Autonomous electrocatalyst discovery for sustainable nitrogen reduction
Sequential learning and autonomous atomistic simulations help discover new catalysts with co-optimized properties.
Closed-loop fully-automated frameworks for accelerating materials discovery
How much can a combination of sequential learning and closed-loop automation accelerate materials discovery?
Quantifying the Performance of Machine Learning Models in Materials Discovery
Our findings illustrate the importance of designing a modeling and discovery workflow which is highly tailored toward the specific problem of interest. In ML and SL for materials discovery, one size does not fit all, traditional error metrics may not be a good predictor of success, and the specifics of the design challenge have important implications for the optimal configuration of materials discovery strategies.
Materials informatics accelerates customer tailored composite material design
Materials Informatics helps a custom thermoplastic producer rapidly identify custom masterbatch + polymer blends for its customized solutions with far fewer experiments than traditional approaches to product development.
Getting Data Ready for AI
Dr. Lenore Kubie passes on advice around data strategy.
Data Scientists – a hot commodity in tech
Steve Edkins, Citrine’s Data Science Manager, speaks about working at Citrine.
AI-Driven Development of Additives for Carbon Fiber Manufacturing Process
Read how the Citrine Platform was used to develop new carbon fiber process additives with local ingredients in record time.
Rapidly Screen Polymers Using AI
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.
Why I Now Care About What Goes Into Everyday Products – Brooke Anderson
Account Executive Brooke Anderson writes an opinion piece about sustainability.
Accelerating electrochemical material discovery for sustainable chemical manufacturing
New electrochemical reactions are needed to reduce the carbon footprint of chemical production. Use AI to find new catalysts.