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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A new efficient grain growth model using a random Gaussian-sampled mode filter

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics processing units to simulate grain growth up to 100 times faster than the state-of-the-art, publicly available Monte Carlo Potts model. We show that, given the correct neighborhood, the mode filter can replicate normal grain growth in two or three dimensions. In addition, the paper briefly demonstrates the ability to model limited anisotropic in grain boundary energy and mobility. Anisotropic grain boundary energy is modeled by defining a weighted mode filter operation. Anisotropic grain boundary mobility is modeled by scaling and orienting the Gaussian neighborhood in a particular direction.

Anisotropy↗
DOE OSTI2022

Random Walks and Sticky Surfaces: Single-Molecule Measurements of Solute Diffusion in Ethanol/Water-Filled Anodic Alumina Nanopores

Nanoporous anodic aluminum oxide (AAO) membranes are now being explored for use in advanced chemical separations, including in the dehydration of biofuels such as ethanol. Optimization of membrane performance requires an in-depth understanding of how solvent mixtures and solutes behave under nanoconfinement. In this work, the diffusion of rhodamine B (RhB) dye through 10 nm and 20 nm AAO nanopores filled with a series of ethanol/water mixtures (0 - 33% water) is explored by fluorescence correlation spectroscopy (FCS). RhB was found to diffuse through the pores by two distinct mechanisms with mean diffusion coefficients, $D_f$ and $D_s$, reflecting fast and slow diffusive motions, respectively, with values that differ by nearly two orders of magnitude. Further, both $D_f$ and $D_s$ increased with pore size and were significantly smaller than $D_b$, the RhB diffusion coefficient in bulk liquid. Mean $D_f$ values follow a composition-dependent trend that closely mimics the viscosity dependence of $D_b$. Additional slowing of fast RhB diffusion is attributed to both hydrodynamic drag and electrostatic interactions with the nanopore surface. The mean $D_s$ values exhibit a different trend with increasing water content, revealing an increase in $D_s$ and a decrease in the contributions of slow diffusion to the observed dynamics. The fluorescence time transient data used in the analysis show that the slow diffusion process is strongly hindered and likely involves frequent adsorption of RhB to the pore surfaces. These results provide new insights into the detailed molecular-level mechanisms of mass transport in nanoporous AAO membranes.

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

macroMS: Image-Guided Analysis of Random Objects by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Mass spectrometry imaging is well-suited to characterizing sample surfaces for their chemical content in a spatially resolved manner. However, when the surface contains small objects with significant empty spaces between them, more efficient approaches to sample acquisition are possible. Image-guided mass spectrometry (MS) enables high-throughput analysis of a diverse range of sample types, such as microbial colonies, liquid microdroplets, and others, by recognizing and analyzing selected location targets in an image. Here, we describe an imaging protocol and macroMS, an online software suite that can be used to enhance MS measurements of macroscopic samples that are imaged by a camera or a flatbed scanner. Furthermore, the web-based tool enables users to find and filter targets from the optical images, correct optical distortion issues for improved spatial location of selected targets, input the custom geometry files into an MS device to acquire spectra at the selected locations, and finally, perform limited data analysis and use visualization tools to aid locating samples containing compounds of interest. Using the macroMS suite, an enzyme mutant library of Saccharomyces cerevisiae and nL droplet arrays of Escherichia coli and Pseudomonas fluorescens have been assayed at a rate of ~2 s/sample.

47 OTHER INSTRUMENTATION↗