Distinction of mechanisms causing experimental degradation of perovskite solar cells by simulating associated pathways

Abstract

Mechanisms responsible for the degradation of perovskite solar cells are identified by using a novel simulation method. Mutual correlations of current-voltage parameters measured along time are plotted to produce trajectories...

Identifying Performance Limiting Parameters in Perovskite Solar Cells Using Machine Learning

“…Known applications of ML in the field of PSC that go in a similar direction are, for example, identifying the dominant recombination loss, [18] or finding the optimum annealing temperature and solvent ratios, determined based on J-V curves. [19] Similar to what we present here, parameter variation and comparison to a reference device [20] have been shown to be able to detect the major loss mechanism upon degradation. In this last example, the classification was done without ML.…”

Tungsten-Doped ZnO as an Electron Transport Layer for Perovskite Solar Cells: Enhancing Efficiency and Stability

“…Perovskite solar cells (PSCs) have become one of the fastest-growing technologies in photovoltaics due to exceptionally tailored optoelectronic parameters as dictated by a higher power conversion efficiency (PCE) of up to 26% in combination with joint efforts and methods to improve both device fabrication and photostability. − Nevertheless, PSCs still need to improve their stability, allowing doubts about technological development and growth. , PSCs have become more robust and stable by optimizing the perovskite materials and transport layers. ,, A tremendous amount of work and processes have been considered for controlling and modifying interfaces to obtain stability of PSCs. ,, Perovskite materials offer many benefits, such as excellent optical absorption, tunable band gaps, long diffusion lengths, high carrier mobilities, and low-cost fabrication processes. ,− For instance, the materials’ tunable band gap properties have made it possible to develop high-efficiency tandem solar cells and better multispectral sorters for image sensor technologies. ,− In the case of PSCs, the perovskite material is placed between carrier transport layers (CTLs), which are sandwiched between a front transparent material such as indium tin oxide (ITO) or fluorine-doped tin oxide and a metal back reflector such as gold (Au), aluminum (Al), or silver (Ag). , On the other hand, the electron transport material (ETM) in the PSCs is critical in controlling electron extraction and hole blocking from the perovskite absorber and transporting electrons to the contact, which is essential for eliminating electrical shunt resistance from the electrode to the perovskite absorber. ,, Therefore, the electron transport layer (ETL) needs to be efficient enough to meet several essential requirements, including high transparency, good conductivity, and a suitable work function to develop highly efficient PSCs. ,,, Besides, the quality of the ETL controls the perovskite film growth in n–i–p configuration. , Metal oxides (MO X ) such as titanium dioxide (TiO 2 ), tin oxide (SnO 2 ), and zinc oxide (ZnO) can provide excellent optoelectronic properties for PSCs. These materials reduce shunt resistance between the transparent contact and perovskite interface, improving electron extraction and transportation to the corresponding electrode. − Various methods are em...…”

“…5,6 PSCs have become more robust and stable by optimizing the perovskite materials and transport layers. 2,6,7 A tremendous amount of work and processes have been considered for controlling and modifying interfaces to obtain stability of PSCs. 5,6,8 Perovskite materials offer many benefits, such as excellent optical absorption, tunable band gaps, long diffusion lengths, high carrier mobilities, and low-cost fabrication processes.…”

Advanced Characterization and Degradation Analysis of Perovskite Solar Cells Using Machine Learning and Bayesian Optimization

“…Joseph Chakar (joseph.chakar@polytechnique.edu), Arthur Julien, Karim Medjoubi, Jorge Posada, Jean-François Guillemoles, Jean-Baptiste Puel, and Yvan Bonnassieux Advanced Characterization and Degradation Analysis of Perovskite Solar Cells using Machine Learning and Bayesian Optimization We consider in-house triple-cation perovskite solar cells with different concentrations of PbSCN and define the parameters of a 1D driftdiffusion model [1] based on prior experience and the literature [2].…”