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DSM Launches an AI Powered Color & Mechanical Properties Prediction Tool

Called Lucidiris, this prediction tool can reduce time to market when developing colors of high-performance materials for a variety of applications.  

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DSM Engineering Materials develops Lucidiris, and AI powered color and mechanical properties prediction tool
Photo Credit: DSM Engineering Materials

A new, patented color and mechanical properties prediction tool powered by Artificial Intelligence (AI) has been developed by DSM Engineering Materials. Called Lucidiris, it reportedly 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. “Lucidiris changes our design-build-test-learn development cycle for the customer applications of our materials fundamentally. This state-of-the-art AI based digital tool reinforces our strengths in colored materials development and enables us to take on some tough challenges for reusing circular materials,” Erwin Houben, DSM’s R&T digitization manager

This patent-protected AI technology facilitates the development of material recipes with targeted optical properties while assuring mechanical properties. Houben further explains, “What we have developed for some of our grades is that we can visualize an envelope of colors that we would be able to create with good confidence level based on historical data and our advanced ML prediction model. Our high-performance materials can have high processing temperatures. It results in the use of more temperature stable inorganic crystalline colorants that can have an effect on the glass fibers for instance and therefore on the mechanical properties. We included the mechanical properties in our models, so we are able to take mechanical property specs into account when creating the attainable color envelope of L*, a*, b* values. It is our strength that we can predict the effect on the mechanical properties that we can take into account when developing color recipes. It helps us to reduce the number of iterations needed and therefore to reduce the time-to-market for our customers in color development of our high-performance materials.”

This tool supports customers 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.

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