Trap-Controlled Conduction and Metal−Insulator Transition in Superconducting Cuprate Memristors
Memristive devices based on high-temperature superconducting cuprates offer promising routes for neuromorphic computing, yet the microscopic mechanisms governing their resistive switching remain unclear. Here we investigate YBa2Cu3O7−δ (YBCO) memristors across 80–300 K, revealing robust bipolar swit...
| Autores: | , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/416213 |
| Acceso en línea: | http://hdl.handle.net/10261/416213 |
| Access Level: | acceso abierto |
| Palabra clave: | Cryogenic memristor Resistive switching Conduction mechanisms Trap-controlled space-charge-limited conduction High-temperature superconductor Metal−insulator transition Neuromorphic computing |
| Sumario: | Memristive devices based on high-temperature superconducting cuprates offer promising routes for neuromorphic computing, yet the microscopic mechanisms governing their resistive switching remain unclear. Here we investigate YBa2Cu3O7−δ (YBCO) memristors across 80–300 K, revealing robust bipolar switching between high- and low-resistance states with temperature-independent SET and RESET voltages. Current–voltage analysis shows both states follow trap-controlled space-charge-limited conduction, modulated by shallow and deep trap states at an oxygen-deficient interfacial YBCO layer. A key enabler of this behavior is the formation of a deoxygenated layer beneath the top contact, which acts as a dynamic trap region and allows electrostatic control over a field-induced metal–insulator transition. We propose a dual-trap model where deep traps linked to CuO chain fragmentation stabilize a field-induced metal–insulator transition, enabling nonvolatile switching. These insights elucidate the role of trap dynamics in cuprate memristors and highlight their potential for cryogenic neuromorphic platforms compatible with superconducting computing architectures. |
|---|