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By reversibly intercalating ions between the layers of two‐dimensional graphene, Feng Xiong and co‐workers at Pitt develop a novel artificial synapse for neuromorphic computing, as described in article number 1802353. With over 250 tunable analog states, good energy efficiency, and promising scalability, these electrochemical synapses can lead to the hardware implementation of neural networks and...
Brain‐inspired neuromorphic computing has the potential to revolutionize the current computing paradigm with its massive parallelism and potentially low power consumption. However, the existing approaches of using digital complementary metal–oxide–semiconductor devices (with “0” and “1” states) to emulate gradual/analog behaviors in the neural network are energy intensive and unsustainable; furthermore,...
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