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Graphene-based 3D XNOR-VRRAM with ternary precision for neuromorphic computing

Engineering and Technology

Graphene-based 3D XNOR-VRRAM with ternary precision for neuromorphic computing

B. Alimkhanuly, J. Sohn, et al.

Discover how the innovative use of microfabricated, graphene-based Vertical RRAM (VRRAM) can revolutionize neuromorphic computing, enhancing energy efficiency and recognition accuracy. This exciting research conducted by Batyrbek Alimkhanuly, Joon Sohn, Ik-Joon Chang, and Seunghyun Lee showcases the advantages of graphene in advanced computing technologies.

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