 This research has developed a graphene-based memrister with a lateral structure that consumes less energy than traditional memristers. The memrister is capable of emulating typical synaptic behavior and is used to create a reservoir computing network with a high accuracy of 95.74%. This work could provide a cost-effective solution for mass production of artificial synapse hardware platforms, which would greatly accelerate the development of neural network computing hardware platforms. This article was authored by Chin Men, Wang Jingfen, Dong Hao, and others.