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Learning to Improve Chemical Reactions with AI


Researchers working with the Idaho National Laboratory's Temporal Analysis of Products reactor system.

Credit: Idaho National Laboratory

Researchers at the Idaho National Laboratory (INL) working with the Temporal Analysis of Products (TAP) reactor system are using artificial intelligence (AI) to study the role of catalysts to improve their understanding of chemical reactions.

The researchers incorporated AI into the TAP system to accurately model the processes that occur during TAP experiments.

They validated their approach using a well-studied reaction, the transformation of carbon monoxide into carbon dioxide.

The researchers now are studying TAP data from more complex industrial catalysts and working with researchers at the Georgia Institute of Technology to apply the method to digital twins, which will enable researchers to make predictions based on changes to certain aspects of a reaction.

INL's Rebecca Fushimi said, "These tools are the foundation of a new paradigm in catalyst science, but also pave the way for radical new approaches in chemical manufacturing."

From Idaho National Laboratory
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA


 

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