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· Chemical Engineering Online
AI summary

Kemira and CuspAI used generative AI to design new materials for removing trace PFAS (“forever chemicals”) from drinking and process water, focusing on chemistries that are stable, sustainable, and manufacturable. Their discovery effort explored a design space of roughly 300 trillion possible materials.

What outcomes or performance metrics (e.g., selectivity, capacity, regeneration, cost) would you most want to see to trust AI-designed PFAS-removal materials in real-world water treatment?

Kemira and CuspAI designing new PFAS-remediation materials using generative AI

This article was originally posted on chemengonline.com.
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Kemira Oyj (Helsinki, Finland) and CuspAI announced that they have used generative AI to design new materials targeting the removal of PFAS, so-called “forever chemicals,” from drinking and process water at trace concentrations, using chemistry that is stable, sustainable, and manufacturable. The materials discovery project explored a design space of approximately 300 trillion possible material […]

The post Kemira and CuspAI designing new PFAS-remediation materials using generative AI appeared first on Chemical Engineering.

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