Rapid Characterization and Parameter Space Exploration of Perovskites Using an Automated Routine

Abstract

are promising solar cell materials. However, due to the large parameter space spanned by the manifold combinations of divalent metals with organic cations and anions, an efficient approach is needed to rapidly test and categorize new promising materials. Herein, we developed a high throughput approach for the automated synthesis of perovskite layers with different precursor ratios at varying annealing temperatures. The layers were analyzed by optical absorption and photoluminescence (PL) spectroscopy as well as X-ray diffraction (XRD) and evaluated using two different procedures. The first one is a stepwise exclusion of nonperforming reactant ratios and synthesis conditions by using both spectroscopic techniques, followed by a final validation of the procedure by XRD. In the second procedure, only PL results were consulted in combination with high throughput screening using design of experiments (DoE) to reduce the total number of experiments needed and compared to the manual cascade approach. Noteworthy, by simple PL screening, it was possible to identify the best ratio of perovskite to byproducts and annealing temperature. Thus, only with PL, more detailed results as with the manual protocol were reached, while at the same time the effort for characterization was significantly reduced (by 60% of the experimental time). In conclusion, our approach opens a way toward fast and efficient identification of new promising materials under different reaction and process conditions.