Abstract:We report the presence of defects in CH3NH3PbI3, which is one of the main factors that deteriorates the performance of perovskite solar cells.
“…The major defect states observed in FTO/TiO 2 /MAPbI 3 /Spiro-OMeTAD/Au devices include a major shallowdefect peak at 0.167 eV and a deep-level defect higher than 0.3 eV above the valence band [44]. The integrated densities of the major defect states in both cases are ∼10 16 cm −3 , which lie within the broad range of later reports, where values of ∼10 15 to 10 17 cm −3 were found [45,46,51,52]. AS measurements sample an ensemble and are limited by assumptions about system homogeneity that can mask nanoscale heterogeneity.…”
Hybrid metal halide perovskites have shown an unprecedented rise as semiconductor building blocks for solar energy conversion and light-emitting applications. Currently, the field moves empirically towards more and more complex chemical compositions, including mixed halide quadruple cation compounds that allow optical properties to be tuned and show promise for better stability. Despite tremendous progress in the field, there is a need for better understanding of mechanisms of efficiency loss and instabilities to facilitate rational optimization of composition. Starting from the device level and then diving into nanoscale properties, we highlight how structural and compositional heterogeneities affect macroscopic optoelectronic characteristics. Furthermore, we provide an overview of some of the advanced spectroscopy and imaging methods that are used to probe disorder and non-uniformities. A unique feature of hybrid halide perovskite compounds is the propensity for these heterogeneities to evolve in space and time under relatively mild illumination and applied electric fields, such as those found within active devices. This introduces an additional challenge for characterization and calls for application of complimentary probes that can aid in correlating the properties of local disorder with macroscopic function, with the ultimate goal of rationally tailoring synthesis towards optimal structures and compositions.Organic-inorganic metal halide perovskites have attracted tremendous research attention as a fascinating class of semiconductors with applications in low-cost, high performance optoelectronics, including photovoltaics [1, 2], light emitting diodes [3], and lasers [4]. In particular, their exceptional photophysical properties, such as high defect tolerance compared to conventional semiconductors [5][6][7][8], long diffusion lengths [9], and long lifetimes [10], have motivated studies that attempt to elucidate the physical properties and interactions underlying desirable charge transport mechanisms and dynamics. Although extraordinarily high power conversion efficiencies have been achieved within about 10 years of research, there is a need to better understand mechanisms of efficiency loss and instabilities to facilitate rational optimization of composition. Currently, the field is driven empirically, going from the archetype CH 3 NH 3 PbI 3 to more and more complex chemical compositions, such as KCsFAMAPbI 3-x Br x (FA=CH(NH 2 ) 2 + , MA=CH 3 NH 3 + ), that allow precise tuning of the optical properties, stabilization of desired phases, and mitigation of photoinduced ion migration [11].Recent studies have revealed that there can be substantial heterogeneities in polycrystalline metal halide perovskite films [12][13][14][15][16][17][18]. These heterogeneities manifest on a variety of different length scales and can significantly influence the underlying structural, transport, and optoelectronic properties. The complex nature of metal halide perovskites has lately evoked the question of 'whether their ex...
“…The major defect states observed in FTO/TiO 2 /MAPbI 3 /Spiro-OMeTAD/Au devices include a major shallowdefect peak at 0.167 eV and a deep-level defect higher than 0.3 eV above the valence band [44]. The integrated densities of the major defect states in both cases are ∼10 16 cm −3 , which lie within the broad range of later reports, where values of ∼10 15 to 10 17 cm −3 were found [45,46,51,52]. AS measurements sample an ensemble and are limited by assumptions about system homogeneity that can mask nanoscale heterogeneity.…”
Hybrid metal halide perovskites have shown an unprecedented rise as semiconductor building blocks for solar energy conversion and light-emitting applications. Currently, the field moves empirically towards more and more complex chemical compositions, including mixed halide quadruple cation compounds that allow optical properties to be tuned and show promise for better stability. Despite tremendous progress in the field, there is a need for better understanding of mechanisms of efficiency loss and instabilities to facilitate rational optimization of composition. Starting from the device level and then diving into nanoscale properties, we highlight how structural and compositional heterogeneities affect macroscopic optoelectronic characteristics. Furthermore, we provide an overview of some of the advanced spectroscopy and imaging methods that are used to probe disorder and non-uniformities. A unique feature of hybrid halide perovskite compounds is the propensity for these heterogeneities to evolve in space and time under relatively mild illumination and applied electric fields, such as those found within active devices. This introduces an additional challenge for characterization and calls for application of