Read how the Citrine Platform was used to develop new carbon fiber process additives with local ingredients in record time.
Learn how Citrine’s AI Platform was used to rapidly screen 2500+ polymers in just 5 months. See how a new workflow was developed where researchers can now set a target and immediately receive a list of the top 10 polymers most likely to hit the target.
Learn how Citrine worked with SLAC National Accelerator laboratory to optimize synthesis parameters for nanoparticles using an AI-guided closed-loop system in just 12 hours.
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.
This white paper summarizes the differences between Machine Learning for Materials and typical AI applications. It explains 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.