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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Diffractive Imaging of Conical Intersections Amplified by Resonant Infrared Fields

The fate of virtually all photochemical reactions is determined by conical intersections. These are energetically degenerate regions of molecular potential energy surfaces that strongly couple electronic states, thereby enabling fast relaxation channels. Their direct spectroscopic detection relies on weak features that are often buried beneath stronger, less interesting contributions. For azobenzene photoisomerization, a textbook photochemical reaction, we demonstrate how a resonant infrared field can be employed during the conical intersection passage to significantly enhance its coherence signatures in time-resolved Xray diffraction while leaving the product yield intact. Furthermore, this transition-state amplification holds promise to bring signals of conical intersections above the detection threshold.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Direct observations of shock-induced melting in a porous solid using time-resolved x-ray diffraction

Here in this work we provide direct evidence of shock-induced melting and associated kinetics in a porous solid (aluminum powder) using time-resolved x-ray diffraction. Unambiguous evidence of melting in 50% porous aluminum (Al) powder samples, shocked to peak pressures between ~13 - 19 GPa, was provided by the broadening of the Debye-Scherrer ring corresponding to the (111) peak. Shocked Al powder did not melt completely in any of our experiments within the durations of measurement. Incomplete (partial) melting of the powder, even after several hundreds of nanoseconds of shock loading, provides insights into thermal transport with Al powder particles under high-pressure dynamic loading. Such insights are quite valuable for developing well-constrained melting models and thermodynamic equations of state for porous Al and other porous solids relevant to planetary and materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Diffraction Methods for Qualitative and Quantitative Texture Analysis of Ferroelectric Ceramics

Crystallographic textures are pervasive in ferroelectrics and underpin the functional properties of devices utilizing these materials because many macroscopic properties (e.g., piezoelectricity) require a non-random distribution of dipoles. Inducing a preferred grain texture has become a viable route to improve these functional properties. X-ray and neutron diffraction have become valuable tools to probe crystallographic textures. This paper presents an overview of qualitative and quantitative methods for assessing crystallographic textures in electroceramics (domain and grain textures) and discusses their strengths and weaknesses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Virtual diffraction simulations using the quasi-coarse-grained dynamics method to understand and interpret plasticity contributions during in situ shock experiments

The dynamic deformation response of metallic materials has contributions from dislocations, deformation twinning, and plastic deformation. The current state-of-art techniques can detail the complex mechanistic history of deformation modes under shock loading in real-time using in situ X-ray diffraction (XRD). However, the capability of these experiments to unravel plasticity contributions is challenging due to limitations in interpreting results and the lack of validation from atomistic simulations. Molecular dynamics (MD) simulations can successfully capture various deformation modes in metals and complement experiments using simulated diffractograms at various stages of evolution. However, the difference in length and time scales of MD simulations and experiments is a substantial obstacle in completing and interpreting in situ diffractograms. Therefore, the existing modeling methods require various approximations to model defect evolution and interaction at the mesoscales. However, while using approximations to correlate the peak broadening behavior to the density of dislocations or the shifts/splitting due to the presence of twins, the interpretations of the plasticity contributions from diffractograms are non-trivial, especially when multiple modes of deformation may be operating. This viewpoint discusses combining a mesoscale modeling method called quasi-coarse-grained dynamics and virtual XRD to characterize the plasticity contributions in BCC metals from slip, twinning, and phase transformation behavior. Furthermore, the combined approach shows promise in bridging the mesoscale gap between the capabilities of atomic-scale simulations and in situ experiments to characterize the dynamic deformation of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

X-ray diffraction, differential scanning calorimetry and evolved gas analysis of aged plutonium tetrafluoride (PuF4)

A 30 year-old PuF4 sample consisting of brown powder (PuF4-b) and pink granules (PuF4-p) was analyzed. X-ray difraction shows the bulk is comprised of three compounds: PuF4, PuO2, and PuF4·1.6H2O. Broadening of PuF4 XRD peaks suggests possible a-damage. After annealing at 650 °C, crystalline PuF4 and PuO2 remain. Thermogravimetric analysis and diferential scanning calorimetry—with simultaneous evolved gas analysis—of the separated PuF4-p and PuF4-b components reveal a distinct sequence of reactions. Dehydration occurs between~90 and 300 °C. Exothermic annealing of the a-damage occurs in two stages: at 350–355 °C and at 555–558 °C. Hydrofuoric acid, fuorine and helium desorb during the frst exotherm. Above 700 °C, PuF4 reacts with PuO2, resulting in oxygen release and mass loss.

