Perovskite solar cells have drawn extensive attention in the photovoltaic(PV)field due to their rapidly increasing efficiency.Recently,additives have become necessary for the fabrication of highly efficient perovskite...Perovskite solar cells have drawn extensive attention in the photovoltaic(PV)field due to their rapidly increasing efficiency.Recently,additives have become necessary for the fabrication of highly efficient perovskite solar cells(PSCs).Additionally,alkali metal doping has been an effective method to decrease the defect density in the perovskite film.However,the traditional trial-and-error method to find the optimal doping concentration is timeconsuming and needs a significant amount of raw materials.In this work,in order to explore new ways of facilitating the process of finding the optimal doping concentration in perovskite solar cells,we applied a machine learning(ML)approach to assist the optimization of KI doping in MAPbI_(3) solar cells.With the aid of ML technique,we quickly found that 3%KI doping could further improve the efficiency of MAPbI_(3) solar cells.As a result,a highest efficiency of 20.91%has been obtained for MAPbI_(3) solar cells.展开更多
基金Nanchang University High Talent Project(No.9166-2701010119)the National Key R&D Program of China(No.2016YFB0401003)+1 种基金the National Natural Science Foundation of China(Nos.61935016,61775004 and U1605244)。
文摘Perovskite solar cells have drawn extensive attention in the photovoltaic(PV)field due to their rapidly increasing efficiency.Recently,additives have become necessary for the fabrication of highly efficient perovskite solar cells(PSCs).Additionally,alkali metal doping has been an effective method to decrease the defect density in the perovskite film.However,the traditional trial-and-error method to find the optimal doping concentration is timeconsuming and needs a significant amount of raw materials.In this work,in order to explore new ways of facilitating the process of finding the optimal doping concentration in perovskite solar cells,we applied a machine learning(ML)approach to assist the optimization of KI doping in MAPbI_(3) solar cells.With the aid of ML technique,we quickly found that 3%KI doping could further improve the efficiency of MAPbI_(3) solar cells.As a result,a highest efficiency of 20.91%has been obtained for MAPbI_(3) solar cells.
