CrossNets: Neuromorphic networks for nanoelectronic implementation Hybrid “CMOL” integrated circuits, incorporating advanced CMOS devices for neural cell bodies, nanowires as axons and dendrites, and single-molecule latching switches as synapses, may be used for the hardware implementation of extremely dense (∼10 7 cells and ∼10 12 synapses per cm 2 ) neuromorphic networks, operating up to 10 6 times faster than their biological prototypes. We are exploring several “CrossNet” architectures that accommodate the limitations imposed by CMOL hardware and should allow effective training of the networks without a direct external access to individual synapses. CrossNet training in the Hopfield mode have been confirmed on a software model of the network.