The team has published their work in a letter to Nature.
Because the CNTs and ReRAM materials can be fabricated at temperatures below 200C they can be laid down without damaging circuitry below and theoretically allow highly stacked logic and memory systems.
The researchers integrated more than 1 million RRAM cells and 2 million carbon nanotube field-effect transistors with the ReRAM built above the CNT transistors making a dense 3D architecture of interleaved layers of logic and memory.
The researchers then took advantage of the ability of CNTs to perform as sensors. On the top layer of the chip they placed more than 1 million carbon nanotube-based sensors, which were used to detect and classify ambient gases. Typically the Stanford University team have made ReRAM using metal-oxides such as a sandwich of titanium nitride, hafnium oxide and platinum.
“These structures may be particularly suited for alternative learning-based computational paradigms such as brain-inspired systems and deep neural nets, and the approach presented by the authors is definitely a great first step in that direction,” said Jan Rabaey, a professor of electrical engineering and computer science at the University of California at Berkeley, in a statement issued by MIT.
The next step is for the researchers to work with Analog Devices Inc. (Norwood, Mass.) to develop versions of the system that can take advantage of the ability to sense, store and process on one chip.
This work was funded by the Defense Advanced Research Projects Agency, the National Science Foundation, Semiconductor Research Corporation, STARnet SONIC, and member companies of the Stanford SystemX Alliance.
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