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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 397 records · Page 22

Nanoscale Antiferromagnetic Domain Imaging using Full-Field Resonant X-ray Magnetic Diffraction Microscopy

The physical properties of magnetic materials frequently depend not only on the microscopic spin and electronic structures, but also on the structures of mesoscopic length scales that emerge, for instance, from domain formations, or chemical and/or electronic phase separations. However, experimental access to such mesoscopic structures is currently limited, especially for antiferromagnets with net zero magnetization. Here, full-field microscopy and resonant magnetic X-ray diffraction are combined to visualize antiferromagnetic (AF) domains of the spin–orbit Mott insulator Sr 2 IrO 4 with area over ≈0.1 mm 2 and with spatial resolution as high as ≈150 nm. With the unprecedented wide field of views and high spatial resolution, an intertwining of two AF domains on a length comparable to the measured average AF domain wall width of 545 nm is revealed. This mesoscopic structure comprises a substantial portion of the sample surface, and thus can result in a macroscopic response unexpected from its microscopic magnetic structure. In particular, the symmetry analysis presented in this work shows that the inversion symmetry, which is preserved by the microscopic AF order, becomes ill-defined at the mesoscopic length scale. We report this result underscores the importance of this novel technique for a thorough understanding of the physical properties of antiferromagnets.

36 MATERIALS SCIENCE↗

Correction to: Imaging Light–Induced Migration of Dislocations in Halide Perovskites with 3D Nanoscale Strain Mapping

Owing to an error in properly normalizing the reconstruction phase data into atomic displacements, the strain values that we used to calculate the root mean squared local strain, ε rms , and to calculate the fraction of the crystals more strain than 1%, f, quoted in the original paper, are roughly one order of magnitude too large. This error was only discovered recently whilst performing further analysis.

36 MATERIALS SCIENCE↗

A Nanoscale Ternary Amide‐rGO Composite with Boosted Kinetics for Reversible H 2 Storage

Abstract Metal amides are attractive candidates for hydrogen storage due to their high volumetric and gravimetric hydrogen densities. However, the sluggish kinetics and competing side reactions during hydrogen uptake and release limit their practical use. Here, a novel nanoconfined Li 2 Mg(NH) 2 @reduced graphene oxide (rGO) composite is presented, which is fabricated using a melt‐infiltration method with a minimum weight penalty of only 2 wt.%. The presence of rGO ensures close contact between the active phases, effectively preventing aggregation during cycling process. As a result, the reversible capacity of Li 2 Mg(NH) 2 @rGO reaches 4.42 wt.%, with no capacity degradation observed after multiple cycling. Theoretical calculations show that rGO catalyzes the hydrogen bond cleavage at the Mg‐amide/Li hydride interface, leading to local dehydrogenation hotspots and significantly improves kinetics of dehydrogenation compared to the bulk counterpart. This study provides a promising strategy for designing metal imide‐based composites to overcome the kinetic limitations and improve their reversible hydrogen storage performance.

08 HYDROGEN↗

Nanoscale Decoupling of Carrier-Phonon Transport in Carbon Nanotube-Halide Perovskite Heterostructures

In conventional semiconductors, electrical and thermal conductivity are typically coupled, posing a challenge in optimizing both simultaneously. Overcoming this inherent trade-off enables strategies for advancing electronic applications. Herein, a strategy is demonstrated to decouple electrical and thermal conductivity trade-off by creating heterostructures of highly conductive single-walled carbon nanotubes (SWCNTs) coated with low conductivity hybrid perovskites. Coating SWCNTs with methylammonium lead iodide perovskite results in an enhancement in electrical conductivity (408-1266 S cm-1) due to p-type doping followed by a threefold decrease of the in-plane thermal conductivity (3.3-1 W m-1 K-1), compared to pristine SWCNTs. Molecular dynamics simulations uncover phonon boundary scattering at the SWCNT/perovskite interface as well as localization of methylammonium-related and softening of the Pb-I-related phonon modes in methylammonium lead iodide perovskite decreasing the thermal conductivity.

