Ghoneim, Mohamed T.; Zidan, Mohammed A.; Salama, Khaled N.; Hussain, Muhammad Mustafa(2014 14th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA), Institute of Electrical and Electronics Engineers (IEEE), 2014-07)[Conference Paper]
Neuromorphic computer will need folded architectural form factor to match brain cortex's folded pattern for ultra-compact design. In this work, we show a state-of-the-art CMOS compatible pragmatic fabrication approach of building structurally foldable and densely integrated neuromorphic devices for non-volatile memory applications. We report the first ever memristive devices with the size of a motor neuron on bulk mono-crystalline silicon (100) and then with trench-protect-release-recycle process transform the silicon wafer with devices into a flexible and semi-transparent silicon fabric while recycling the remaining wafer for further use. This process unconditionally offers the ultra-large-scale-integration opportunity-increasingly critical for ultra-compact memory.
Ghoneim, Mohamed T.; Zidan, Mohammed A.; Salama, Khaled N.; Hussain, Muhammad Mustafa(Microelectronics Journal, Elsevier BV, 2014-11)[Article]
The advantages associated with neuromorphic computation are rich areas of complex research. We address the fabrication challenge of building neuromorphic devices on structurally foldable platform with high integration density. We present a CMOS compatible fabrication process to demonstrate for the first time memristive devices fabricated on bulk monocrystalline silicon (100) which is next transformed into a flexible thin sheet of silicon fabric with all the pre-fabricated devices. This process preserves the ultra-high integration density advantage unachievable on other flexible substrates. In addition, the memristive devices are of the size of a motor neuron and the flexible/folded architectural form factor is critical to match brain cortex's folded pattern for ultra-compact design.
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