MemFlash device: floating gate transistors as memristive devices for neuromorphic computing

Memristive devices are promising candidates for future non-volatile memory applications and mixed-signal circuits. In the field of neuromorphic engineering these devices are especially interesting to emulate neuronal functionality. Therefore, new materials and material combinations are currently investigated, which are often not compatible with Si-technology processes. The underlying mechanisms of the device often remain unclear and are paired with low device endurance and yield. These facts define the current most challenging development tasks towards a reliable memristive device technology. In this respect, the MemFlash concept is of particular interest. A MemFlash device results from a diode configuration wiring scheme of a floating gate transistor, which enables the persistent device resistance to be varied according to the history of the charge flow through the device. In this study, we investigate the scaling conditions of the floating gate oxide thickness with respect to possible applications in the field of neuromorphic engineering. We show that MemFlash cells exhibit essential features with respect to neuromorphic applications. In particular, cells with thin floating gate oxides show a limited synaptic weight growth together with low energy dissipation. MemFlash cells present an attractive alternative for state-of-art memresitive devices. The emulation of associative learning is discussed by implementing a single MemFlash cell in an analogue circuit.