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	<title>AI@JSI Seminar Upcoming | Department of Knowledge Technologies</title>
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		<title>AI for Materials Science: Tuning Laser-Induced Graphene Production</title>
		<link>https://kt.ijs.si/aijsi-seminar-upcoming/ai-for-materials-science-tuning-laser-induced-graphene-production/</link>
		
		<dc:creator><![CDATA[Anja Glusic]]></dc:creator>
		<pubDate>Wed, 08 Apr 2026 13:42:34 +0000</pubDate>
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					<description><![CDATA[23 Apr 2025 at 13:00]]></description>
										<content:encoded><![CDATA[<p>AI and machine learning have advanced the state of the art in many application domains. We present an application to materials science; in particular, we use surrogate models with Bayesian optimization for automated parameter tuning to optimize the fabrication of laser-induced graphene. This process allows to create thin conductive lines in thin layers of insulating material, enabling the development of next-generation nano-circuits. This is of interest for example for in-space manufacturing. We are able to achieve improvements of up to a factor of two compared to existing approaches in the literature and to what human experts are able to achieve, in a reproducible manner. Our implementation is based on the open-source mlr and mlrMBO frameworks and generalizes to other applications.</p>
<p>Zoom link: <a href="https://zoom.us/j/92010489234?pwd=TnP9ZtXTfT0aZayMJEHaNBlInprgNU.1" target="_blank" rel="noopener">Click me.</a></p>
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