Deducing transport properties of mobile vacancies from perovskite solar cell characteristics
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abstract
The absorber layers in perovskite solar cells possess a high concentration of mobile ion vacancies. These vacancies undertake thermally activated hops between neighboring lattice sites. The mobile vacancy concentration N0 is much higher and the activation energy EA for ion hops is much lower than is seen in most other semiconductors due to the inherent softness of perovskite materials. The timescale at which the internal electric field changes due to ion motion is determined by the vacancy diffusion coefficient Dv and is similar to the timescale on which the external bias changes by a significant fraction of the open-circuit voltage at typical scan rates. Therefore, hysteresis is often observed in which the shape of the current–voltage, J–V, characteristic depends on the direction of the voltage sweep. There is also evidence that this defect migration plays a role in degradation. By employing a charge transport model of coupled ion-electron conduction in a perovskite solar cell, we show that EA for the ion species responsible for hysteresis can be obtained directly from measurements of the temperature variation of the scan-rate dependence of the short-circuit current and of the hysteresis factor H. This argument is validated by comparing EA deduced from measured J–V curves for four solar cell structures with density functional theory calculations. In two of these structures, the perovskite is MAPbI3, where MA is methylammonium, CH3NH3; the hole transport layer (HTL) is spiro (spiro-OMeTAD, 2,2′,7,7′- tetrakis[N,N-di(4-methoxyphenyl) amino]-9,9′-spirobifluorene) and the electron transport layer (ETL) is TiO2 or SnO2. For the third and fourth structures, the perovskite layer is FAPbI3, where FA is formamidinium, HC(NH2)2, or MAPbBr3, and in both cases, the HTL is spiro and the ETL is SnO2. For all four structures, the hole and electron extracting electrodes are Au and fluorine doped tin oxide, respectively. We also use our model to predict how the scan rate dependence of the power conversion efficiency varies with EA, N0, and parameters determining free charge recombination.
