Machine learning(ML)-assisted optimization doping of KI in MAPbI_(3) solar cells

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.

To increase more than 10% in efficiency of perovskite solar cells by using nanoholes SnO_(2)

The perovskite solar cells have been intensively investigated these years due to their premium electrical and optical properties as well as huge potential for application.In order to further increase the power conversion efficiency(PCE) of the thin film perovskite solar cells, light management should be taken into consideration. Herein, we apply a lithography method to transfer randomly distributed polystyrene(PS) nanospheres into the electron transporting SnO_(2) layer, by means of which, a nanoholes structure is formed. Finally, we get a nanostructured perovskite layer under low temperature(less than 150 ℃).The depth of SnO_(2) nanoholes is around 60 nm when the device is fabricated with 300-nm PS, and 150 nm in depth when 500-nm PS is used. The device gains PCE of 17.97%,which is 12.3% higher than that with planar electrontransporting SnO_(2) layer and 300-nm CH_(3)NH_(3)PbI_(3) layer.Our findings provide an applicable method to improve the light absorption, which can not only make the absorbing layer of lead-based perovskite solar cells thinner to help decrease the content of lead, but also increase the PCE of non-lead perovskite devices.