Artificial synapse based on 1,4-diphenylbutadiyne with femtojoule energy consumption
*a
and
Weifeng
Zhang
*a
Abstract
Memristors as electronic artificial synapses have attracted increasing attention in neuromorphic computing. Especially, organic small molecule artificial synapses show great promise for low-energy neuromorphic devices. In this study, the basic functions of biological synapses including paired-pulse facilitation/paired-pulse depression (PPF/PPD), spike rate-dependent plasticity (SRDP) and fast Bienenstock–Cooper–Munro learning rules (BCM) have been successfully simulated in the 1,4-diphenylbutadiyne (DPDA) memristor device. Furthermore, ultra-low energy consumption (∼25 fJ per spike), linear and large conductance changes have been obtained in the small molecule DPDA device. This work makes a great contribution to improve the accuracy, speed and to reduce the energy consumption for neuromorphic computing.
- This article is part of the themed collection: 2023 PCCP HOT Articles
Please wait while we load your content...
