卤化物
带隙
电子
直接和间接带隙
化学
导带
电子亲和性(数据页)
光电子学
分析化学(期刊)
材料科学
物理
无机化学
分子
色谱法
量子力学
有机化学
作者
Chaiyawat Kaewmeechai,Yongyut Laosiritaworn,Atchara Punya Jaroenjittichai
标识
DOI:10.1016/j.rinp.2022.106015
摘要
• The natural band offsets of Cs 2 BX 6 and TiO 2 could be rapidly estimated by using electron affinity rule. • Band alignment of Cs 2 BX 6 is type-I, whether grouped by the same B or same X. • The CBM of Cs 2 ZrX 6 and Cs 2 HfX 6 are relatively close to each other due to the d states of Zr and Hf. • The shift in valence band is more influential cause of bandgap variation in Cs 2 TiX 6 than that in conduction band. Cs 2 BX 6 double halide perovskites have attracted broad attention in the field of materials science, physics, and optoelectronics. They are promising as potential candidates for light-absorber layers in solar cells and ultrafast scintillators. This is due to their remarkable preferences such as low-cost and simple processability, tunable bandgaps, large-absorption coefficient, high mobility and fast respond under excitation. To provide an initial information for designing multijunction devices made from Cs 2 BX 6 , the band alignment of Cs 2 BX 6 is necessary to determine. Thus, we investigated the surface physics of Cs 2 BX 6 , where B = Ti, Zr, Hf and X =Cl, Br, I, by using electron affinity rule and extracted all the natural band offsets among Cs 2 BX 6 and TiO 2 . We found that the band alignment of Cs 2 BX 6 is type-I, whether they were grouped by the same transition-metal or same halide. The positions of conduction band minimum of Zr – and Hf – compounds are relatively close to each other due to the position of Zr – and Hf – d states. The shift in valence band is more influential cause of bandgap variation in Ti – compounds than the change in conduction band. We hope that the band alignment of Cs 2 BX 6 will be benefit not only for the heterostructure design but also for understanding the behavior of tuning bandgaps of alloys among Cs 2 BX 6 either by mixing B or X atoms.
科研通智能强力驱动
Strongly Powered by AbleSci AI