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Autonomous materials discovery.
Connecting synthesis, measurement and machine learning to explore polymer chemistry more intelligently.
We build experimental systems that can make polymers, measure what they do and use the results to decide what to try next. The aim is to understand the relationships between a polymer's chemistry, its processing and its eventual performance.
01
How can an experiment choose the most informative next polymer to make?
02
Which measurements give useful feedback early enough to guide synthesis?
03
How do we make automated discoveries interpretable to a chemist?
Making the connection
Our approach brings together continuous-flow synthesis, robotic liquid handling, in-line and at-line measurements, and data-guided experiment selection. We design each workflow around a scientific question and the property we need to explain.
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