New insights into halide perovskites could transform solar cell technology

New insights into halide perovskites could transform solar cell technology

by Robert Schreiber

Berlin, Germany (SPX) Sep 25, 2025

Global electricity consumption is rising rapidly, and researchers at Chalmers University of Technology in Sweden have made progress toward developing next-generation solar cell materials. Their work uses computer simulations and machine learning to better understand halide perovskites, which are lightweight, flexible, and highly efficient but prone to instability.

According to the International Energy Agency, electricity will account for over half of the world’s energy use in 25 years, up from 20 percent today. “To meet the demand, there is a significant and growing need for new, environmentally friendly and efficient energy conversion methods, such as more efficient solar cells.

“Our findings are essential to engineer and control one of the most promising solar cell materials for optimal utilisation. It’s very exciting that we now have simulation methods that can answer questions that were unresolved just a few years ago,” said Julia Wiktor, principal investigator and associate professor at Chalmers.

Halide perovskites are among the strongest candidates for future solar technologies, offering high efficiency at low cost and potential applications ranging from building coatings to LEDs. Yet, they degrade quickly and require deeper scientific understanding to improve stability.

A critical focus has been formamidinium lead iodide, a crystalline compound with excellent optoelectronic properties but limited use due to its instability. Researchers believe mixing perovskite types may resolve the issue, but such approaches demand precise knowledge of their phases and interactions.

The Chalmers team has now described the elusive low-temperature phase of formamidinium lead iodide, providing missing information needed to design and control both this material and its mixtures. “The low-temperature phase of this material has long been a missing piece of the research puzzle and we’ve now settled a fundamental question about the structure of this phase,” explained Chalmers researcher Sangita Dutta.

By integrating machine learning with traditional modelling, the group extended simulation times thousands of times longer than before and scaled models from hundreds of atoms to millions. These advances allowed unprecedented accuracy, later confirmed by experiments at the University of Birmingham, where the material was cooled to -200oC to replicate simulation conditions.

“We hope the insights we’ve gained from the simulations can contribute to how to model and analyse complex halide perovskite materials in the future,” said Erik Fransson of the Department of Physics at Chalmers.

Research Report:Revealing the Low-Temperature Phase of FAPbI3 Using a Machine-Learned Potential