Flexible Co-TCPP nanosheet-based memristor for neuromorphic computing and simulation of human water turnover at different temperatures

Abstract

The integration of memristors and temperature sensors enables high-precision temperature recognition and real-time monitoring. Importantly, understanding the impact of temperature variations on the human body is also critical. In this study, the Co-TCPP (TCPP: 4 (4-carboxyphenyl)) nanosheet-based memristor demonstrates typical synaptic plasticity at a low operating voltage of 160 mV, with synaptic characteristics remaining well-preserved even after 2000 bending cycles with a 5 mm radius. The neuromorphic system constructed using flexible Co-TCPP nanosheet-based memristor achieves a recognition accuracy of up to 95.99 %, meanwhile has a faster pixel image reconstruction speed. Notably, the Co-TCPP nanosheet-based memristor and NTC (negative temperature coefficient) temperature sensor effectively simulate moisture turnover at different temperatures. As the temperature increases, both moisture consumption and replenishment rise accordingly. These results highlight the significant potential of this approach in artificial intelligence and the future development of bionic robots.