Automated Fabrication and Accelerated Stability Testing of Halide Perovskite Absorbers
Hilal Aybike Can a, Christian M. Wolff a, Christophe Ballif a
a Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
Proceedings of MATSUS Fall 2024 Conference (MATSUSFall24)
#AMADISTA - Accelerated Materials Discovery Through Automation and Machine Learning
Lausanne, Switzerland, 2024 November 12th - 15th
Organizers: Philippe Schwaller, Tobias Stubhan and Christian Wolff
Oral, Hilal Aybike Can, presentation 281
Publication date: 28th August 2024

     Halide perovskites have emerged as one of the most promising and diverse material systems in the history of photovoltaics. Intense interest in these materials is a result of several favorable optoelectronic characteristics while being solution-processable using abundant elements at low temperatures. Furthermore, bandgap tunability from the UV to the NIR makes them ideally suited for multi-junction solar cells.

     Despite their advantages, most perovskite compositions used in highly efficient PSCs exhibit comparatively poor thermal stability due to the presence of organic cations, particularly the volatile methylammonium. Inorganic Cs-based perovskites are an intriguing exception and have recently been demonstrated to exhibit excellent operational stability in single-junction solar cell devices. An attractive next step would be to find a stable composition for use in multi-junction devices. The optimization problem therefore is therefore to find a stable material with a suitable bandgap that can be processed at temperatures compatible with a multi-junction substrate. 

     Here we report on a robotic high-throughput system for exploring the compositional space of perovskite top-cell absorbers. The system comprises a robotic liquid-handling system capable of preparing a large array of solutions (up to approx. 100 per batch) from a set of stocks or precursors ready for manual spin-coating. A separate apparatus has been assembled for automatic characterization and accelerated aging. In the latter, optoelectronic properties (e.g., bandgap, luminescence) are recorded before and during ageing under elevated temperatures and intense illumination. The gathered information is used to develop a material database, and computer-aided decision-making (e.g., Bayesian optimization) is used to model the hyperspace and iteratively improve the model with each new experiment. In combination we expect this system to dramatically accelerate the pace of optimization and the discovery of commercially relevant perovskite compositions for use in tandem and multi-junctions.

In this presentation we will address topics such as the comparative stability of films fabricated by spin-coating and drop-casting, the effect of selective contact layers on aging behavior, and the role of the halide fraction.

 

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