Metastable materials are abundant in nature and technology, showcasing
remarkable properties that inspire innovative materials design. However,
traditional crystal structure prediction methods, which rely solely on
energetic factors to determine a structure's fitness, are not suitable for
predicting the vast number of potentially synthesizable phases that represent a
local minimum corresponding to a state in thermodynamic equilibrium. Here, we
present a new approach for the prediction of metastable phases with specific
structural features, and interface this method with the XtalOpt evolutionary
algorithm. Our method relies on structural features that include the local
crystalline order (e.g., the coordination number or chemical environment), and
symmetry (e.g., Bravais lattice and space group) to filter the parent pool of
an evolutionary crystal structure search. The effectiveness of this approach is
benchmarked on three known metastable systems: XeN8​, with a two-dimensional
polymeric nitrogen sublattice, brookite TiO2​, and a high pressure BaH4​
phase that was recently characterized. Additionally, a newly predicted
metastable melaminate salt, P-1 WC3​N6​, was found to possess an
energy that is lower than two phases proposed in a recent computational study.
The method presented here could help in identifying the structures of compounds
that have already been synthesized, and developing new synthesis targets with
desired properties