Responsive Molecules for Organic Neuromorphic Devices: Harnessing Memory Diversification.

Abstract

In the brain, both the recording and decaying of memory information following external stimulus spikes are fundamental learning rules that determine human behaviors. The former is essential to acquire new knowledge and update the database, while the latter filters noise and autorefresh cache data to reduce energy consumption. To execute these functions, the brain relies on different neuromorphic transmitters possessing various memory kinetics, which can be classified as nonvolatile and volatile memory. Inspired by the human brain, nonvolatile and volatile memory electronic devices have been employed to realize artificial neural networks and spiking neural networks, respectively, which have emerged as essential tools in machine learning. Molecular switches, capable of responding to electrical, optical, electrochemical, and magnetic stimuli, display a disruptive potential for emulating information storage in memory devices. This Review highlights recent developments on responsive molecules, their interfacing with low-dimensional nanostructures and nanomaterials, and their integration into electronic devices. By capitalizing on these concepts, a unique account of neurotransmitter-transfer electronic devices based on responsive molecules with ad hoc memory kinetics is provided. Finally, future directions, challenges, and opportunities are discussed on the use of these devices to engineer more complex logic operations and computing functions at the hardware level.