Vertical van der Waals heterostructures have aroused great attention, owing to their promising application in next generation nanoelectronic and optoelectronic devices. The dielectric screening effect plays a key role on...

The photovoltaic performance of perovskite solar cell is determined by multiple interrelated factors, such as perovskite compositions, electronic properties of each transport layer and fabrication parameters, which makes it rather challenging for optimization of device performances and discovery of underlying mechanisms. Here, we propose and realize a novel machine learning approach based on forward-reverse framework to establish the relationship between key parameters and photovoltaic performance in high-profile MASnxPb1-xI3 perovskite materials. The proposed method establishes the asymmetrically bowing relationship between band gap and Sn composition, which is precisely verified by our experiments. Based on the analysis of structural evolution and SHAP library, the rapid-change region and low-bandgap plateau region for small and large Sn composition are explained, respectively. By establishing the models for photovoltaic parameters of working photovoltaic devices, the deviation of short-circuit current and open-circuit voltage with band gap in defective-zone and low-bandgap-plateau regions from Shockley-Queisser theory is captured by our models, and the former is due to the deep-level traps formed by crystallographic distortion and the latter is due to the enhanced susceptibility by increased Sn4+ content. The more difficulty for hole extraction than electron is also concluded in the models and the prediction curve of power conversion efficiency is in a good agreement with Shockley-Queisser limit. With the help of search and optimization algorithms, an optimized Sn:Pb composition ratio near 0.6 is finally obtained for high-performance perovskite solar cells, then verified by our experiments. Our constructive method could also be applicable to other material optimization and efficient device development.

Group IV monochalcogenides MX (M = Ge, Sn; X = S, Se)-semiconductor isostructure to black phosphorene-have recently emerged as promising two-dimensional materials for ultrathin-film photovoltaic applications owing to the fascinating electronic and optical properties. Herein, using first-principles calculations, we systematically investigate the orbital contribution electronic properties, angular and strain dependence on the carrier effective masses of monolayer MX. Based on analysis on the orbital-projected band structure, the VBMs are found to be dominantly contributed from the pz orbital of X atom, while the CBM is mainly dominated by px or py orbital of M atom. 2D SnS has the largest anisotropy ratio due to the lacking of s orbital contribution which increases the anisotropy. Moreover, the electron/hole effective masses along the x direction have the steeper tendency of increase under the uniaxial tensile strain compared to those along y direction.

A shallow acceptor level is formed for the thermally stable β-Ga2O3:NO(II)–VGa(I) complexes due to the Coulomb binding between NO(II) and VGa(I).