AMHERST, Mass., Nov. 15, 2018 – A research team at the University of Massachusetts Amherst says it has developed a promising building block for the next generation of nonvolatile random-access memory, artificial neural networks and bio-inspired computing systems.
The team, led by Qiangfei Xia of the electrical and computer engineering department, says the memristor crossbar arrays they have built are, “to the best of our knowledge, the first high-density electronic circuits with individually addressable components scaled down to 2 nanometers dimension built with foundry-compatible fabrication technologies.” The results appear in the journal Nature Nanotechnology.
“This work will lead to high-density memristor arrays with low power consumption for both memory and unconventional computing applications,” says Xia. “The working circuits have been made with technologies that are widely used to build a computer chip.”
Understanding the scale of this work is important, Xia says. One nanometer (nm) is one billionth of a meter. The diameter of a human hair is about 100 micrometers, or 100,000 nanometers. Two nanometers are just a few atoms wide. A crossbar is a matrix of tiny switches.
In the Nature Nanotechnology paper, Xia’s research team explains that organizing small memristors into high-density crossbar arrays is critical to meet the ever-growing demands in high-capacity and low-energy consumption, but is challenging because of difficulties in making highly ordered and highly conductive nanoelectrode arrays. The team has addressed this challenge by developing “nanofins,” metallic nanostructures with very high height-to-width ratio and hence vastly reduced resistance, as the electrodes.
This research is an outgrowth of Xia’s 2013, five-year, $400,000 grant from the National Science Foundation (NSF) Faculty Early Career Development (CAREER) Program to develop emerging nanoelectronic devices. Xia’s NSF research has been addressing the biggest obstacle for the continued operation of Moore’s Law, which states that the number of transistors on integrated circuits doubles approximately every two years.
“It (Moore’s Law) worked perfectly for more than 40 years, but now we’re reaching its fundamental limit, due to the quantum effects related to electron flow,” says Xia. “So, we absolutely need new devices that can do a better job.”
In addition to Xia, the other authors of the Nature Nanotechnology paper are Shuang Pi, Can Li, Hao Jiang, Weiwei Xia, Joshua Yang and Huolin Xin.
Link to paper:
Source: UMass Amherst