Temperature-induced transition between resistive switching modes of parylene-based memristive crossbar structures

In order to create neuromorphic computing systems (NCSs) capable of efficiently solving artificial intelligence problems, elements with short- and long-term memory effects are required. Memristors are promising candidates for the implementation of such elements since they demonstrate volatile and nonvolatile resistive switching (RS) modes. Of particular interest are structures that realize both RS modes in a single device. In this work, parylene-based nanocomposite memristors with MoO$_3$ nanoparticles have been studied in crossbar architecture, which is convenient for NCS implementation. For these structures, a reversible temperature-induced transition between volatile and nonvolatile RS modes was found if local, controlled via the compliance current, or external temperature is fine-tuned. In addition, the crossbar structures showed high endurance to cyclic RS, ability to retain states in nonvolatile mode and multilevel nature of RS. The obtained results open the possibility of using parylene-based crossbar structures in bioinspired NCSs.