Our AI-driven platform identifies optimal synthesis recipes for target inorganic materials, accelerating materials R&D and lowering the cost of manufacturing.
1. Target material
Start with any inorganic compound (e.g., BaTiO3) and its known or predicted crystal structure.
2. Reaction networks
Using AI-assisted algorithms, we construct massive networks with millions of chemical reactions among thousands of compounds in a wide chemical search space.
3. Recipe generation
Thousands of synthesis routes towards the target material are identified within the network and ranked by thermodynamic optimality, reaction selectivity, cost, and more.
4. Experimental validation
Predicted synthesis recipes are sent to the lab to be tested. Efficient synthesis optimization algorithms are used to converge on an ideal recipe.
Our sponsors
We are proud to announce that we are an Activate 2024 company!
Our team
Interested in joining our small, passionate team? Please reach out below.
Matthew McDermott, Ph.D.
Founder & CEO
U.C. Berkeley PhD graduate and former postdoctoral researcher at Lawrence Berkeley National Laboratory, where his research focused on the development of inorganic synthesis planning algorithms and the A-Lab, a robotic laboratory to discover new materials.
Contact us
Please reach out to learn more or set up a meeting. We look forward to hearing from you!
