Hysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron-Style Models
Ver/ Abrir
Metadatos
Mostrar el registro completo del ítemcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/160292
comunitat-uji-handle3:10234/160293
comunitat-uji-handle4:
INVESTIGACIONMetadatos
Título
Hysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron-Style ModelsAutoría
Fecha de publicación
2024Editor
WileyISSN
1614-6832; 1614-6840Cita bibliográfica
J. Bisquert, Hysteresis, Impedance, and Transients Effects in Halide Perovskite Solar Cells and Memory Devices Analysis by Neuron-Style Models. Adv. Energy Mater. 2024, 2400442. https://doi.org/10.1002/aenm.202400442Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://onlinelibrary.wiley.com/doi/full/10.1002/aenm.202400442Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
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 ... [+]
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. [-]
Publicado en
Advanced Energy Materials, 2024Datos relacionados
https://doi.org/10.5281/zenodo.10972533Entidad financiadora
European Research Council
Código del proyecto o subvención
info:eu-repo/grantAgreement/EC/HE/101097688
Título del proyecto o subvención
PeroSpiker: Perovskite Spiking Neurons for Intelligent Networks
Derechos de acceso
info:eu-repo/semantics/openAccess
Aparece en las colecciones
- INAM_Articles [517]