Perovskite plasticity: exploiting instability for self-optimized performance

Julia van der Burgt^a, Francesca Scalerandi^a, Jeroen de Boer^a, Susan Rigter^a^,^b, Erik Garnett^a^,^b

^aAMOLF, Science Park, 102, Amsterdam, Netherlands

^bUniversity of Amsterdam, Science Park 904, Amsterdam, 1098, Netherlands

Materials for Sustainable Development Conference (MATSUS)
Proceedings of nanoGe Spring Meeting 2022 (NSM22)

#PhotoPero22. Photophysics of Halide Perovskites and Related Materials - from Bulk to Nano

Online, Spain, 2022 March 7th - 11th

Organizers: Sascha Feldmann, Annamaria Petrozza and Ajay Ram Srimath Kandada

Contributed talk, Julia van der Burgt, presentation 054
DOI: https://doi.org/10.29363/nanoge.nsm.2022.054
Publication date: 7th February 2022

Halide perovskites are the new wonder material of the optoelectronics community due totheir outstanding photoluminescence quantum yield, tunable emission wavelength and simplesolution or vapor-phase deposition. At the same time, their facile ion migration andtransformation under optical, electrical and chemical stress are seen as a major limitation fordevice implementation. Mixed halide perovskites are particularly problematic sinceoptical excitation can cause changes in the band gap that are detrimental for solar cell and light-emitting diode efficiency and stability. In this work, instead of preventing suchchanges, we exploit photo-induced halide segregation in perovskites to enable responsive,reconfigurable and self-optimizing materials. We show how a mixed halide perovskite film can betrained to give highly directional light emission using a nanophotonic microlens: through a self-optimized process of halide photosegregation, the system mimics the training stimulus. Longertraining leads to more highly directional emission, while the different halide migration kineticsin the light (fast training) and dark (slow forgetting) allow for material memory. This self-optimized material performs significantly better than lithographically aligned quantum dots[1], because it eliminates lens-emitter misalignment and automatically corrects for lens aberrations.Our system shows a combination of mimicking, improving over time, and memory, which make itcompatible with the basic requirements for learning,[2,3] and give the intriguing prospectof intelligent optoelectronic materials

References:

[1] J. S. Van Der Burgt, C. D. Dieleman, E. Johlin, J. J. Geuchies, A. J. Houtepen, B. Ehrler, andE. C. Garnett, “Integrating Sphere Fourier Microscopy of Highly Directional Emission,”ACSPhotonics, vol. 8, no. 4, pp. 1143–1151, 2021

[2] J. de Houwer, D. Barnes-Holmes, and A. Moors, “What is learning? On the nature and meritsof a functional definition of learning,”Psychonomic Bulletin and Review, vol. 20, no. 4, pp. 631–642, 2013

[3] C. Kaspar, B. J. Ravoo, W. G. van der Wiel, S. V. Wegner, and W. H. Pernice, “The rise ofintelligent matter,”Nature, vol. 594, no. 7863, pp. 345–355, 2021

Acknowledgements:

This work is part of the research programme Mat4Sus, which is financed by the Netherlands Organisation for Scientific Research (NWO). The work has been carried out at Amolf, an NWO funded institute.

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