PuF4, dsc, differential scanning calorimetry, plut↗
DOE OSTI2020

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal–organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. Furthermore, this CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Phase Transitions in Metal–Organic Frameworks Directly Monitored through In Situ Variable Temperature Liquid-Cell Transmission Electron Microscopy and In Situ X-ray Diffraction

Zr 6 -based metal–organic frameworks (MOFs) with tetratopic organic linkers have been extensively investigated owing to their versatile structural tunability. While diverse topologies and polymorphism in the resulting MOFs are often encountered with tetratopic linkers and Zr 6 nodes, reports on phase transitions within these systems are rare. Thus, we have a limited understanding of polymorph transformations, hindering the rational development of pure phase materials. In this study, a phase transition from a microporous MOF, scu-NU-906, to a mesoporous MOF, csq-NU-1008, was discovered and monitored through in situ variable temperature liquid-cell transmission electron microscopy (VT-LCTEM), high-resolution transmission electron microscopy (HRTEM), and in situ variable temperature powder X-ray diffraction (VT-PXRD). Furthermore, it was found that the microporous- to-mesoporous transformation in the presence of formic acid occurs via a concomitant dissolution–reprecipitation process.

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

In situ synchrotron diffraction of pressure-induced phase transition in DyPO 4 under variable hydrostaticity

In situ synchrotron x-ray diffraction was conducted on polycrystalline DyPO 4 to elucidate the details of the pressure-induced transition from the xenotime polymorph to the monazite polymorph. We used three different pressure-transmitting media (neon, a 16:3:1 methanol-ethanol-water mixture, and potassium chloride) to investigate the effect of hydrostaticity on the phase behavior. Specifically, our data clearly show a hydrostatic onset pressure of the xenotime-monazite transition of 9.1 GPa, considerably lower than the 15.3 GPa previously determined by Raman spectroscopy. Based on (quasi)hydrostatic data taken in a neon environment, third-order Birch-Murnaghan equation-of-state fits give a xenotime bulk modulus of 144 GPa and a monazite bulk modulus of 180 GPa (both with pressure derivatives of 4.0). Structural data and axial compressibilities show that DyPO 4 is sensitive to shear and has an anisotropic response to pressure. More highly deviatoric conditions cause the onset of the transition to shift to pressures at least as low as 7.0 GPa. We attribute early transition to shear-induced distortion of the PO4 tetrahedra. Finally, our characterization of the high-pressure behavior of DyPO 4 under variable hydrostaticity is critical for advancing rare earth orthophosphate fiber coating applications in ceramic matrix composites and may inform future tailoring of phase composition for controlled shear and pressure applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

X-Ray Diffraction and Electron Microscopy Studies of the Size Effects on Pressure-Induced Phase Transitions in CdS Nanocrystals

In recent years, investigations of the phase transition behavior of semiconducting nanoparticles under high pressure has attracted increasing attention due to their potential applications in sensors, electronics, and optics. However, current understanding of how the size of nanoparticles influences this pressure-dependent property is somewhat lacking. In particular, phase behaviors of semiconducting CdS nanoparticles under high pressure have not been extensively reported. Therefore, in this work, CdS nanoparticles of different sizes are used as a model system to investigate particle size effects on high-pressure-induced phase transition behaviors. In particular, 7.5, 10.6, and 39.7 nm spherical CdS nanoparticles are synthesized and subjected to controlled high pressures up to 15 GPa in a diamond anvil cell. Analysis of all three nanoparticles using in-situ synchrotron wide-angle X-ray scattering (WAXS) data shows that phase transitions from wurtzite to rocksalt occur at higher pressures than for bulk material. Bulk modulus calculations not only show that the wurtzite CdS nanomaterial is more compressible than rocksalt, but also that the compressibility of CdS nanoparticles depends on their particle size. Furthermore, sintering of spherical nanoparticles into nanorods was observed for the 7.5 nm CdS nanoparticles. Our results provide new insights into the fundamental properties of nanoparticles under high pressure that will inform designs of new nanomaterial structures for emerging applications.

Meng, Lingyao↗