A Smarter Pavlovian Dog with Optically Modulated Associative Learning in an Organic Ferroelectric Neuromem

Abstract

Associative learning is a critical learning principle uniting discrete ideas and percepts to improve individuals’ adaptability. However, enabling high tunability of the association processes as in biological counterparts and thus integration of multiple signals from the environment, ideally in a single device, is challenging. Here, we fabricate an organic ferroelectric neuromem capable of monadically implementing optically modulated associative learning. This approach couples the photogating effect at the interface with ferroelectric polarization switching, enabling highly tunable optical modulation of charge carriers. Our device acts as a smarter Pavlovian dog exhibiting adjustable associative learning with the training cycles tuned from thirteen to two. In particular, we obtain a large output difference (>103), which is very similar to the all-or-nothing biological sensory/motor neuron spiking with decrementless conduction. As proof-of-concept demonstrations, photoferroelectric coupling-based applications in cryptography and logic gates are achieved in a single device, indicating compatibility with biological and digital data processing.

Pseudo-transistors for emerging neuromorphic electronics

“…Ferroelectric material is a dielectric material with large application potential because its polarization intensity can be precisely regulated by drain. Take P(VDF-TrFE) as an example [ 112 ]. The ferroelectric properties of P(VDF-TrFE) are comparable to those of chalcogenide oxide ferroelectric materials.…”

A Bio‐Inspired Neuromorphic Sensory System

“…[9,15] To achieve the computing-in-memory, many systems based on emergent devices such as memristive devices that have the capability of parallel computing and characters similar to biological neurons and synapses, have been designed to accelerate deep neural networks (DNNs) or realize spiking neural networks (SNNs). [3,[16][17][18][19][20][21][22][23][24][25][26] Sometimes, processing units were integrated with sensors, so that these systems could preliminarily and selectively extract useful data from a large volume of raw data by suppressing unwanted noise or distortion, or by enhancing the features for further processing, which are especially important in data-intensive applications. [9,[27][28][29][30][31] To detect and process environmental information in real time, some attempts have also been taken to combine the computing-in-memory and the computing-in-sensor, so that the sense of feeling can be generalized.…”

Emerging Logic Devices beyond CMOS

“…For example, Hao et al proposed a self-powered optoelectronic synapse based on organic asymmetric heterojunctions that can realize sensing and multimode logic computation for the mimic of the retina . Furthermore, Pei et al demonstrated an optically modulated organic neuromem with a two-terminal planar architecture using ferroelectric polymers and small-molecule semiconductors (Figure a–c) . In this device, the photoferroelectric coupling can contribute to sensing, processing, and memory functions in a single device for further cryptographical applications.…”

“…(b) Schematic diagram of the optoelectronic logic switch. (c) Current switching behavior obtained by manipulating the input voltage under continuous illumination with different intensities . Reproduced with permission from ref .…”

“…(c) Current switching behavior obtained by manipulating the input voltage under continuous illumination with different intensities . Reproduced with permission from ref . Copyright 2021, Exclusive Licensee Science and Technology Review Publishing House.…”