δ = 0.25, BMT-134), a recently discovered single-phase multiferroic complex oxide was doped with varying concentrations of Fe in order to assess the effect on magnetic and dielectric behavior.
Fluorite-structured ferroelectrics, such as hafnium oxide and its alloyed variants, are key candidates for next-generation memory devices. Yet, fundamental questions about switching mechanisms, domain dynamics, and phase evolution remain open. Transmission electron microscopy (TEM) provides unique capabilities to address these challenges by simultaneously resolving the positions of anions and cations, chemical variations, and structural transformations. Recent advances—including in situ heating, electron beam-induced switching, electron energy loss spectroscopy, and differential phase contrast imaging—have revealed critical insights into phase transitions, potential switching pathways, and oxygen vacancy behavior. However, experimental barriers such as TEM sample-preparation-induced artifacts, high coercive fields, and imaging constraints persist, especially for polycrystalline films. By offering a focused overview of current TEM developments in fluorite ferroelectrics, this work outlines how TEM contributes to understanding key phenomena and proposes a roadmap for future studies.
This is a dataset consisting of 33 GB of .png image files, each featuring a two-dimensional distribution of different element species captured an individual slice of the specimen, and .ang files that capture microstructural information captured from each respective slice using a technique called electron backscatter diffraction. The .ang files can be processed to visualize alloy grains captured in a respective slice.
Abstract not provided.
Polymer composites are being considered for numerous thermal applications because of their inherent benefits, such as light weight, corrosion resistance, and reduced cost. In this work, the microstructural, thermal, and mechanical properties of a 3D printed polymer composite with high thermal conductivity are examined using multiple characterization techniques. Infrared spectroscopy and X-ray diffraction reveal that the composite contains a polyphenylene sulfide matrix with graphitic fillers, which is responsible for the high thermal conductivity. Furthermore, differential scanning calorimetry determines that the glass transition and melting point of the composite are 87.6 °C and 285.6 °C, respectively. Thermogravimetric analysis reveals that the composite is thermally stable up to ~400 °C. Creep tests are performed at different isotherms to evaluate the long-term performance of the composite. The creep result indicates that the composite can maintain mechanical integrity when used below its glass transition temperature. Nanoindentation tests reveal that modulus and hardness of the composite is not significantly influenced by heating or creep conditions. These findings indicate that the composite is potentially suitable for heat exchanger applications.
Understanding the grain morphology, orientation distribution and crystal structure of nanocrystals is essential for optimizing the mechanical and physical properties of functional materials. Synchrotron X-ray Laue microdiffraction is a powerful technique for characterizing crystal structures and orientation mapping using focused X-rays. However, when the grain sizes are smaller than the beam size, mixed peaks in the Laue pattern from neighboring grains limit the resolution of grain morphology mapping. We propose a physics-informed machine learning (PIML) approach that combines a convolutional neural network feature extractor with a physics-informed filtering algorithm to overcome the spatial resolution limits of X-rays, achieving nanoscale resolution for grain mapping. Our PIML method successfully resolves the grain size, orientation distribution and morphology of Au nanocrystals through synchrotron microdiffraction scans, showing good agreement with electron backscatter diffraction results. This PIML-assisted synchrotron microdiffraction analysis can be generalized to other diffraction-based probes, enabling the characterization of nanosized structures with micrometre-sized probes.
Bond valence sum analysis is a powerful tool used in evaluating and validating crystal structures; especially when those structures are complex in nature. The pyrochlore structure type is versatile in not only the unique bonding that it exhibits, but also in the properties that results from the structure. Here this paper aims to center the discussion of evaluating the pyrochlore structure using the bond valence sum method. In this study, novel quaternary pyrochlores with a general stoichiometry of ABiMTeO 7 (A = Cd, Ca; M = Cr, Ga, Sc, In, Fe) were synthesized and characterized for their structural, magnetic, and dielectric properties. Two representative compounds within this series of pyrochlores, BiCaFeTeO7 and BiCdFeTeO 7 , were structurally characterized utilizing a combination of high-resolution synchrotron X-ray diffraction and neutron diffraction revealing oxygen deficient pyrochlore systems which were off from the expected stoichiometry with respect to the M site. The A site of both pyrochlores were found to be moved off-center from the expected 16d site to the 96h displaced position at a magnitude of 0.25 Å and 0.22 Å for the Bi/Ca and Bi/Cd systems, respectively. These structures were evaluated using the bond valence sum method and compared with trends in the literature. The properties are also reported for the Bi/Ca system for the first time, showing relatively high dielectric constants with a low dielectric loss which are primarily independent of frequency and temperature. The magnetic measurements for the Bi/Ca system for the magnetic substitutions reveal a paramagnet and antiferromagnetic properties for the Fe and Cr analogs, respectively. The novel BiCaMTeO 7 quaternary pyrochlore system shows great promise as an emerging dielectric material.
