The inherent instability of CHNHPbXremains a major technical barrier for the industrial applications of perovskite materials. Recently, the most stable surface structures of CHNHPbXhave been successfully characterized by using density functional theory (DFT) calculations together with the high-resolution scanning tunneling microscopy (STM) results. The two coexisting phases of the perovskite surfaces have been ascribed to the alternate orientation of the methylammonium (MA) cations. Notably, similar surface defect images (a dark depression at the sites of X atoms) have been observed on surfaces produced with various experimental methods. As such, these defects are expected to be intrinsic to the perovskite crystals and may play an important role in the structural decomposition of perovskite materials. Understanding the nature of such defects should provide some useful information toward understanding the instability of perovskite materials. Thus, we investigate the chemical identity of the surface defects systematically with first-principles density functional theory calculations and STM simulations. The calculated STM images of the Br and Br-MA vacancies are both in good agreement with the experimental measurements. In vacuum conditions, the formation energy of Br-MA is 0.43 eV less than the Br vacancy. In the presence of solvation effects, however, the formation energy of a Br vacancy becomes 0.42 eV lower than the Br-MA vacancy. In addition, at the vacancy sites, the adsorption energies of water, oxygen, and acetonitrile molecules are significantly higher than those on the pristine surfaces. This clearly demonstrated that the structural decomposition of perovskites are much easier to start from these vacancy sites than the pristine surfaces. Combining DFT calculations and STM simulations, this work reveals the chemical identities of the intrinsic defects in the CHNHPbXperovskite crystals and their effects on the stability of perovskite materials.
Liu Yunxia Palot́s Krisztín Yuan Xiao Tingjun Hou Lin Haiping Youyong Li 李述汤
ACS Nano
2017