Content Library

In this webinar, Malcolm Davidson, Citrine’s Senior Data Solutions Engineer, will describe why AI is particularly suited to modeling catalytic reactions and give examples of how the Citrine Platform...

Using machine learning to create a new open database of corrosion-resistant alloys.

Design spaces define the search area for AI models. This blog explains what they are, and how they can be used in AI powered materials research.

In this panel discussion, Citrine Informatics sits down with Diversity, Equity, and Belonging leaders in Tech to discuss systemic and organizational barriers to experiencing belonging at work.

This webinar will showcase the benefits of combining AI with physics-based simulations at different length scales, from atomic and molecular simulation to microstructural modelling tools and FEA.

Machine learning techniques are seeing increased usage for predicting new materials with targeted properties. However, widespread adoption of these techniques is hindered by the relatively greater experimental efforts required...

In this webinar, we’re joined by Anantha Desikan, the Executive Vice President and Chief Innovation and Technology Officer at ICL, to discuss sustainability across the agricultural chemical and food...

High-temperature alloy design is challenging, but crucial to aeronautical applications. Citrine is working on a project to improve the representation of alloys data and develop techniques to to accurately...

In this webinar, learn about the founding, growth, and successes of the Data-Driven Design group within Exxon’s materials research and development organization.

Extracting, cleaning and analyzing and visualizing MPEA data.