SKM 2023 – wissenschaftliches Programm

Bereiche | Tage | Auswahl | Suche | Aktualisierungen | Downloads | Hilfe

CPP: Fachverband Chemische Physik und Polymerphysik

CPP 33: Perovskite and photovoltaics II (joint session HL/CPP)

CPP 33.11: Vortrag

Mittwoch, 29. März 2023, 12:45–13:00, JAN 0027

FAIR Cesium Lead Halide Perovskites Data by High-Throughput Investigation of Co-Evaporated Combinatorial Libraries — •Hampus Näsström¹, Pascal Beblo², Fatima Akhundova², Oleksandra Shargaieva², Jose A. Marquez¹, Hannes Hempel², Andrea Albino¹, Sebastian Brückner¹, Claudia Draxl¹, Eva Unger², and Thomas Unold² — ¹Humboldt-Universität zu Berlin — ²Helmholtz-Zentrum Berlin

Artificial intelligence presents new possibilities in experimental materials research but typically require large well-characterized datasets. High-throughput technologies, including combinatorial synthesis, provide one method for obtaining such datasets. In this work, we show how such a dataset can be created through combinatorial co-evaporation and high-throughput characterization of Cs_yPb_1−y(Br_xI_1−x)_2−y perovskites. The evaporated films were investigated with a multitude of contact-less characterization methods such as hyperspectral photoluminescence imaging, time-resolved photoluminescence mapping, and grazing-incidence wide-angle X-ray scattering mapping. The results were combined to estimate the potential of the material in terms of the photovoltaic power conversion efficiency as a function of the Cs to Pb and Br to I ratio. Finally, a generalized data schema for combinatorial thin films was developed, and the data of the 3456 individual samples was disseminated in a Findable, Accessible, Interoperable and Reusable (FAIR) way within the Novel Materials Discovery (NOMAD) laboratory (nomad-lab.eu) that is operated by the NFDI consortium FAIRmat (fairmat-nfdi.eu).