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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 37 records · Page 2

Connecting particle interactions to agglomerate morphology and rheology of boehmite nanocrystal suspensions

Rheology imposes significant challenges on processing of complex suspensions such as nuclear waste slurries at the Hanford and Savannah River sites. Understanding rheology connecting to microstructures and underlying particle interactions in complex slurries is therefore important for both fundamental knowledge and practical applications. Here, we use suspensions of aluminum oxyhydroxide minerals in the form of boehmite as an analog of the radioactive waste slurry to gain physical insights on the correlation between particle interactions, microstructures, and slurry rheology. Specifically, we use a combination of Couette rheometry and small-angle scattering techniques (independently and simultaneously) to understand how the slurry microstructure changes under flow and how these structural changes manifest themselves in the bulk rheology of the suspensions. Our experiments show that the boehmite slurries are thixotropic, with the rheology and structure of the suspensions changing with increasing exposure to flow. In the slurries, particle aggregates begin as loose, system-spanning clusters, but exposure to moderate shear rates causes the aggregates to irreversibly consolidate into denser clusters of finite size. The microstructural changes directly influence the rheological properties of the slurries such as viscosity and viscoelasticity. More importantly, our study shows that solution pH affects the amount of structural rearrangement and the kinetics of the rearrangement process, with an increase in pH leading to faster and more dramatic changes in the bulk rheology. Such dynamic microstructural changes and resultant rheology are understood via correlations between particle interactions and strength of particle network, coupled with surface chemistry and anisotropic nature of particle interactions. Nearly identical structural changes are also observed in Poiseuille flow geometries, implying that the observed changes are relevant in the pipe flow conditions present during waste processing.

Weston, Javen S.↗

Phase Behavior and Ionic Conductivity of Blended, Ion-Condensed Electrolytes with Ordered Morphologies

In this study, the amphiphilic salt lithium trifluoromethanesulfonylimide octadecane (C18LiTFSI) was used as a basis to investigate the effects of anion density and cation coordination sites within blended electrolytes with strong ionic aggregation. C18LiTFSI was previously reported as a single-component, ion-condensed electrolyte with a wide layered liquid crystalline phase regime. Three additive molecules with varyingly sized polar sulfonyl groups attached to an octodecane-tail were synthesized and mixed with C18LiTFSI. The thermal properties, morphology, and ionic conductivity of the blended electrolytes were characterized. It was found that the blended electrolytes exhibited layered liquid crystalline morphology over a narrower temperature range than the pure salt, and the ionic conductivity of the blended liquid crystalline electrolytes were generally lower than that of the pure salt. Surprising, the additives were found to have the greatest effect on the bulk ionic conductivity of the semicrystalline phase of the electrolytes. Addition of minor fractions of methylsulfonyloctadecane to C18LiTFSI resulted in increases in conductivity of over two orders of magnitude at room temperature, while addition of ethylsulfonyloctadecane or isopropylsulfonyloctadecane with the larger head group resulted in decreased ionic conductivity over the entire composition space and temperature range investigated.

Collins, Hannah (ORCID:0000000338858136)↗

Unveiling the mechanism of phase and morphology selections during the devitrification of Al-Sm amorphous ribbon

The complex interplay between energetic and kinetic factors that governs the phase and morphology selections can originate at the earliest stage of crystallization in the amorphous parent phases. Because of the extreme difficulties in capturing the microscopic nucleation process, a detailed picture of how initial disordered structures affect the transformation pathway remains unclear. Here, we report the experimental observation of widely varying phase selection and grain size evolution during the devitrification of a homogeneous melt-spun glassy ribbon. Two different crystalline phases, θ-Al 5 Sm and ε-Al 60 Sm 11 , are found to form in the different regions of the same metallic glass ribbon during the devitrification. The grain size of ε-Al 60 Sm 11 phase shows a strong spatial heterogeneity. Coarse-grained ε-Al 60 Sm 11 phase coupled with the small volume fraction of θ-Al 5 Sm phase is preferably formed close to wheel side of the melt-spun ribbon. Combining experimental characterization and computational simulations, we show that phase selection and microstructure evolution can be traced back to different types and populations of atomic clusters that serve as precursors for the nucleation of different crystalline phases. Inhomogeneous cooling rates cause different structure orders across the glass sample during the quenching process. Our findings provide direct insight into the effect of structural order on the crystallization pathways during the devitrification of metallic glass. It also opens an avenue to study the detailed nucleation process at the atomic level using the metallic glass as a platform and suggests the opportunity of microstructure and property design via controlling the cooling process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Dataset for Leveraging CryoEM and AI-Driven Morphological Feature Analysis for Insights on Bacterial Structures

This repository hosts an AI-assisted image segmentation and analysis pipeline for Pantoea sp. YR343 cryo-electron microscopy (cryoEM) datasets. The workflow automates membrane thickness measurements, flagella detection, and field-of-view (FOV) screening from low-dose, high-resolution cryoEM micrographs eliminating the need for slow manual annotation. By integrating deep-learning based segmentation (YOLOv11) with quantitative post-processing, this toolkit provides a scalable and reproducible way to study bacterial morphology under hydrated, near-native conditions. The GitHub repository for AI-based tools for cryoEM bacteria ultrastructures can be found here: https://github.com/Sireesiru/Cryo-EM-Ultrastructures/tree/main

60 APPLIED LIFE SCIENCES↗