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CORDIS - Résultats de la recherche de l’UE

Solar cells at the nanoscale: imaging active photoelectrodes in the transmission electron microscope

Final Report Summary - PHOTO-EM (Solar cells at the nanoscale: imaging active photoelectrodes in the transmission electron microscope.)

Photo-EM studied organic-inorganic hybrid nanostructured solar cells, looking at how the individual components intermix and function at the nanometre scale. We have achieved this by taking cross sections of working devices, and imaging them in the transmission electron microscope (TEM) complemented by analytical techniques that allow us to monitor composition and electronic properties, as well as structure and crystallography.
One of the most exciting developments for the photovoltaic community since 2012 has been the a rapid evolution of power conversion efficiency for hybrid perovskite-based solar cells, now reaching certified values larger than 20%. Having developed a successful methodology for the analysis of devices, we focused on the study of perovskite nanocrystals, thin films, and devices. We investigated the relationships between chemistry, structure, and optical properties for a range of novel perovskites, and studied ageing and thermal stability of four types of devices in the TEM. We have created quantitative elemental maps for nanostructured hybrid composites using energy-dispersive X-ray spectroscopy (EDX) and electron energy loss spectroscopy (EELS). Our results contribute to the optimisation of cell architecture and operating procedures, enhancing the lifetime of the devices and promoting perovskite cells as a strong candidate for next-generation solar cells.
During this project we have also been able apply advanced TEM techniques to the study of novel electrode materials for Li-S batteries, based on high surface area, porous nanostructured composites.

Efficient data processing and theoretical interpretation of the microscopy results was essential to the success of this process, and we have built capabilities in these areas to support and guide the experimental work. In particular we have created and used multivariate statistical analysis tools that handle large datasets very efficiently.