14 SOLAR ENERGY↗

Multimodal Nanoscale Tomographic Imaging for Battery Electrodes

Accurate representations of the 3D structure within a lithium-ion battery are key to understanding performance limitations. However, obtaining exact reconstructions of electrodes, where the active particles, the carbon black and polymeric binder domain, and the pore space are visualized is challenging. In this work, it is shown that multimodal imaging can be used to overcome this challenge. High-resolution ptychographic X-ray computed tomography are combined with lower resolution but higher contrast transmission X-ray tomographic microscopy to obtain 3D reconstructions of pristine and cycled graphite-silicon composite electrodes. This cross-correlation enables quantitative analysis of the surface of active particles, including the heterogeneity of carbon-black and binder domain and solid-electrolyte interphase coverage. Capturing the active particles as well as the carbon black-binder domain allows using these segmented structures for electrochemical simulations to highlight the influence of the particle embedding on local state of charge heterogeneities.

25 ENERGY STORAGE↗

A Three–Dimensional Nanoscale View of Electrocatalyst Degradation in Hydrogen Fuel Cells

The loss of platinum (Pt) electrochemically active surface area (ECSA) is a critical degradation mode that often becomes a limiting factor for heavy-duty proton exchange membrane fuel cell vehicles. High surface area carbon supports have been shown to improve Pt dispersion and limit detrimental ionomer-electrocatalyst interactions due to their large interior pore volume. Here, in this work, using automated scanning transmission electron tomography, the degradation of nanoparticles located on the interior versus exterior surfaces of the carbon support is compared following a catalyst-specific accelerated stress test (AST) of 90,000 voltage cycles between 0.6 V to 0.95 V. The results reveal a notable increase in median particle size for both interior and exterior Pt catalyst particles, with a slightly higher increase in particle size distribution and loss of specific surface area for the particles located on the exterior carbon surface. The fraction of Pt nanoparticles that reside within the interior of the carbon support also increased following the AST test, accompanied by evidence of an increase in average carbon mesopore size. Here, the results shed light on the degradation mechanisms affecting electrochemical properties and the enhanced particle accessibility at lower relative humidity.

08 HYDROGEN↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

Fricke, Sophia N.↗

Deactivation of Cu-Exchanged Automotive-Emission NH 3 -SCR Catalysts Elucidated with Nanoscale Resolution Using Scanning Transmission X-ray Microscopy

To gain insight into the underlying mechanisms of catalyst durability for the selective catalytic reduction (SCR) of NO x with an ammonia reductant, we employed scanning transmission X-ray microscopy (STXM) to study Cu-exchanged zeolites with the CHA and MFI framework structures before and after simulated 135 000-mile aging. X-ray absorption near-edge structure (XANES) measurements were performed at the Al K- and Cu L-edges. The local environment of framework Al, the oxidation state of Cu, and geometric changes were analyzed, showing a multi-factor-induced catalytic deactivation. In Cu-exchanged MFI, a transformation of Cu II to Cu I and Cu x O y was observed. We also found a spatial correlation between extra-framework Al and deactivated Cu species near the surface of the zeolite as well as a weak positive correlation between the amount of CuI and tri-coordinated Al. By inspecting both Al and Cu in fresh and aged Cu-exchanged zeolites, we conclude that the importance of the preservation of isolated Cu II sites trumps that of Brønsted acid sites for NH 3 -SCR activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molten Salts-Driven Discovery of a Polar Mixed-Anion 3D Framework at the Nanoscale: Zn 4 Si 2 O 7 Cl 2 , Charge Transport and Photoelectrocatalytic Water Splitting

Mixed-anion compounds widen the chemical space of attainable materials compared to single anionic compounds, but the exploration of their structural diversity is limited by common synthetic paths. Especially, oxychlorides rely mainly on layered structures, which suffer from low stability during photo(electro)catalytic processes. Herein we report a strategy to design a new polar 3D tetrahedral framework with composition Zn 4 Si 2 O 7 Cl 2 . We use a molten salt medium to enable low temperature crystallization of nanowires of this new compound, by relying on tetrahedral building units present in the melt to build the connectivity of the oxychloride. These units are combined with silicon-based connectors from a non-oxidic Zintl phase to enable precise tuning of the oxygen content. This structure brings high chemical and thermal stability, as well as strongly anisotropic hole mobility along the polar axis. These features, associated with the ability to adjust the transport properties by doping, enable to tune water splitting properties for photoelectrocatalytic H 2 evolution and water oxidation. This work then paves the way to a new family of mixed-anion solids

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multivariate Machine Learning Models of Nanoscale Porosity from Ultrafast NMR Relaxometry

