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	<title>refrigerant recovery &#8211; BIOENGINEER.ORG</title>
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		<title>Simple Machine Learning Model Predicts Fluorinated Gas Capture in Ionic Liquids</title>
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		<pubDate>Sun, 25 Oct 2026 20:34:27 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[CatBoost]]></category>
		<category><![CDATA[chemical engineering]]></category>
		<category><![CDATA[ensemble learning]]></category>
		<category><![CDATA[feature importance]]></category>
		<category><![CDATA[fluorinated gases]]></category>
		<category><![CDATA[gas solubility]]></category>
		<category><![CDATA[greenhouse gases]]></category>
		<category><![CDATA[ionic liquids]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[phase equilibrium]]></category>
		<category><![CDATA[refrigerant recovery]]></category>
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					<description><![CDATA[A new study shows a CatBoost machine learning model with only seven simple inputs predicts fluorinated gas solubility in ionic liquids with roughly three times the accuracy of earlier descriptor-heavy neural networks.]]></description>
		
		
		
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