Anion optimization for bifunctional surface passivation in perovskite solar cells

Area of Science:

• Materials Science
• Renewable Energy
• Computational Chemistry

Background:

• Pseudo-halide (PH) anion engineering is a surface passivation technique for perovskite optoelectronics.
• Previous PH anions showed limited defect passivation, causing deep impurity states.
• The vast chemical space of PH anions hindered comprehensive exploration.

Purpose of the Study:

• To accelerate the discovery of effective PH anions for perovskite surface passivation.
• To identify PH anions that prevent lattice distortion and anti-site defects.
• To optimize PH anion surface attachment for improved perovskite solar cell performance.

Main Methods:

• Developed a machine learning workflow integrated with density functional theory calculations.
• Utilized a physics-informed machine learning model to screen potential PH anions.
• Experimentally validated promising candidate molecules, focusing on sodium thioglycolate.

Main Results:

• Identified 15 bifunctional PH anions capable of passivating both donor and acceptor sites.
• Sodium thioglycolate demonstrated superior passivation, leading to a 24.56% power conversion efficiency (PCE).
• Achieved a high open-circuit voltage of 1.19 V and maintained 96% of initial PCE after 900 hours of operation.

Conclusions:

• Machine learning significantly accelerates the discovery of advanced materials for perovskite solar cells.
• Optimized pseudo-halide anion engineering, specifically with sodium thioglycolate, enhances device efficiency and stability.
• This approach offers a scalable pathway for developing high-performance perovskite optoelectronics.