Machine-Learning-Driven Exploration of HTL Effects in Mg₃SbBr₃ Perovskite Solar Cells for Ultra-High Efficiency

Key Points

• The aim is to investigate the effects of hole transport layers (HTL) on the efficiency of magnesium antimonide perovskite solar cells.
• Conducted a computational investigation of novel inorganic absorbers.
• Applied machine learning algorithms to analyze HTL impacts.
• Evaluated thermal stability and efficiency metrics.
• Identified a significant increase in efficiency when using specific HTLs.
• Achieved thermal stability metrics that exceed industry benchmarks.
• Demonstrated potential for lead-free alternatives in solar applications.