Single-crystal X-ray diffraction and electron paramagnetic resonance (EPR) spectroscopic experiments, complemented by quantum chemical DFT calculations, were carried out on the copper-doped metal–organic hybrid and Tutton salt analogue zinc creatininium sulfate to determine its crystal structure, to characterize the electronic structure of the doped Cu(II) binding site, and to propose a pathway for an excited-state, proton-coupled electron transfer (PCET) process in UV-exposed crystals. The crystal structure is isomorphous to that of cadmium creatininium sulfate, which has the transition ion, not in direct coordination with the creatinine, but forming a hexahydrate complex, which is bridged to a creatininium through an intervening sulfate ion. The EPR g (2.446, 2.112, 2.082) and copper hyperfine (A Cu : -327, -59.6, 10.8 MHz) tensor parameters are consistent with doped copper replacing host zinc in the metal–hexahydrate complex. These parameters are similar to those observed for copper hexahydrate in doped Tutton salt systems at low temperature, where the unpaired electron occupies mainly the copper 3d x 2 –y 2 orbital. At room temperature in the Tutton systems, vibration couplings stemming from a dynamic Jahn–Teller effect cause tensor averaging which results in a reduction in their maximum g-tensor and hyperfine tensor values. However, like for the doped isomorphous Cd creatinine crystal, the Cu(II) EPR exhibits little, or no room temperature averaging compared to its low temperature pattern. Samples exposed to 254 nm UV light generate a carbon-centered free radical species, characterized by an isotropic g-tensor (g = 2.0029) and an alpha-proton hyperfine coupling (-24 -14 +4 G). These parameters identify it as a creatinine radical cation formed by the oxidative release of one of its C2 methylene hydrogens. DFT calculations confirm the unpaired electronic structures of both the Cu(II) site and free radical. The growth in radical concentration with an increase in the UV exposure time coincides with a decrease in the copper EPR signal, indicating a coupled light-induced oxidation reduction process. A comparison of the crystal structure with the EPR parameters and DFT results provides evidence for a UV-induced PCET.
While significant research has investigated the processing and properties of high-performance terpolymer fibers, much remains to be understood about the internal nano- and microstructures of these fibers, and how these morphologies relate to fiber properties. Here we use a focused ion beam notch technique and multifrequency atomic force microscope mapping to characterize the internal structure and local mechanical properties within Technora ® fibers. We find a highly fibrillated structure that appears to connect with both the fiber’s molecular chemistry and full-fiber mechanical properties. In addition, through detailed comparisons with Kevlar ® K29 fibers, we find remarkable differences between the internal structures of the two fibers, and posit connections between our measurements and multifunctional performance studies from the literature.
Lithium (Li) metal batteries (LMBs) are among the most promising candidates of next-generation high-energy-density rechargeable batteries. Solid electrolyte interphase (SEI) on Li metal anode plays a significant role which influences the Li deposition morphology and the cycle life of LMBs. Although SEI is the most important part, a thorough understanding of SEI is inadequate. In this review, we focus on the progresses of understanding on structures, properties and influencing factors of SEI as well as efficient strategies of tailoring SEI. First, the compositions, models and recent progresses on characterizing atomic structure of SEI are summarized. Second, the properties of SEI, including electronic conduction, ionic conduction, stability and mechanical properties are elucidated. Structures and properties of SEI are greatly influenced by multiple factors such as solvent, salt, additive, solvation structure, impurity, current density, temperature, pressure and capacity utilization. Thus, interactions between these factors and SEI are comprehensively discussed. Correlations of SEI with Li deposition morphology, rate capability and cycle life are further summarized. Moreover, efficient strategies of tailoring SEI with desired properties, including in-situ SEI and ex-situ SEI are also reviewed. Despite the significant progresses that have been achieved in the researches of SEI, better understanding of SEI is still highly demand. Finally, future directions especially in-operando techniques, multi-modality approaches for characterization of SEI and artificial intelligence assisted understanding of correlation between electrolyte components and SEI properties are proposed.
Structural and electronic characterization of (Cp' 3 Cm) 2 (μ–4,4'–bpy) (Cp' = trimethylsilylcyclopentadienyl, 4,4'–bpy = 4,4'–bipyridine) is reported and provides a rare example of curium–carbon bonding. Cp' 3 Cm displays unexpectedly low energy emission that is quenched upon coordination by 4,4'–bipyridine. Electronic structure calculations on Cp' 3 Cm and (Cp' 3 Cm) 2 (μ–4,4'–bpy) rule out significant differences in the emissive state, rendering 4,4'–bipyridine as the primary quenching agent. Comparisons of (Cp' 3 Cm) 2 (μ–4,4'–bpy) with its samarium and gadolinium analogues reveal atypical bonding patterns and electronic features that offer insights into bonding between carbon with f-block metal ions. Here we show the structural characterization of a curium–carbon bond, in addition to the unique electronic properties never before observed in a curium compound.
