Unveiling full-dimensional distribution of trap states toward highly efficient perovskite photovoltaics

Abstract

To gain a deep understanding and address key issues in perovskite photovoltaics, such as power conversion efficiency (PCE) and long-term stability, defect passivation and analysis of the device performance are required. Here, we proposed a non-contact characterization technique named scanning photocurrent measurement system (SPMS) for device surface detection, having conducted signal analysis and method adjustments based on perovskite photovoltaic devices. This technique enables the monitoring of minority carriers in the device, allowing for the investigation of carrier behavior based on photocurrent signals. By integrating SPMS with thermal conductance spectroscopy (TAS) and drive-level capacitance profiling (DLCP), we further simulated a spatial three-dimensional (3D) distribution of trap states in the device and analyzed the distribution of trap states matched with energy space. Through extensive case studies, we have validated the universality and accuracy of this method. The integration of trap state characterization techniques provides strong support for targeted defect passivation and performance evaluation of perovskite photovoltaic devices, yielding a highly efficient perovskite solar cell with PCE as high as 25.74%.