Title: Neuron-inspired flexible memristive device on silicon (100),
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.