Content Library

In this webinar, Dr. Jake Mohin will explore how AI & Materials Informatics can be applied to this domain to accelerate cell testing efforts in the face of high...

How much can a combination of sequential learning and closed-loop automation accelerate 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,...

Autonomous experimental systems offer a compelling glimpse into a future where closed-loop, iterative cycles—performed by machines and guided by artificial intelligence (AI) and machine learning (ML)—play a foundational role...

A grand challenge of materials science is predicting synthesis pathways for novel compounds. Data-driven approaches have made significant progress in predicting a compound’s synthesizability; however, some recent attempts ignore...

Interest in high entropy alloy thermoelectric materials is predicated on achieving ultralow lattice thermal conductivity κL through large compositional disorder. However, here it is shown that for a given mechanism,...

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these...

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.

In this panel discussion, Citrine Informatics’ Director of People Operations, Ify Eva Edwards, sits down with other Diversity, Equity, and Belonging leaders to discuss the impact of solidarity.

In this webinar, we will explore how AI & Materials Informatics can be applied to this domain to accelerate reformulation efforts in the face of changing raw materials supply.