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Tools To Measure Dispersion Descriptors From Polymer Nanocomposites
Zuniga Cuellar, Kevin Dimas
Zuniga Cuellar, Kevin Dimas
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Abstract
MaterialsMine is a new open-source data resource with the goal of supporting faster nanocomposite and metamaterials discovery and design. One goal of MaterialsMine is to provide tools that help researchers gain a better fundamental understanding of nanofiller behavior. While it is well known that the dispersion of nanofillers in nanocomposites critically controls properties, there is limited quantitative data. This thesis develops a methodology for quantitatively measuring the dispersion of polymer nanocomposites quickly and within the MaterialsMine data framework. The method processes transmission electron microscopy (TEM) images from MaterialsMine. TEM images are first pre-processed and transformed into binary images. Then the binary images are processed by microstructure characterization algorithms such as correlation functions, physical descriptors, and spectral density functions to obtain critical dispersion features (such as interfacial area or average cluster size). We used the new tools to quantify about 100 images and incorporated the dispersion descriptors into MaterialsMine. We then developed correlations between materials properties and dispersion descriptors. The results obtained from the new methodology demonstrate consistent outcomes across various image processing methods. Moreover, the correlation analysis reveals a consistent relationship between AC breakdown strength and the average nearest cluster center distance.
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Date
2023-01-01