3 years ago

Artificial Synapses with Short- and Long-Term Memory for Spiking Neural Networks Based on Renewable Materials

Artificial Synapses with Short- and Long-Term Memory for Spiking Neural Networks Based on Renewable Materials
Jang-Sik Lee, Youngjun Park
Emulation of biological synapses that perform memory and learning functions is an essential step toward realization of bioinspired neuromorphic systems. Artificial synaptic devices have been developed based mostly on inorganic materials and conventional semiconductor device fabrication processes. Here, we propose flexible biomemristor devices based on lignin by a simple solution process. Lignin is one of the most abundant organic polymers on Earth and is biocompatible, biodegradable, as well as environmentally benign. This memristor emulates several essential synaptic behaviors, including analog memory switching, short-term plasticity, long-term plasticity, spike-rate-dependent plasticity, and short-term to long-term transition. A flexible lignin-based artificial synapse device can be operated without noticeable degradation under mechanical bending test. These results suggest lignin can be a promising key component for artificial synapses and flexible electronic devices.

Publisher URL: http://dx.doi.org/10.1021/acsnano.7b03347

DOI: 10.1021/acsnano.7b03347

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