Hexagonal boron nitride (h-BN) holds great potential for applications due to its unique electronic properties and high chemical stability. Practical applications of h-BN, however, rely on the growth of large-scale, high-quality samples, for which an adequate understanding of the growth mechanism is critically important. In this work, we study the nucleation of h-BN on the Ni(111) surface by density functional theoretical calculations. Our results reveal a novel structural crossover from a chain-like BN cluster to an sp2-bonded honeycomb network at the very beginning of growth. This structural transition occurs in clusters with a critical size of 8 BN pairs, beyond which the honeycomb structure is energetically preferred. After that, the growth proceeds in a downhill manner till a full coverage of h-BN on the Ni surface, driven by continuous reduction in energy of the BN clusters with feeding BN pairs. The critical size can be controlled by tuning chemical potentials. Our results also present that lattice defects, such as 4- and 5-membered rings, are higher in energy and, thus, disfavored in the growth. This work not only explains the formation of high-quality BN sheets but also opens a way to rationally control the synthesis of h-BN by selecting appropriate substrates. The atomistic understandings of nucleation of h-BN are extendable to other two-dimensional materials.

The stable geometries of both different-sized and magic clusters of CVD-prepared hexagonal BN on Ni(111)/Cu(111) are revealed based on DFT simulations.

Hexagonal boron nitride (h-BN) has received extensive attention due to its potential applications in electronic devices, but the growth mechanism of h-BN remains unclear. Here, the stability of various h-BN...

Graphene-like two dimensional (2D) monolayers constructed with β-structured Group 15 (β-G15) elements have attracted great interests due to their intrinsic bandgaps, thermodynamic stabilities and high mobilities. Quite different from graphene,...

The nucleation of h-BN on Ru(0001) and Rh(111) surfaces via an energy-driven process is systematically studied by density functional theory simulations.