cmos compatible bio-realistic implementation with ag/hfo2-based synaptic nanoelectronics for artificial neuromorphic system

The emerging resistive switching devices have attracted broad interest as promising candidates for future memory and computing applications. Particularly, it is believed that memristor-based neuromorphic engineering promises to enable efficient artificial neuromorphic systems. In this work, the synaptic abilities are demonstrated in HfO2-based resistive memories for their multi-level storage capability as well as being compatible with advanced CMOS technology. Both inert metal (TaN) and active metal (Ag) are selected as top electrodes (TE) to mimic the abilities of a biological synapse. HfO2-based resistive memories with active TE exhibit great advantages in bio-realistic implementation such as suitable switching speed, low power and multilevel switching. Moreover, key features of a biological synapse such as short-term/long-term memory, “learning and forgetting”, long-term potentiation/depression, and the spike-timing-dependent plasticity (STDP) rule are implemented in a single Ag/HfO2/Pt synaptic device without the poorly scalable software and tedious process in transistors-based artificial neuromorphic systems.