Double perovskites as p-type conducting transparent semiconductors: a high-throughput search

Abstract

The gap versus of double perovskite p-type TCS candidates compared with other systems from the literature.

The Cs2AgRhCl6 Halide Double Perovskite: A Dynamically Stable Lead-Free Transition-Metal Driven Semiconducting Material for Optoelectronics

“…For instance, the contribution of Rh(4d), Cl(3p), and Ag(5s) to the CBM of Rb 2 AgRhCl 6 was 61.0, 23.5, and 6.0%, respectively, whereas those of Rb 2 AgRhCl 6 were 60.8, 23.6, and 6.0%, respectively. Since the CBM is far away, and at the same time, the VBM is just below the fermi level, one might conclude that A 2 AgRhCl 6 are p-type conducting materials (Wang H.-C. et al, 2019). The spin-polarized DOS and band structures of the first three members of the series are shown in Figures S1-S3, revealing that spin-polarization does not have any marked impact on the orbital character of CBM and VBM.…”

“…The three different DFT functionals employed for the relaxation of the geometry of A 2 AgRhCl 6 were SCAN-rVV10 (Sun et al, 2015;Sun J. et al, 2016;Buda et al, 2017), PBE (Perdew et al, 1996) and PBEsol (Perdew et al, 2008). The reason for choosing three functionals is that we were interested in determining the extent to which the latter two functionals underestimate the bandgaps of the systems under investigation compared to SCAN-rVV10, since they generally underestimate the bandgap of halide single and double perovskites compared to both experiment and the computationally expensive GW and HSE06 (Volonakis et al, 2017;Lamba et al, 2019;Umadevi and Watson, 2019;Wang H.-C. et al, 2019). We note that the newly-proposed SCAN-rVV10 functional is one of the strongly constrained and appropriately normed metageneralized gradient approximation (meta-GGA) functionals that is considered to model well metallic, insulating and semiconducting materials (Sun et al, 2015;Sun J. et al, 2016;Buda et al, 2017).…”

Theoretical Progress on the Relationship between the Structures and Properties of Perovskite Solar Cells

“…There are also other reports about high‐throughput calculations or ML for perovskite coating materials, such as the screening perovskites with gradient‐boosted regression tree [ 117 ] or artificial neural network, [ 118 ] predicting electron transmission coefficients between MAPbI 3 and metal electrodes, and so on. [ 119–126 ] Now the artificial intelligence or machine learning could even surpass human intelligence in some fields. For example, they have defeated the top player in chess and go games, and we hope artificial intelligence can work as top chemists and physicists to design and optimize the high performance perovskite in the near future.…”

“…coefficients between MAPbI 3 and metal electrodes, and so on. [119][120][121][122][123][124][125][126] Now the artificial intelligence or machine learning could even surpass human intelligence in some fields. For example, they have defeated the top player in chess and go games, and we hope artificial intelligence can work as top chemists and physicists to design and optimize the high performance perovskite in the near future.…”

Latest directions in p-type transparent conductor design

“…However the authors recognise that the ultimate obstacle for these materials is their p-type dopability, which in this case has not been studied computationally, and there is a call to arms for experimental investigation. 102 Hu et al have already demonstrated that it is not possible to generate sufficient p-type carriers in Cs 4 CdSb 2 Cl 12 due to the spontaneous formation of native n-type defects, 91 which could be the downfall of these Cs and Rb double halide perovskites too.…”