Screening for lead-free inorganic double perovskites with suitable band gaps and high stability using combined machine learning and DFT calculation

2021 ◽  
pp. 150916
Author(s):  
Zhengyang Gao ◽  
Hanwen Zhang ◽  
Guangyang Mao ◽  
Jianuo Ren ◽  
Ziheng Chen ◽  
...  
2019 ◽  
Vol 43 (37) ◽  
pp. 14892-14897 ◽  
Author(s):  
Diwen Liu ◽  
Qiaohong Li ◽  
Zhang Zhang ◽  
Kechen Wu

Lead-free hybrid perovskites have attracted great attention as environmentally friendly light absorber layers.


2020 ◽  
Vol 8 (16) ◽  
pp. 5349-5354 ◽  
Author(s):  
Mohamed Saber Lassoued ◽  
Le-Yu Bi ◽  
Zhaoxin Wu ◽  
Guijiang Zhou ◽  
Yan-Zhen Zheng

Here, we report two silver(i)–bismuth(iii)-based layered lead-free double perovskites with direct band gaps and high moisture stability.


Nanoscale ◽  
2019 ◽  
Vol 11 (18) ◽  
pp. 8665-8679 ◽  
Author(s):  
Sasha Khalfin ◽  
Yehonadav Bekenstein

In this topical review, we have focused on the recent advances made in the studies of lead-free perovskites in the bulk form and as nanocrystals. We highlight how nanocrystals can serve as model systems to explore the schemes of cationic exchange, doping and alloying for engineering the electronic structure of double perovskites.


2016 ◽  
Vol 7 (13) ◽  
pp. 2579-2585 ◽  
Author(s):  
Marina R. Filip ◽  
Samuel Hillman ◽  
Amir Abbas Haghighirad ◽  
Henry J. Snaith ◽  
Feliciano Giustino

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Qiuling Tao ◽  
Pengcheng Xu ◽  
Minjie Li ◽  
Wencong Lu

AbstractThe development of materials is one of the driving forces to accelerate modern scientific progress and technological innovation. Machine learning (ML) technology is rapidly developed in many fields and opening blueprints for the discovery and rational design of materials. In this review, we retrospected the latest applications of ML in assisting perovskites discovery. First, the development tendency of ML in perovskite materials publications in recent years was organized and analyzed. Second, the workflow of ML in perovskites discovery was introduced. Then the applications of ML in various properties of inorganic perovskites, hybrid organic–inorganic perovskites and double perovskites were briefly reviewed. In the end, we put forward suggestions on the future development prospects of ML in the field of perovskite materials.


2019 ◽  
Vol 3 (8) ◽  
Author(s):  
Anita Halder ◽  
Aishwaryo Ghosh ◽  
Tanusri Saha Dasgupta

2021 ◽  
Vol 266 ◽  
pp. 115064
Author(s):  
Q. Mahmood ◽  
M.H. Alhossainy ◽  
M.S. Rashid ◽  
Tahani H. Flemban ◽  
Hind Althib ◽  
...  

Author(s):  
Tahani I. Al‐Muhimeed ◽  
Aamar Shafique ◽  
Abeer A. AlObaid ◽  
Manal Morsi ◽  
Ghazanfar Nazir ◽  
...  

Author(s):  
Jun Guo ◽  
Yadong Xu ◽  
Wenhui Yang ◽  
Bao Xiao ◽  
Qihao Sun ◽  
...  

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