  While many piezoelectric materials are known, there is still great potential
to improve on the figures of merit of existing materials through compositional
doping, forming solid solutions. Specifically, it has been shown that doping
and alloying wurtzite-structured materials can improve the piezoelectric
response; however, a vast compositional space has remained unexplored. In this
work, we apply a multi-level screening protocol combining machine learning,
chemical intuition, and thermodynamics to systematically discover dopant
combinations in wurtzite material space that improve the desired piezoelectric
response. Through our protocol, we use computationally inexpensive screening
calculations to consider more than 3000 possible ternary wurtzite solid
solutions from 9 different wurtzite base systems: AlN, BeO, CdS, CdSe, GaN,
ZnO, ZnS, ZnSe, and AgI. Finally, based on thermodynamic analysis and explicit
piezoelectric response calculations, we predict 11 materials with improved
piezoelectric response, due to the incorporation of electropositive dopants.

Materials Science