Perovskite is one of the most promising photovoltaic materials for the future. While
low stability has long been the bottleneck issue limiting their commercialization. In the
past, by using enhanced sampling coupled with machine learning (ML) potential model,
I have unraveled the degradation mechanism of organic inorganic hybrid perovskite,
FAPbI3, the most used component in solar cells.
However, in experiments, perovskite photovoltaic films are heavily doped for better
opto-electrical performance. Thus, understanding of ion diffusion and how it affects the
degradation is a widely recognized but unresolved problem. In my proposal for the
Bidmap fellowship, I aim to build a framework to accelerate the nested Monte Carlo
and molecular dynamics (MC/MD) simulations for study of the interplay between
diffusion and phase transitions.
The accelerated framework will extend the time and length scales of the current
cross-scale simulations. Consequently, it will facilitate a comprehensive mapping of the
relation between ion diffusion and stability of photovoltaic perovskites. The project is
poised to unveil critical insights, paving the way toward addressing the stability issue
of perovskite solar cells.
This seminar will be delivered remotely but an in-person viewing will be offered in 373 Cory Hall. Lunch will be provided.
Location:
373 Cory Hall