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Photonic curing (PC) can facilitate high-speed perovskite solar cell (PSC) manufacturing because it uses high-intensity light pulses to crystallize perovskite films in milliseconds. However, optimizing PC conditions is challenging due to its many variables, and using power conversion efficiency (PCE) as the optimization metric is both time-consuming and labor-intensive. This work presents a machine learning (ML) approach to optimize PC conditions for fabricating methylammonium lead iodide (MAPbI3) films by quantitatively comparing their ultraviolet-visible (UV-vis) absorbance spectra to thermal annealed (TA) films using four similarity metrics. We perform Bayesian optimization coupled with Gaussian process regression (BO-GP) to minimize the similarity metrics. Refining PC conditions using active learning based on BO-GP models, we achieve a PC MAPbI3 film with an absorbance spectrum closely matching a TA reference film, which is further verified by its crystalline and morphological properties. Thus, we demonstrate that the UV-vis absorption spectrum can accurately proxy film quality. Additionally, we use an AI-based segmentation model for a more efficient grain size analysis. However, when we use the optimized PC condition to fabricate PSCs, we find that interaction between MAPbI3 and the hole transport layer (HTL) during PC critically degrades the PSC performance. By adding a buffer layer between the HTL and MAPbI3, the optimized PC PSCs produce a champion PCE of 11.8%, comparable to the TA reference of 11.7%. Using UV-vis similarity metrics instead of device PCE as the objective in our BO-GP method accelerates the optimization of PC processing conditions for MAPbI3 films.
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Effects of polyethylene oxide particles on the photo-physical properties and stability of FA-rich perovskite solar cells
Abstract In this paper, we use Polyethylene Oxide (PEO) particles to control the morphology of Formamidinium (FA)-rich perovskite films and achieve large grains with improved optoelectronic properties. Consequently, a planar perovskite solar cell (PSC) is fabricated with additions of 5 wt% of PEO, and the highest PCE of 18.03% was obtained. This solar cell is also shown to retain up to 80% of its initial PCE after about 140 h of storage under the ambient conditions (average relative humidity of 62.5 ± 3.25%) in an unencapsulated state. Furthermore, the steady-state PCE of the PEO-modified PSC device remained stable for long (over 2500 s) under continuous illumination. This addition of PEO particles is shown to enable the tuning of the optoelectronic properties of perovskite films, improvements in the overall photophysical properties of PSCs, and an increase in resistance to the degradation of PSCs.
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- Award ID(s):
- 2018326
- PAR ID:
- 10369134
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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