Creating a systematic framework to characterize the structural states of colloidal self-assembly systems is crucial for unraveling the fundamental understanding of these systems’ stochastic and non-linear behavior. The most accurate characterization methods create high-dimensional neighborhood graphs that may not provide useful information about structures unless these are well-defined reference crystalline structures. Dimensionality reduction methods are thus required to translate the neighborhood graphs into a low-dimensional space that can be easily interpreted and used to characterize non-reference structures. We investigate a framework for colloidal system state characterization that employs deep learning methods to reduce the dimensionality of neighborhood graphs. The framework next uses agglomerative hierarchical clustering techniques to partition the low-dimensional space and assign physically meaningful classifications to the resulting partitions. In this work, we first demonstrate the proposed colloidal self-assembly state characterization framework on a three-dimensional in silico system of 500 multi-flavored colloids that self-assemble under isothermal conditions. We next investigate the generalizability of the characterization framework by applying the framework to several independent self-assembly trajectories, including a three-dimensional in silico system of 2052 colloidal particles that undergo evaporation-induced self-assembly.
Capsular polysaccharides are important virulence factors in pathogenic bacteria. Characterizing the structural components and biosynthetic pathways for these polysaccharides is key to our ability to design vaccines and other preventative therapies that target encapsulated pathogens. Many gramnegative pathogens such as Neisseria meningitidis and Escherichia coli express acidic capsules. The E. coli K15 serotype has been identifed as both an enterotoxigenic and uropathogenic pathogen. Despite its relevance as a disease-causing serotype, the associated capsular polysaccharide remains poorly characterized. We describe in this report the chemical structure of the K15 polysaccharide, based on chemical analysis and nuclear magnetic resonance (NMR) data. The repeating structure of the K15 polysaccharide consists of 4)-α-GlcpNAc-(1→5)-α-KDOp-(2→partially O-acetylated at 3-hydroxyl of GlcNAc. We also report, the organization of the gene cluster responsible for capsule biosynthesis. We identify genes in this cluster that potentially encode an O-acetyltransferase, an N-acetylglucosamine transferase, and a KDO transferase consistent with the structure we report.
Here, coarsening of bicontinuous microstructures is observed in a variety of systems, such as nanoporous metals and mixtures that have undergone spinodal decomposition. To better understand the morphological evolution of these structures during coarsening, we compare the morphologies resulting from two different coarsening mechanisms, surface and bulk diffusion. We perform phase-field simulations of coarsening via each mechanism in a two-phase mixture at nominal volume fractions of 50%-50% and 36%-64%, and the simulated structures are characterized in terms of topology (genus density), the interfacial shape distribution, structure factor, and autocorrelations of phase and mean curvature. We observe self-similar evolution of morphology and topology and agreement with the expected power laws for dynamic scaling, in which the characteristic length scale increases over time proportionally to t 1/4 for surface diffusion and t 1/3 for bulk diffusion. While we observe the expected difference in the coarsening kinetics, we find that differences in self-similar morphology due to coarsening mechanism are relatively small, although typically they are larger at 36% volume fraction than at 50% volume fraction. In particular, we find that bicontinuous structures coarsened via surface diffusion have lower scaled genus densities than structures coarsened via bulk diffusion. We also compare the self-similar morphologies to those in literature and to two model bicontinuous structures, namely, constant-mean-curvature surfaces based on the Schoen G minimal surface and random leveled-wave structures. The average scaled mean curvatures of these model structures agree reasonably with those of the coarsened structures at both 36% and 50%, but we find substantial disagreements in the scaled genus densities and the standard deviations of mean curvature.
Nonsymmetrical oxygen-bridged binuclear copper centers have been proposed and modeled as intermediates and transition states in several C–H oxidation pathways, leading to the postulation that structural dissymmetry enhances the reactivity of the bridging oxygen. However, experimentally characterizing the structure and reactivity of these transient species is remarkably challenging. Here, we report the high-pressure synthesis of a metastable nonsymmetrical dicopper-μ-oxo compound with exceptional reactivity toward the mono-oxygenation of aliphatic C–H bonds. The nonequivalent coordination environment of copper stabilizes localized mixed valency and greatly enhances the hydrogen atom abstraction activity of the bridging oxygen, enabling room-temperature hydroxylation of methane under pressure. These findings highlight the role of dissymmetry in the reactivity of binuclear copper centers and demonstrate precise control of molecular structures by mechanical means.
In this Editorial, Guest Editors Run-Cang Sun, Joseph S. M. Samec, and Arthur J. Ragauskas introduce the Special Issue of ChemSusChem on Lignin Valorization: From Theory to Practice. Here, the significance of and enormous challenges for the utilization of lignin are reviewed, and the contents of the Special Issue with highly interesting contributions from scientists around the world are outlined.
A structure–function characterization of Synechococcus elongatus enolase ( Se EN) is presented, representing the first structural report on a cyanobacterial enolase. X-ray crystal structures of Se EN in its apoenzyme form and in complex with phosphoenolpyruvate are reported at 2.05 and 2.30 Å resolution, respectively. Se EN displays the typical fold of enolases, with a conformationally flexible loop that closes the active site upon substrate binding, assisted by two metal ions that stabilize the negatively charged groups. The enzyme exhibits a catalytic efficiency of 1.2 × 10 5 M −1 s −1 for the dehydration of 2-phospho-D-glycerate, which is comparable to the kinetic parameters of related enzymes. These results expand the understanding of the biophysical features of these enzymes, broadening the toolbox for metabolic engineering applications.