How to stabilize standard perovskite solar cells to withstand operating conditions under an ambient environment for more than 1000 hours using simple and universal encapsulation

Belich, Nikolai A.; Petrov, Andrey A.; Ivlev, Pavel A.; Udalova, Natalia N.; Pustovalova, A. A.; Goodilin, Eugene A.; Tarasov, Alexey B.

doi:10.1016/j.jechem.2022.12.010

Cited by 19 publications

(9 citation statements)

References 52 publications

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“…[7][8][9] This problem is of particular importance in the rapidly developing field of perovskite solar cells (PSCs), as they are likely more prone to reliability and stability issues under external biasing. While the PSC community has made great progress in improving both the device efficiency and the longterm stability, [10][11][12][13][14][15] the research on PID of PSCs has been scarce. As a result, there are so far no strategies available in the literature that address the mitigation of PID in PSCs.…”

Section: Introductionmentioning

confidence: 99%

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiO_x Barrier Layer

Nakka,

Shen,

Aberle

et al. 2023

Solar RRL

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While the efficiency of perovskite solar cells has been increasing rapidly in recent years, studies on potential‐induced degradation (PID) in these devices have so far been very limited. Herein, the first successful mitigation of PID in glass‐encapsulated perovskite solar cells is reported. A thin NiOx blocking layer between the indium tin oxide and the self‐assembled monolayer is proposed to suppress the PID in these solar cells. Two groups of devices are fabricated, with and without the presence of the NiOx layer. When −1000 V is applied between the short‐circuited solar cell and the front glass pane, the original devices without NiOx only retain about 27% of the initial efficiency, and the modified devices with NiOx retained ≈65% after an extended stress duration of 96 h. The Na+ ions from the glass pane occupy NiOx vacancies under high voltage stress and, as a result, the Nax ion migration toward the perovskite layer is heavily suppressed due to the introduction of NiOx. The modified devices also demonstrate good long‐term stability, retaining more than 80% of initial efficiency after the PID stress test. The results of this work are helpful on the journey toward successful commercialization of perovskite solar cells.

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Section: Introductionmentioning

confidence: 99%

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiO_x Barrier Layer

Nakka,

Shen,

Aberle

et al. 2023

Solar RRL

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show abstract

“…In the first example from Belich et al [29] , (Data from Figure S5, supporting information), a PSC was encapsulated and then exposed to standard conditions under an ambient environment for more than 1000 h. The reference cell (before stressing) is close to the optimum of our simulation, where it can be difficult to make accurate predictions. In the ff-J sc plane, it is very close to the path of changes in anion density, which is detected by the RF very well.…”

Section: Testing/applicationsmentioning

confidence: 97%

Identifying Performance Limiting Parameters in Perovskite Solar Cells Using Machine Learning

Zbinden,

Knapp,

Tress

2024

Solar RRL

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Herein, it is shown that machine learning (ML) methods can be used to predict the parameter that limits the solar‐cell performance most significantly, solely based on the current density–voltage (J–V) curve under illumination. The data (11’150 J–V curves) to train the model is based on device simulation, where 20 different physical parameters related to charge transport and recombination are varied individually. This approach allows to cover a wide range of effects that could occur when varying fabrication conditions or during degradation of a device. Using ML, the simulated J–V curves are classified for the changed parameter with accuracies above 80%, where Random Forests perform best. It turns out that the key parameters, short‐circuit current density, open‐circuit voltage, maximum power conversion efficiency, and fill factor are sufficient for accurate predictions. To show the practical relevance, the ML algorithms are then applied to reported devices, and the results are discussed from a physics perspective. It is demonstrated that if some specified conditions are met, satisfying results can be reached. The proposed workflow can be used to better understand a device's behavior, e.g., during degradation, or as a guideline to improve its performance without costly and time‐consuming lab‐based trial‐and‐error methods.

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“…57 However, most experimental studies focus on the effect of encapsulation on the long-term stability, temperature resistance, and humidity resistance of the PSC. [58][59][60] Nevertheless, it is expected that the encapsulation layer can release the interlayer stress and delay the propagation of cracks. A more detailed understanding of the effect of encapsulation will require further experimental and theoretical investigation.…”

Section: External Structure Optimisation To Achieve Stretchable Benda...mentioning

confidence: 99%

Perspectives on the mechanical robustness of flexible perovskite solar cells

Zhang

Gong

et al. 2023

Energy Adv.

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How to stabilize standard perovskite solar cells to withstand operating conditions under an ambient environment for more than 1000 hours using simple and universal encapsulation

Cited by 19 publications

References 52 publications

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiO_x Barrier Layer

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiO_x Barrier Layer

Identifying Performance Limiting Parameters in Perovskite Solar Cells Using Machine Learning

Perspectives on the mechanical robustness of flexible perovskite solar cells

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How to stabilize standard perovskite solar cells to withstand operating conditions under an ambient environment for more than 1000 hours using simple and universal encapsulation

Cited by 19 publications

References 52 publications

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiOx Barrier Layer

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiOx Barrier Layer

Identifying Performance Limiting Parameters in Perovskite Solar Cells Using Machine Learning

Perspectives on the mechanical robustness of flexible perovskite solar cells

Contact Info

Product

Resources

About

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiO_x Barrier Layer

Mitigation of Potential‐Induced Degradation in Glass‐Encapsulated Perovskite Solar Cells Using a NiO_x Barrier Layer