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	<title>structural optimization &#8211; BIOENGINEER.ORG</title>
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		<title>AI Discovers Multiple Growth Recipes That Build Identical Carbon Nanotube Forests</title>
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		<pubDate>Wed, 07 Oct 2026 07:11:24 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Artificial Intelligence]]></category>
		<category><![CDATA[carbon nanotubes]]></category>
		<category><![CDATA[chemical vapour deposition]]></category>
		<category><![CDATA[inverse design]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[materials synthesis]]></category>
		<category><![CDATA[nanomaterials]]></category>
		<category><![CDATA[nanotechnology]]></category>
		<category><![CDATA[nanotube arrays]]></category>
		<category><![CDATA[National Science Review]]></category>
		<category><![CDATA[Neural Networks]]></category>
		<category><![CDATA[structural optimization]]></category>
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					<description><![CDATA[An AI-driven inverse-design framework has identified multiple distinct chemical vapour deposition recipes that grow carbon nanotube arrays with nearly identical height, density and alignment, revealing that structurally matched nanotube forests can arise from very different processing conditions.]]></description>
		
		
		
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