![]() ![]() The incubation method, while practical for industry, doesn’t align the nanotubes at all. “To put these length scales into context, it’s like trying to cover the entire state of New Hampshire in perfectly oriented dry spaghetti.” “It’s really hard to lay down billions of tiny 1-nanometer diameter nanotubes in a perfect orientation across a large 200-millimeter wafer,” Bishop explains. They’re “either stuck onto the wafer in random orientations like cooked spaghetti or all aligned in the same direction like uncooked spaghetti still in the package,” she says.Īligning the nanotubes perfectly in a CNFET leads to ideal performance, but alignment is difficult to obtain. The performance of the CNFET is dictated in large part by the deposition process, says Bishop, which affects both the number of carbon nanotubes on the surface of the wafer and their orientation. ![]() One of the most effective ways to build CNFETs in the lab is a method for depositing nanotubes called incubation, where a wafer is submerged in a bath of nanotubes until the nanotubes stick to the wafer’s surface. “You can’t do this with silicon-based technology, because you would melt the layers underneath.”Ī 3D computer chip, which might combine logic and memory functions, is projected to “beat the performance of a state-of-the-art 2D chip made from silicon by orders of magnitude,” he says. “This means that you can actually build layers of circuits right on top of previously fabricated layers of circuits, to create a three-dimensional chip,” Shulaker explains. Unlike silicon-based transistors, which are made at temperatures around 450 to 500 degrees Celsius, CNFETs also can be manufactured at near-room temperatures. That trend may be nearing its end, however, as increasing numbers of transistors packed into integrated circuits do not appear to be increasing energy efficiency at historic rates.ĬNFETs are an attractive alternative technology because they are “around an order of magnitude more energy efficient” than silicon-based transistors, says Shulaker. Bishop, a PhD student in the Harvard-MIT Health Sciences and Technology program, along with Gage Hills, Tathagata Srimani, and Christian Lau.įor decades, improvements in silicon-based transistor manufacturing have brought down prices and increased energy efficiency in computing. Other MIT researchers on the study include lead author Mindy D. “But it’s an important litmus test for emerging technologies.” ![]() ![]() Shulaker, who has been designing CNFETs since his PhD days, says the new study represents “a giant step forward, to make that leap into production-level facilities.”īridging the gap between lab and industry is something that researchers “don’t often get a chance to do,” he adds. The technique deposited carbon nanotubes edge to edge on the wafers, with 14,400 by 14,400 arrays CNFETs distributed across multiple wafers. The CNFETs were created in a commercial silicon manufacturing facility and a semiconductor foundry in the United States.Īfter analyzing the deposition technique used to make the CNFETs, Max Shulaker, an MIT assistant professor of electrical engineering and computer science, and his colleagues made some changes to speed up the fabrication process by more than 1,100 times compared to the conventional method, while also reducing the cost of production. In a study published June 1 in Nature Electronics, however, scientists show how CNFETs can be fabricated in large quantities on 200-millimeter wafers that are the industry standard in computer chip design. But until now, they’ve existed mostly in an “artisanal” space, crafted in small quantities in academic laboratories. Carbon nanotube transistors are a step closer to commercial reality, now that MIT researchers have demonstrated that the devices can be made swiftly in commercial facilities, with the same equipment used to manufacture the silicon-based transistors that are the backbone of today’s computing industry.Ĭarbon nanotube field-effect transistors or CNFETs are more energy-efficient than silicon field-effect transistors and could be used to build new types of three-dimensional microprocessors. ![]()
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