Using machine learning to create a new open database of corrosion-resistant alloys.
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 predict properties outside of the range of input data.
Extracting, cleaning and analyzing and visualizing MPEA data.
New electrochemical reactions are needed to reduce the carbon footprint of chemical production. Use AI to find new catalysts.
Summary of peer reviewed, papers showing experimentally verified predictions of material properties.
Citrine has quantified uncertainty in DFT property calculations as part of a project funded by the US Department of Energy and with collaborators from Olin College and MolSSI.