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	<title>industrial solid waste &#8211; BIOENGINEER.ORG</title>
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		<title>From Atoms to Algorithms: New Review Maps the Future of Low-Carbon Geopolymer Materials</title>
		<link>https://bioengineer.org/from-atoms-to-algorithms-new-review-maps-the-future-of-low-carbon-geopolymer-materials/</link>
		
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		<pubDate>Mon, 05 Oct 2026 07:31:31 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[aluminosilicate binders]]></category>
		<category><![CDATA[electron microscopy]]></category>
		<category><![CDATA[geopolymers]]></category>
		<category><![CDATA[industrial solid waste]]></category>
		<category><![CDATA[low-carbon cement]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[molecular dynamics]]></category>
		<category><![CDATA[Neutron scattering]]></category>
		<category><![CDATA[pair distribution function]]></category>
		<category><![CDATA[solid-state NMR]]></category>
		<category><![CDATA[structure-property relationships]]></category>
		<category><![CDATA[synchrotron radiation]]></category>
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					<description><![CDATA[A sweeping new review in the Journal of Materials Science shows how synchrotron light, neutron scattering, advanced microscopy, molecular simulation, and machine learning are transforming geopolymers from empirically optimized wastes into predictively designed low-carbon materials.]]></description>
		
		
		
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