Polymer-based Neuromorphic Devices

As Moore’s scaling law reaches an end, new brain-like (neuromorphic) computing architectures that embed memory and computation into a single device are highly sought after. Traditional semiconductor memory technology has yet to satisfy the needs of the “artificial synapse” that is the core of the neuromorphic computing architecture. In our group, we use organic semiconductors to mimic synaptic behavior in an electrochemical organic neuromorphic device (ENODe), which couples ionic and electronic currents to emulate the strength of neuron-to-neuron connections. The high linearity and low switching energy of ENODes make them highly suitable for massively parallel neural algorithm accelerators, i.e. brain-like computer chips. Our group’s research focuses on leveraging the ionic/electronic transport properties of polymeric semiconductors to design novel devices for neuromorphic computing.

(a) Schematic of a polymer-based neuromorphic device used to mimic a biological synapse. (b) The conductance (G) of the polymer channel, mimicking the strength of neuron-to-neuron connections, can be tuned by voltage pulses at the gate.