What question did this study set out to answer?

The aim is to explore how machine learning can aid in the screening of chalcogenide perovskites as effective solar energy materials.

April 11, 2026Faraday Discussions0 citationsOpen Access

ML-guided screening of chalcogenide perovskites as solar energy materials

DGDiego A. Garzόn LHLauri Himanen LALuisa Andrade

Key Points

The aim is to explore how machine learning can aid in the screening of chalcogenide perovskites as effective solar energy materials.
Utilized machine learning algorithms for screening materials
Analyzed structural polymorphism of perovskites
Evaluated synthetic challenges in producing materials
Identified key phases that compete in perovskite formation
Showed that certain compositions improve photovoltaic performance
Demonstrated easier pathways for synthesizing effective materials

Abstract

Chalcogenide perovskites have emerged as promising absorber materials for next-generation photovoltaic devices, yet their experimental realization remains limited by competing phases, structural polymorphism, and synthetic challenges. Here, we present a...

问 AI

Bookmark

View Full Paper