Content Library

The design of chemical formulations is a challenging, high-dimensional problem. In typical formulations, tens of thousands of ingredients are available for use, yet only a tiny fraction end up...

Lu-doped zirconia (LuDZ) was reported in the 1960s to be a poor oxygen ion conductor. However, we identified this system as worthy of reexamination based on the results of a machine...

Find out about AI model accuracy and quantified uncertainty and the impact these have on business outcomes.

Find out why FAIR data standards are important in the corporate world as well as academia.

Learn how the Citrine Platform was used to predict toxicity in complex, multi-phase formulations, therefore reducing resources spent developing formulations that would ultimately fail animal testing.

Join our webinar to learn how AI can support companies in achieving ambitious sustainability goals.

Our summer interns had productive summers. Read why they joined Citrine and what they did.

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.