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			<titleStmt><title level='a'>Applying various machine learning techniques to predict material properties</title></titleStmt>
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				<publisher>NA</publisher>
				<date>10/17/2023</date>
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				<bibl> 
					<idno type="par_id">10507161</idno>
					<idno type="doi"></idno>
					<title level='j'>NRT Annual Meeting</title>
<idno></idno>
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					<author>P Cuddihy</author><author>Mack JP</author><author>A. Russell</author>
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			<abstract><ab><![CDATA[This poster looks to apply machine learning in different aspects such as predicting dynamic viscosity of ionic liquids, determining parameters to generate a nonwoven mat through electrospinning, and predictions of extent of damage along with residual strength in fiber reinforced polymer composites. Through the use of machine learning we look to better understand the factors that go into each of these predictions and to eliminate time and costs in each process.]]></ab></abstract>
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