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

Author:

Pei Mengjiao1,Wan Changjin1,Chang Qiong2ORCID,Guo Jianhang1,Jiang Sai3,Zhang Bowen1,Wang Xinran1,Shi Yi1ORCID,Li Yun1ORCID

Affiliation:

1. National Laboratory of Solid-State Microstructures, School of Electronic Science and Engineering, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China

2. School of Computing, Tokyo Institute of Technology, Tokyo 152-8550, Japan

3. School of Microelectronics and Control Engineering, Changzhou University, Changzhou 213164, China

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.

Funder

Natural Science Foundation of Jiangsu Province

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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