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Neuron-inspired flexible memristive device on silicon (100)

Published 18 Jun 2017 in physics.app-ph and cond-mat.mes-hall | (1706.05645v1)

Abstract: Comprehensive understanding of the world's most energy efficient powerful computer, the human brain, is an elusive scientific issue. Still, already gained knowledge indicates memristors can be used as a building block to model the brain. At the same time, brain cortex is folded allowing trillions of neurons to be integrated in a compact volume. Therefore, we report flexible aluminium oxide based memristive devices fabricated and then derived from widely used bulk mono-crystalline silicon (100). We use complementary metal oxide semiconductor based processes to layout the foundation for ultra large scale integration (ULSI) of such memory devices to advance the task of comprehending a physical model of human brain.

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