complimentary probes that can aid in correlating the properties of local disorder with macroscopic function, with the ultimate goal of rationally tailoring synthesis towards optimal structures and compositions.Organic-inorganic metal halide perovskites have attracted tremendous research attention as a fascinating class of semiconductors with applications in low-cost, high performance optoelectronics, including photovoltaics [1, 2], light emitting diodes [3], and lasers [4]. In particular, their exceptional photophysical properties, such as high defect tolerance compared to conventional semiconductors [5][6][7][8], long diffusion lengths [9], and long lifetimes [10], have motivated studies that attempt to elucidate the physical properties and interactions underlying desirable charge transport mechanisms and dynamics. Although extraordinarily high power conversion efficiencies have been achieved within about 10 years of research, there is a need to better understand mechanisms of efficiency loss and instabilities to facilitate rational optimization of composition. Currently, the field is driven empirically, going from the archetype CH 3 NH 3 PbI 3 to more and more complex chemical compositions, such as KCsFAMAPbI 3-x Br x (FA=CH(NH 2 ) 2 + , MA=CH 3 NH 3 + ), that allow precise tuning of the optical properties, stabilization of desired phases, and mitigation of photoinduced ion migration [11].Recent studies have revealed that there can be substantial heterogeneities in polycrystalline metal halide perovskite films [12][13][14][15][16][17][18]. These heterogeneities manifest on a variety of different length scales and can significantly influence the underlying structural, transport, and optoelectronic properties. The complex nature of metal halide perovskites has lately evoked the question of 'whether their ex...
“…Defect levels are often measured using methods like deep level transient spectroscopy (DLTS) and cathodoluminescence (CL) [10][11][12][13] . However, difficulties in incorporating specific impurities or dopants in a given compound and in attributing measured levels to specific defects make experimental methods less than ideal for an extensive study of defects and impurities in semiconductors.…”
The ability to predict the likelihood of impurity incorporation and their electronic energy levels in semiconductors is crucial for controlling its conductivity, and thus the semiconductor's performance in solar cells, photodiodes, and optoelectronics. The difficulty and expense of experimental and computational determination of impurity levels makes a data-driven machine learning approach appropriate. In this work, we show that a density functional theory-generated dataset of impurities in Cd-based chalcogenides CdTe, CdSe, and CdS can lead to accurate and generalizable predictive models of defect properties. By converting any semiconductor + impurity system into a set of numerical descriptors, regression models are developed for the impurity formation enthalpy and charge transition levels. These regression models can subsequently predict impurity properties in mixed anion CdX compounds (where X is a combination of Te, Se and S) fairly accurately, proving that although trained only on the end points, they are applicable to intermediate compositions. We make machine-learned predictions of the Fermi-level-dependent formation energies of hundreds of possible impurities in 5 chalcogenide compounds, and we suggest a list of impurities which can shift the equilibrium Fermi level in the semiconductor as determined by the dominant intrinsic defects. These 'dominating' impurities as predicted by machine learning compare well with DFT predictions, revealing the power of machine-learned models in the quick screening of impurities likely to affect the optoelectronic behavior of semiconductors.
“…DLTS is a well-accepted powerful tool to investigate defect energy level, type and concentration in thin film photovoltaics 14, 15, 37–40 . It uses the transient capacitance of p–n junction at different temperature as a probe to monitor the changes in charge state of a deep defect center 41 .…”
Section: Resultsmentioning
confidence: 99%
“…The shift of quasi-Fermi levels is positively correlated with the nonequilibrium carrier concentration. The difference between the two quasi-Fermi levels determines V OC of the solar cell 14 .Fig. 6Influence of defect levels on the CdS/Sb 2 Se 3 solar cells.…”
Antimony selenide is an emerging promising thin film photovoltaic material thanks to its binary composition, suitable bandgap, high absorption coefficient, inert grain boundaries and earth-abundant constituents. However, current devices produced from rapid thermal evaporation strategy suffer from low-quality film and unsatisfactory performance. Herein, we develop a vapor transport deposition technique to fabricate antimony selenide films, a technique that enables continuous and low-cost manufacturing of cadmium telluride solar cells. We improve the crystallinity of antimony selenide films and then successfully produce superstrate cadmium sulfide/antimony selenide solar cells with a certified power conversion efficiency of 7.6%, a net 2% improvement over previous 5.6% record of the same device configuration. We analyze the deep defects in antimony selenide solar cells, and find that the density of the dominant deep defects is reduced by one order of magnitude using vapor transport deposition process.
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