  Crystal structure prediction algorithms have become powerful tools for
materials discovery in recent years, however, they are usually limited to
relatively small systems. The main challenge is that the number of local minima
grows exponentially with system size. In this work, we proposed two
crossover-mutation schemes based on graph theory to accelerate the evolutionary
structure searching. These schemes can detect molecules or clusters inside
periodic networks using quotient graphs for crystals and the decomposition can
dramatically reduce the searching space. Sufficient examples for the test,
including the high pressure phases of methane, ammonia, MgAl2O4, and boron,
show that these new evolution schemes can obviously improve the success rate
and searching efficiency compared with the standard method in both isolated and
extended systems.
