Hysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron‐Style Models

Abstract Halide perovskites are at the forefront of active research in many applications, such as high performance solar cells, photodetectors, and synapses and neurons for neuromorphic computation. As a result of ion transport and ionic‐electronic interactions, current and recombination are influenced by delay and memory effects that cause hysteresis of current–voltage curves and long switching times. A methodology to formulate device models is shown, in which the conduction and recombination electronic variables are influenced by internal state variables. The models are inspired in biological frameworks of the Hodgkin–Huxley class of models. Here, the theoretical precedents, the main physical components of the models, and their application to describe dynamical measurements in halide perovskite devices are summarized. The application of several measurement methods is analyzed, as the current–voltage curves at different scan rates, the impedance spectroscopy response, and the time transients. The transition from normal (capacitive) to inverted (inductive) hysteresis, and the convergence of current–voltage curves to a stable value, are described. It is proposed that neuron‐style models capture dynamical complexity with a favorable economy of parameters, toward the identification of the dominant global dynamic processes across a wide voltage span that determines the practical response of different types of devices.