Openaiperovskite: a smart dashboard for solar performance trends of 2d lead-halide perovskites

Perovskite materials are at the forefront of photovoltaic research due to their exceptional optoelectronic properties, tunable band gaps, and low-cost fabrication. While threedimensional (3D) perovskites achieve high power conversion efficiencies (PCEs), their longterm stability remains a major challenge, particularly under humid conditions. In contrast, wodimensional (2D) perovskites offer greater environmental durability but often at the expense of efficiency. To address these limitations, this project introduces OpenAIPerovskite, an AIpowered, web-based dashboard developed using Power BI. The platform integrates curated data from over 1,000 peer- reviewed articles, focusing on fabrication methods, material compositions, and device performance. Key features include dynamic PCE visualisation, parameter-based filtering, and machine learning-driven predictions for efficiency and stability based on user-defined inputs. OpenAIPerovskite enables users to explore and compare experimental data and predictive trends without the need for manual literature review or programming expertise. For instance, users can analyse high-performance devices such as the 20.62% PCE achieved in 2018 using a TiO₂/BAFAPbBrI/Spiro-MeOTAD/gold configuration. Developed at a cost under RM 5,000, the dashboard offers an affordable and accessible alternative to commercial data analysis platforms. This collaborative initiative between Shibaura Institute of Technology, Japan, Universiti Malaysia Terengganu, and an industry partner, bridges academic researchers to make data-driven decisions, minimize experimental trial-and-error, and accelerate the development of stable, high-performance perovskite solar cells.