Ionic Screening and its Impact on J-V Curves in Carbon-Based Perovskite Solar Cells

In recent years, organic-inorganic lead halide perovskite-based solar cells (PSCs) have emerged as a potentially disruptive photovoltaic technology, offering high power conversion efficiencies (PCE) with low manufacturing costs and simple fabrication via solution processing. Despite the mixed ionic-electronic conductivity of perovskites and the high defect densities in the semiconductor expected from solution processing, PSCs can easily achieve high PCE values. The defects most likely to form mostly induce shallow energy levels close to the band gap edges, which relates to why perovskites are often said to have a notorious defect tolerance. However, abundant ionic defects are mobile and often critically affect the performance and stability of PSCs. To improve stability and scalability of PSCs, fully mesoscopic carbon-based PSCs (CPSCs) have emerged as a promising architecture, which avoids the need for precious metal electrodes and organic hole transporting layers. However, their PCE still lags behind the record efficiencies achieved by other single-junction planar PSC stacks, highlighting the need for a deeper understanding of their limitations. The effects of mobile ions in CPSCs infiltrated with methylammonium lead triiodide (MAPbI3) are investigated through an approach combining experiments and simulations. The electric field screening effect of ionic charges is found to be visible in external quantum efficiency (EQE) measurements, which show how current collection losses depend on the illumination wavelength. By analyzing temperature and voltage dependent EQE spectra, we reveal how the internal energy landscape is shaped by the ionic distribution – which in turn determines the response observed in the current density-voltage (J-V) curve. The experimental results are reproduced by drift-diffusion simulations (including mobile ionic charges) coupled with an optical model. The findings shed light on the device physics of PSCs and provide new characterization approaches useful towards device optimization.