Symmetry-based computational search for novel binary and ternary 2D materials

Abstract We present a symmetry-based systematic approach to explore the structural and compositional richness of two-dimensional materials. use ‘combinatorial engine’ that constructs candidate compounds by occupying all possible Wyckoff positions for certain space group with combinations chemical elements. These are restricted imposing charge neutrality Pauling test electronegativities. The structures then pre-optimized specially crafted universal neural-network force-field, before final step geometry optimization using density-functional theory is performed. In this way we unveil an unprecedented variety materials, covering whole periodic table in more than 30 different stoichiometries form A n B m or C k . Among discovered structures, find examples can be built decorating nearly Platonic Archimedean tessellations as well their dual Laves Catalan tilings. also obtain rich, unexpected, polymorphism some specific compounds. further accelerate exploration materials employing machine-learning-accelerated prototype search, based on types search. total, around 6500 compounds, not previous available databases 2D distance convex hull thermodynamic stability smaller 250 meV/atom.