Three-dimensional integration of nanotechnologies for computing and data storage on a single chip

By M. Shulaker, G. Hills, R. Park, R. Howe, Krishna C. Saraswat, H. Philip Wong, Subhasish G. Mitra. Nature, 2017

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Fully memristive neural networks for pattern classification with unsupervised learning (2018, positive): “Progress has been made in building hardware ANNs that incorporate redox memristors 2–14 , phase-change memristors 15–18 , organic transistors 19 and conventional CMOS circuits 20,21 to emulate synapses by utilizing their tuneable conductance as synaptic weights.”
Skin-inspired highly stretchable and conformable matrix networks for multifunctional sensing (2018, background): “Besides, different functional sensors could be fabricated on the same sensory node in stack with insulation of PI dielectric thin ﬁ lms, regarded as stacked layout or 3D integration 57,58 (schematically shown in Supplementary Fig.”
Memory devices and applications for in-memory computing (2020, background): “To achieve a denser and more fine-grained connectivity between memory and processing units, even three-dimensional (3D) monolithic integration has been proposed 10 .”
The future of electronics based on memristive systems (2018, background): “…not be able to provide the required bandwidth between the memristor layer and the CMOS circuitry, and monolithic integration of memristor arrays directly on top of CMOS circuitry with very-high-density local interconnects is necessary and has indeed been shown experimentally to be feasible 52,53 .”