SUNY Polytechnic Institute (SUNY Poly) announced today that Professor of Nanoscale Engineering Dr. Ji Ung Lee has been awarded $150,000 in funding from the SUNY Applied Materials Research Institute (SAMRI) to develop new stacking processes for increasing transistor density in computer chips. By using novel interconnect technology between different transistor layers, this stacked arrangement can serve as a more cost-effective alternative to shrinking transistors and potentially lead to faster, more power-efficient computer chips.
By Steve Ference
SAMRI is a strategic alliance between the State University of New York (SUNY) and Applied Materials, Inc. that serves as a nucleus of research and development activities on advanced materials, devices, manufacturing, and emerging areas of science and technology. SAMRI is a key component of Applied’s broader collaborations in New York, which include the Materials Engineering Technology Accelerator (META Center) at the Albany Nanotech Complex and a venture capital co-investment initiative with the State of New York.
“On behalf of SUNY Poly, I congratulate Dr. Lee for being selected to receive this award which could lead to next-generation computer chips that are both faster and less expensive to produce, and could help contribute to addressing the chip shortage in the future,” said SUNY Poly Acting President Dr. Tod A. Laursen. “Dr. Lee’s research is a testament to the caliber of this institute’s faculty, and it showcases how New York State and SUNY Poly’s collaborative high-tech initiatives can help meet the nation’s advanced computing needs.”
As part of this SAMRI award, a postdoctoral researcher is anticipated to be hired to support this work. They will use the advanced 300mm wafer line at the Albany Nanotech Complex, in partnership with New York Center for Research, Economic Advancement, Technology, Engineering and Science (NY CREATES), and introduce new materials, including two-dimensional semiconductors, to form the various transistor layers.
In addition, this project, which is eligible for up to an additional $450,000 in future funding, will aim to develop a new type of transistor to allow the development of more power-efficient machine learning hardware.
“I am proud to congratulate Dr. Lee on receiving this award, which will support his research that is highly relevant for addressing current computer chip challenges, including making them faster and more efficient at information processing and less costly to produce,” said Dr. Nathaniel Cady, SUNY Poly Interim Vice President of Research; Empire Innovation Professor of Nanobioscience; and Executive Director of SAMRI. “This is a great example of how the R&D synergies between academic expertise and the availability of state-of-the-art resources make SUNY Poly a world-class institute for research.”
“I am grateful to receive this funding from SAMRI. It will help SUNY Poly maintain its important research-focused role supporting the continuation of Moore’s Law without having to shrink transistors, which can lead to computer chips becoming faster and more affordable, while we also seek to enable more efficient AI-specific hardware,” said Dr. Lee. “I also look forward to working closely with Daniel Steinke of NY CREATES to develop these innovative processes using the 300mm wafer line that is available at the Albany Nanotech Complex.”
In 2019 SUNY Poly announced that Professor Lee was awarded $6.25 million in federal funding from the Naval Research Laboratory (NRL) to leverage the state-of-the-art 300mm fabrication facility, co-located with SUNY Poly’s Albany campus at the Albany Nanotech Complex, and use new nanoscale materials to fabricate advanced electronic devices in order to impart more functionality to future computer chips. As part of this five-year grant, Dr. Lee’s team is also developing artificial intelligence (AI)-specific hardware, which could lead to greater efficiency for AI applications, such as pattern and voice recognition. Notably, this grant represented SUNY Poly’s largest single investigator-faculty award to date.