Neuromorphic electronic behavior in transition metal oxide systems - From resistive switching to artificial synapses and neurons

The information age we live in is supported on a physical under-layer of electronic hardware, which originates
in condensed matter physics research. The mighty progress made in silicon based technology seemed endless.
However, with the smallest feature size of transistors reaching down to mere 5 nm, this technology is reaching
an unavoidable physical limit. This calls for exploration of new alternatives.
Neuromorphic inspired systems are making fast progress. But this is based either on dedicated hardware made
with conventional electronics, or in software, such Deep Neural Networks, running in conventional computers.
Resistive switching phenomena opens the way to explore a  technological disruptive solution, namely, implement
simple devices with the required functionalities to directly build neuromorphic systems. In this talk we shall describe
recent efforts towards making artificial neurons and synapses using transition metal oxides, including Mott strongly
correlated systems.

Refs
[Review] Challenges in materials and devices for resistive-switching-based neuromorphic computing; Journal of Applied Physics 124, 211101 (2018)

Subthreshold firing in Mott nanodevices; Nature, 569 (7756), pp.388-392 (2019).

An ultra-compact leaky-integrate-and-fire model for building spiking neural networks;; Scientific Reports, 9, 11123 (2019).

Biologically relevant dynamical behaviors realised in an ultra-compact neuron model; Frontiers in Neurosciences (accepted).