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Eight layers of memristors can be monolithically integrated on a chip to create a three-dimensional circuit capable of implementing a convolutional neural network. The cover shows a false-colour scanning electron microscopy image of part of the memristor array.
The power consumption and carbon emissions of wireless communication networks are expected to substantially increase in the 5G era. The communications industry must therefore develop strategies to optimize the energy efficiency of 5G networks, without compromising spectrum efficiency.
Metal–semiconductor junctions formed between a transition metal ditelluride and monolayer molybdenum disulfide exhibit nearly ideal Schottky–Mott conditions.
This Review Article examines the development of neural interfaces, which can provide a direct, electrical bridge between analogue human nervous systems and digital man-made devices, considering challenges and opportunities created with such technology.
A quantum point contact formed in the two-dimensional electron gas of a LaAlO3/SrTiO3 interface exhibits quantized conductance due to ballistic transport in a controllable number of one-dimensional conducting channels.
Two-dimensional metallic WTe2 and MoTe2 layers can be combined with a semiconducting MoS2 monolayer to create metal–semiconductor junctions that are free from substantial disorder effects and Fermi-level pinning.
A 3D printing technique that produces structures with programmable patterns of charged surface, allowing different functional materials to be deposited in pre-defined regions, can be used to create electronic devices with a single printing step.
A three-dimensional circuit composed of eight layers of monolithically integrated memristive devices is built and used to implement complex neural networks, demonstrating accurate MNIST classification and effective edge detection in videos.