Accelerated chemical space search using a quantum-inspired cluster expansion approach
Hitarth Choubisa, Jehad Abed, Douglas Mendoza, Zhenpeng Yao, Ziyun Wang, Brandon Sutherland, Alán Aspuru-Guzik, Edward H Sargent
To enable the accelerated discovery of materials with desirable properties,
it is critical to develop accurate and efficient search algorithms. Quantum
annealers and similar quantum-inspired optimizers have the potential to provide
accelerated computation for certain combinatorial optimization challenges.
However, they have not been exploited for materials discovery due to absence of
compatible optimization mapping methods. Here we show that by combining cluster
expansion with a quantum-inspired superposition technique, we can lever quantum
annealers in chemical space exploration for the first time. This approach
enables us to accelerate the search of materials with desirable properties 20
times faster over the Metropolis algorithm, with an increase in acceleration
factor up to 150 for large systems. Levering this, we search chemical space and
find a promising previously unexplored chemical family of Ru-Cr-Mn-Sb-O$_2$.
The best catalyst in this chemical family show a mass activity 8 times higher
than state-of-art RuO$_2$ and maintain performance for 180 hours while
operating at 10mA/cm$^2$ in acidic 0.5M H$_2$SO$_4$ electrolyte.