Physical Model for the Current–Voltage Hysteresis and Impedance of Halide Perovskite Memristors
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INVESTIGACIONMetadatos
Título
Physical Model for the Current–Voltage Hysteresis and Impedance of Halide Perovskite MemristorsAutoría
Fecha de publicación
2022-03-01Editor
American Chemical SocietyISSN
2380-8195Cita bibliográfica
Berruet, M.; Pérez-Martínez, J. C.; Romero, B.; Gonzales, C.; Al-Mayouf, A. M.; Guerrero, A.; Bisquert, J. Physical Model for the Current–Voltage Hysteresis and Impedance of Halide Perovskite Memristor. ACS Energy Lett. 2022, 7 (3), 1214-1222. DOI: 10.1021/acsenergylett.2c00121Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://pubs.acs.org/doi/abs/10.1021/acsenergylett.2c00121Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
An investigation of the kinetic behavior of MAPbI3 memristors shows that the onset voltage to a high conducting state depends strongly on the voltage sweep rate, and the impedance spectra generate complex capacitive ... [+]
An investigation of the kinetic behavior of MAPbI3 memristors shows that the onset voltage to a high conducting state depends strongly on the voltage sweep rate, and the impedance spectra generate complex capacitive and inductive patterns. We develop a dynamic model to describe these features and obtain physical insight into the coupling of ionic and electronic properties that produce the resistive switching behavior. The model separates the memristive response into distinct diffusion and transition-state-formation steps that describe well the experimental current–voltage curves at different scan rates and impedance spectra. The ac impedance analysis shows that the halide perovskite memristor response contains the composition of two inductive processes that provide a huge negative capacitance associated with inverted hysteresis. The results provide a new approach to understand some typical characteristics of halide perovskite devices, such as the inductive behavior and hysteresis effects, according to the time scales of internal processes. [-]
Publicado en
ACS Energy Lett. 2022, 7, 3, 1214-1222Entidad financiadora
Generalitat Valenciana | Ministerio de Ciencia, Innovación y Universidades | CONICET | Comunidad de Madrid | Universidad Rey Juan Carlos
Código del proyecto o subvención
GRISOLIAP/2019/048 | MICIU/ICTI2017-2020/PID2019-107348GB-100 | Extern Fellowship 2020 | S2018/NMT-4326-SINFOTON2-CM | M2363
Derechos de acceso
Copyright © 2022 The Authors. Published by American Chemical Society
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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