Accelerated Discovery of Organic Polymer Photocatalysts for Hydrogen Evolution from Water through the Integration of Experiment and Theory

Conjugated
polymers are an emerging class of photocatalysts for
hydrogen production where the large breadth of potential synthetic
diversity presents both an opportunity and a challenge. Here, we integrate
robotic experimentation with high-throughput computation to navigate
the available structure–property space. A total of 6354 co-polymers
was considered computationally, followed by the synthesis and photocatalytic
characterization of a sub-library of more than 170 co-polymers. This
led to the discovery of new polymers with sacrificial hydrogen evolution
rates (HERs) of more than 6 mmol g–1 h–1. The variation in HER across the library does not correlate strongly
with any single physical property, but a machine-learning model involving
four separate properties can successfully describe up to 68% of the
variation in the HER data between the different polymers. The four
variables used in the model were the predicted electron affinity,
the predicted ionization potential, the optical gap, and the dispersibility
of the polymer particles in solution, as measured by optical transmittance.