SPICE Simulation of Superconductor Memristors
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Cryogenic memristors based on the high-temperature superconductor YBa₂Cu₃O₇−δ show strong potential as nonvolatile memory elements and as unit cells for analog artificial neural networks in applications such as quantum-processor control units, cryogenic data centers, and space electronics. In this work, the switching behavior of cuprate-based memristors is experimentally analyzed from cryogenic to room temperature and interpreted through material-specific physical mechanisms. The proposed interpretation—trapping of injected charge carriers at a metal interface and their field-induced detrapping—is incorporated into a physically inspired compact model. The model is based on a differential balance equation and a current equation derived from space-charge-limited conduction. Comparison with experimental data demonstrates that the model reproduces the key switching characteristics over a broad temperature range (80–300 K). Furthermore, the model is implemented in SPICE, enabling circuit-level simulations. This compact model therefore provides a practical framework for guiding experiments, capturing the essential switching dynamics, and linking device-level characterization with circuit-level design.