This white paper focuses on the building of the value, in this case the ability to conceive, evaluate, create, and deliver new materials that meet your business’s goals, meet or exceed the sustainability targets, and differentiate your solutions in the global market.
Digital transformation is a key business initiative of most of the world's large chemicals and materials companies. This paper identifies critical success factors for digitalization in materials and chemicals and how the Citrine Platform supports them.
Formulations development has unique challenges associated with the vast spectrum of possible ingredient combinations and the complex rules that govern their mixing. Learn how we address these challenges with formulations-specific AI and data management approaches.
This paper explains and gives examples of how AI can be used to efficiently explore the highly multi-dimensional challenge of developing new catalysts and how hierarchical, graphical AI models can be used to model complex interactions and compensate for scarce data through transfer learning.
Better batteries with with higher energy density and the ability to charge quickly are needed to enable the energy transition. This paper explores how AI can be used to reach ambitious battery property targets quickly, through material development, battery configuration optimization and improved battery testing.
Learn how Machine Learning for Materials and typical AI applications are different. See how Citrine has overcome these difficulties and why off-the-shelf open source AI will require a lot of tailoring to make it work in this space.
Learn how data can be used to accelerate materials development. Read about the principles of good data management. See how Citrine's Platform supports data management in a way that is tailored for materials and chemicals industries.
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