DSM Engineering Materials has recently announced the launch of Lucidiris™. Lucidiris™ helps customers reduce time to market when developing colors of high-performance materials for a variety of applications. Besides predicting color and mechanical properties, it can predict the envelope of potential color space within critical mechanical properties and prescribe recipes for targeted color properties. Lucidiris™ has been developed for several high-performance material grades and will be extended, including recycled-based and repurposed materials. It is a next step in DSM Engineering Materials’ journey to make product development for their customers quicker and easier via advanced digital solutions.
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DSM Engineering Materials launches Lucidiris™, a color and mechanical properties prediction tool powered by Artificial Intelligence (AI) |
This state-of-the-art patent protected Artificial Intelligence (AI) technology facilitates the development of material recipes with targeted optical properties while assuring mechanical properties. With Lucidiris™ customers will be supported by its ability to:
• Predict color and mechanical properties of polymer compounds upon addition of color ingredients.
• Predict envelope of potential color space that can be produced within critical mechanical properties.
• Prescribe color ingredients to add to a polymer compound to meet targeted properties.
“Lucidiris™ changes our design-build-test-learn development cycle for the customer applications of our materials fundamentally,” said Erwin Houben, R&T Manager Digitization DSM Engineering Materials. “This state-of-the-art AI based digital tool reinforces our strengths in colored materials development and enables to take on some tough challenges for reusing circular materials.”
“And there is more to come,” said Angelika Schmidt, Global R&T Manager of Performance Polymers, DSM Engineering Materials. “Lucidiris™ is our next step into digitization of product development. What we can do for color development already today, will be possible for product development in the future. Combining human intelligence with machine learning will enable us to get to the successful recipes with much less iterations and therefore much shorter development times for our customers.”
