Self-driving labs use artificial intelligence (AI) and computational modelling to predict which materials or small molecules will have the properties required for a particular application.
A robotic lab uses AI predictions to autonomously synthesize and tests for said properties.
The test data is then fed back into the AI system, sothat I a learn from the results to generate a new, better slate of candidates.
After rounds of automated predictions, syntheses, and tests, the material is discovered. This automations allows human scientists to forgo conventional experimentation's tedious trial and error and hand off 90% of the manual work to robots.
We accelerate materials discovery by making the fundamental breakthroughs in fields such as AI, robotics, and materials science which are required to develop robust and scalable SDLs.
We are upskilling today's researchers and training the researchers of tomorrow with the skills they need to advance the emerging field of accelerated science.
We are connecting key players in the innovation continuum to de-risk the design and commercialization of sustainable materials and molecules.
We conduct ethics, economics, and Indigenous science and technology research to ensure that our materials and technologies are ethically designed with community partners to benefit society and the planet.
