atomistic multiscale modelling of defects in halide perovskites
Shuxia Tao a
a Materials Simulation and Modelling, Department of Applied Physics, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
Materials for Sustainable Development Conference (MATSUS)
Proceedings of MATSUS23 & Sustainable Technology Forum València (STECH23) (MATSUS23)
#DeModeP23 - Characterisation and modeling of devices
VALÈNCIA, Spain, 2023 March 6th - 10th
Organizers: Enrique Hernández Balaguera and Alison Walker
Invited Speaker, Shuxia Tao, presentation 060
DOI: https://doi.org/10.29363/nanoge.matsus.2023.060
Publication date: 22nd December 2022

Perovskites is a class of materials with notable crystal structure of ABX3, exceptionally wide tunability in chemical compositions and dimensionality in crystal-structures. Due to their exceptional optoelectronic properties, they are widely used for converting and storing (solar) energy, e.g. oxide perovskites as photocatalysts, halide perovskites as absorbers in solar cells, nitride perovskites as

mechanical energy harvesters. In these applications, the understanding of optoelectronic properties, chemical stability and their changes upon external stimuli (light excitation, mechanical, thermal and chemical stress) are paramount.

In this talk, I will show how our research group investigate these properties using atomistic multiscale modelling by combing electronic structure calculations with reactive molecular dynamics simulations. Her focus is on halide perovskites and the impact of defects on the efficiency and the stability of perovskite solar cells. We identify harmful defects which lead to either recombination losses and/or chemical degradations and show several strategies to mitigate and passivate these defects. These include engineering the composition of perovskite absorbers, optimizing interfaces with contact materials, and finetuning growth conditions. The atomistic insights provide a basis for further improving the efficiency and stability of perovskite materials and devices. The multiscale computational framework can be enhanced with The emerging data-driven approach and straightforwardly applied to other materials and applications.

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