Abstract Nanoporous materials are of great interest in many applications, such as catalysis, separation, and energy storage. The performance of these materials is closely related to their pore sizes, which are inefficient to determine through the conventional measurement of gas adsorption isotherms. Nuclear magnetic resonance (NMR) relaxometry has emerged as a technique highly sensitive to porosity in such materials. Nonetheless, streamlined methods to estimate pore size from NMR relaxometry remain elusive. Previous attempts have been hindered by inverting a time domain signal to relaxation rate distribution, and dealing with resulting parameters that vary in number, location, and magnitude. Here we invoke well‐established machine learning techniques to directly correlate time domain signals to BET surface areas for a set of metal‐organic frameworks (MOFs) imbibed with solvent at varied concentrations. We employ this series of MOFs to establish a correlation between NMR signal and surface area via partial least squares (PLS), following screening with principal component analysis, and apply the PLS model to predict surface area of various nanoporous materials. This approach offers a high‐throughput, non‐destructive way to assess porosity in c.a. one minute. We anticipate this work will contribute to the development of new materials with optimized pore sizes for various applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Complementing Nanoscale Galvanic Exchange with Redox Manipulation toward Architectural Control of Multimetallic Hollow Nanostructures

Galvanic exchange occurring within the confinement by nanoparticulate templates provides a unique pathway to controllably transform solid metallic nanoparticles into architecturally more sophisticated multimetallic hollow nanostructures under facile reaction conditions. As such, in this Minireview, we elaborately discuss how the nanoparticle-templated galvanic exchange can be deliberately coupled with redox manipulation to synthesize a large library of complex multimetallic hollow nanostructures exhibiting precisely tailored architectures and compositions, with a particular emphasis on important mechanistic insights concerning the dynamic interplay among multiple structure-remodeling processes that synergistically dictate the versatile nanoparticle transforming behaviors during kinetically and regioselectively modulated galvanic exchange reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Decahedra and Icosahedra Everywhere: The Anomalous Crystallization of Au and Other Metals at the Nanoscale

Throughout history, objects with fivefold symmetry have been a popular topic of interest for artists, philosophers, and scientists. This may be because fivefold symmetry is very conspicuous in nature. In the case of crystals, fivefold rotational symmetry is mathematically forbidden, and macroscopic crystals exhibiting fivefold symmetry have never been shown to exist. Nevertheless, in the nanoworld, nanoparticles are often found with decahedral and icosahedral shapes that have an overall pseudo–fivefold symmetry. These structures are observed at many length scales, from 1 nm up to 1 µm. In this review, several reasons for the stability of fivefold nanoparticles are discussed. Finally, these include the formation of twin boundaries, surface reconstruction faceting, and other factors.

36 MATERIALS SCIENCE↗

Friction of Metals: A Review of Microstructural Evolution and Nanoscale Phenomena in Shearing Contacts

The friction behavior of metals is directly linked to the mechanisms that accommodate deformation. We examine the links between mechanisms of strengthening, deformation, and the wide range of friction behaviors that are exhibited by shearing metal interfaces. Specifically, the focus is on understanding the shear strength of nanocrystalline and nanostructured metals, and conditions that lead to low friction coefficients. Grain boundary sliding and the breakdown of Hall–Petch strengthening at the shearing interface are found to generally and predictably explain the low friction of these materials. While the following is meant to serve as a general discussion of the strength of metals in the context of tribological applications, one important conclusion is that tribological research methods also provide opportunities for probing the fundamental properties and deformation mechanisms of metals.

36 MATERIALS SCIENCE↗

Effects of three-dimensional Cu/Nb interfaces on strengthening and shear banding in nanoscale metallic multilayers

Manipulation of the atomic-scale structure of two-dimensional (2D) interfaces have been shown to provide nanocomposites with enhanced strength, deformability, and radiation damage resistance. In comparison with 2D interfaces, here we investigate the mechanical response of nanocomposites containing three-dimensional (3D) Cu/Nb interfaces consisting of a chemical/structural gradient separating pure Cu and Nb layers, through which the lattice mismatch between face-centered cubic Cu and body-centered cubic Nb is accommodated over a distance of several nanometers. Furthermore, it is demonstrated that 3D interfaces increase the yield and flow strength by 50% and 22%, respectively, over composites containing 2D interfaces at similar layer thicknesses. After 14% compressive strain, the onset of shear banding results in co-deformation of both Cu and Nb phases within and outside of the shear band. We conclude with a discussion of the role of interface structure in shear band formation and growth in 3D Cu/Nb.

3-dimensional interface↗