J-V analysis hub: an open-source Python tool for multi-model characterization of organic solar cells

The analysis of current-voltage (J-V) characteristics is essential for understanding charge transport, injection barriers, and performance metrics in organic photovoltaic (OPV) devices. However, most available approaches either require advanced programming skills or focus on a limited subset of models. This work introduces a free, cross-platform Python-based tool that integrates multiple theoretical frameworks for J-V curve analysis through a user-friendly graphical interface. The software implements modules for illuminated curves, enabling the extraction of $J_{sc}$, $V_{oc}$, fill factor (FF), power conversion efficiency (PCE), and resistive losses, as well as modules dedicated to dark curves, including the Mott-Gurney law, the circuital model, and the Richardson-Schottky formalism, which allow estimation of carrier mobility, effective mobility, saturation current density, and injection barrier height. Graph customization options are included to generate publication-ready figures directly within the program. The tool was validated against experimental data, providing reliable results consistent with theoretical expectations. Future releases will expand its scope by adding a multiplot functionality for the simultaneous comparison of multiple datasets and a lifetime analysis module to monitor the temporal evolution of PCE, $V_{oc}$, $J_{sc}$, FF, and carrier mobility. By combining rigor, accessibility, and extensibility, the proposed tool contributes to the systematic characterization and optimization of next-generation organic solar cells.