Open AccessKinetic Monte Carlo Simulation of Perovskite Solar Cells to Probe Film Coverage and Thickness
Author(s) -
Bahrami Behzad,
Mabrouk Sally,
Gurung Ashim,
Reza Khan Mamun,
Elbohy Hytham,
Pathak Rajesh,
Saianand Gopalan,
Adhikari Nirmal,
Dubey Ashish,
Rahman Sheikh Ifatur,
Qiao Quinn
Publication year - 2021
Publication title -
advanced energy and sustainability research
Language(s) - English
Resource type - Journals
ISSN - 2699-9412
DOI - 10.1002/aesr.202000068
Subject(s) - perovskite (structure) , kinetic monte carlo , photovoltaic system , materials science , monte carlo method , energy conversion efficiency , probabilistic logic , charge carrier , optoelectronics , computer science , chemistry , electrical engineering , engineering , artificial intelligence , statistics , mathematics , crystallography
Perovskite solar cells (PSCs) have received considerable attention in recent years due to their low processing cost and high‐power conversion efficiency. However, the mechanisms of PSCs are not fully understood. A model based on a probabilistic and statistical approach needs to be developed to simulate, optimize, and predict the photovoltaic (PV) performance of PSC. Herein, the 3D model based on the kinetic Monte Carlo (KMC) approach is developed to simulate 3D morphology of perovskite‐based solar cells and predict their PV performances and charge dynamics. The developed 3D model incorporates the temporal and physical behavior of perovskites, such as charge generation, transport, and recombination. The KMC simulation results show that pin holes‐free perovskite films with a homogenous 400 nm thick perovskite capping layer achieve the highest power conversion efficiency of 20.85%. However, the shortest apparent charge transport time ( τ t ) and the longest apparent charge carrier recombination lifetime ( τ r ) are found for the champion device. PV performance from the fabricated device is used to validate this simulation model. This model can provide a significant conceptual advance in identifying bottlenecks and guiding novel device designs to further improve the performance of perovskite PVs.