Sub-20 nm Hard X-ray Spectromicroscopy Reveals Nanoscale Redox Heterogeneity in Ultrafine Particulates
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Engineering topics
Publications and source records attributed to Yan, Hanfei.
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The concentration gradient is a strategic design, adjusting the distribution of Ni, typically with a higher Ni content in the core and a higher Mn content toward the surface. This design leverages the pivotal role of the Ni/Mn ratio, seeking to optimize cathode performance by balancing Ni's high capacity with Mn's stabilizing effects, particularly at the surface where degradation commonly occurs during cycling. Here, our study delves into the intricate structural and chemical transformations within concentration gradient cathode materials during electrochemical cycling. Utilizing advanced synchrotron X-ray techniques, including hard and soft X-ray absorption spectroscopy (hXAS, sXAS), and nanoscale X-ray imaging, we investigate buried changes in concentration gradient LiNi 0.6 Mn 0.2 Co 0.2 O 2 (CG NMC622). Contrary to conventional assumptions, our findings challenge the notion that cycling stability relies solely on Mn stability. Unraveling the roles of Ni and Mn, we uncover how their individual and collective contributions impact the cathode's overall performance. This investigation transcends established paradigms, shedding light on the crucial mechanisms governing the enhanced cycling stability of Nirich layered cathode materials.
Controlling the three-dimensional (3D) nanoarchitecture of inorganic materials is imperative for enabling their novel mechanical, optical, and electronic properties. Here, by exploiting DNA-programmable assembly, we establish a general approach for realizing designed 3D ordered inorganic frameworks. Through inorganic templating of DNA frameworks by liquid- and vapor-phase infiltrations, we demonstrate successful nanofabrication of diverse classes of inorganic frameworks from metal, metal oxide and semiconductor materials, as well as their combinations, including zinc, aluminum, copper, molybdenum, tungsten, indium, tin, and platinum, and composites such as aluminum-doped zinc oxide, indium tin oxide, and platinum/aluminum-doped zinc oxide. The open 3D frameworks have features on the order of nanometers with architecture prescribed by the DNA frames and self-assembled lattice. Structural and spectroscopic studies reveal the composition and organization of diverse inorganic frameworks, as well as the optoelectronic properties of selected materials. The work paves the road toward establishing a 3D nanoscale lithography.
Bond-orientational order in DNA-assembled nanoparticles lattices is explored with the help of recently introduced Symmetry-specific Bond Order Parameters (SymBOPs). Here, this approach provides a more sensitive analysis of local order than traditional scalar BOPs, facilitating the identification of coherent domains at the single bond level. The present study expands the method initially developed for assemblies of anisotropic particles to the isotropic ones or cases where particle orientation information is unavailable. The SymBOP analysis was applied to experiments on DNA-frame-based assembly of nanoparticle lattices. It proved highly sensitive in identifying coherent crystalline domains with different orientations, as well as detecting topological defects, such as dislocations. Furthermore, the analysis distinguishes individual sublattices within a single crystalline domain, such as pair of interpenetrating FCC lattices within a cubic diamond. The results underscore the versatility and robustness of SymBOPs in characterizing ordering phenomena, making them valuable tools for investigating structural properties in various systems.
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Deep neural network can greatly improve tomography reconstruction with limited data. A recent effort of combining ptycho-tomography model with the 3D U-net demonstrated a significant reduction in both the number of projections and computation time, and showed its potential for integrated circuit imaging that requires high-resolution and fast measurement speed.
Coal combustion byproducts are known to be enriched in arsenic (As) and selenium (Se). This enrichment is a concern during the handling, disposal, and reuse of the ash as both elements can be harmful to wildlife and humans if mobilized into water and soils. The leaching potential and bioaccessibility of As and Se in coal fly ash depends on the chemical forms of these elements and their association with the large variety of particles that comprise coal fly ash. The overall goal of this research was to determine nanoscale and microscale solid phase mineral associations and oxidation states of As and Se in fly ash. We utilized nanoscale 2D imaging (30–50 nm spot size) with the Hard X-ray Nanoprobe (HXN) in combination with microprobe X-ray capabilities (~5 μm resolution) to determine the As and Se elemental associations. Speciation of As and Se was also measured at the nano- to microscale with X-ray absorption spectroscopy. The enhanced resolution of HXN showed As and Se as either diffusely located around or comingled with Ca- and Fe-rich particles. The results also showed nanoparticles of Se attached to the surface of fly ash grains. Overall, a comparison of As and Se species across scales highlights the heterogeneity and complexity of chemical associations for these trace elements of concern in coal fly ash.
Abstract X-ray fluorescence mapping (XRF) is a highly efficient and non-invasive technique for quantifying material composition with micro and nanoscale spatial resolutions. Quantitative XRF analysis, however, confronts challenges from the long-lasting problem called self-absorption. Moreover, correcting two-dimensional XRF mapping datasets is particularly difficult because it is an ill-posed inverse problem. Here we report a semi-empirical method that can effectively correct 2D XRF mapping data. The correction error is generally less than 10% from a comprehensive evaluation of the accuracy in various configurations. The proposed method was applied to quantify the composition distribution around the grain boundaries in an electrochemically corroded stainless steel sample. Highly localized Cr enrichment was found around the crack sites, which was invisible before the absorption correction.
In volume visualization transfer functions are widely used for mapping voxel properties to color and opacity. Typically, volume density data are scalars which require simple 1D transfer functions to achieve this mapping. If the volume densities are vectors of three channels, one can straightforwardly map each channel to either red, green or blue, which requires a trivial extension of the 1D transfer function editor. Here, we devise a new method that applies to volume data with more than three channels. These types of data often arise in scientific scanning applications, where the data are separated into spectral bands or chemical elements. Our method expands on prior work in which a multivariate information display, RadViz, was fused with a radial color map, in order to visualize multi-band 2D images. In this work, we extend this joint interface to blended volume rendering. The information display allows users to recognize the presence and value distribution of the multivariate voxels and the joint volume rendering display visualizes their spatial distribution. We design a set of operators and lenses that allow users to interactively control the mapping of the multivariate voxels to opacity and color. This enables users to isolate or emphasize volumetric structures with desired multivariate properties. Furthermore, it turns out that our method also enables more insightful displays even for RGB data. We demonstrate our method with three datasets obtained from spectral electron microscopy, high energy X-ray scanning, and atmospheric science.
We report a polyvinyl alcohol anion exchange resin composite membrane, functionalized with Co and Cu ions, is reported for use in direct borohydride fuel cells (DBFCs). The CoCu-functionalized membrane has a 30.5% lower fuel permeability than that of a blank membrane. Meanwhile, the cell performance of the DBFC can also be improved by employing the CoCu-functionalized membrane, reaching a maximum power density of 304 mW·cm –2 at 60 °C. High-resolution fluorescence images directly demonstrate the formation of Cu/Co core–shell structure microparticles in the CoCu membrane, which not only reduces the Co content but also increases the active surface area of Co species in CoCu-functionalized membranes, resulting in the improvement of cell performance.