November 5, 2024
Jean-Pierre Leburton
G. Stillman Emeritus
Professor of Electrical and Computer Engineering
University of Illinois
Tuesday, November 12
3:30—4:30 PM Pacific Time
CSE AE 108
2D NANO-ELECTRONIC MATERIALS FOR BIO-SENSING AND BIG DATA
SUMMARY
The last two decades have experienced rapid technological developments in the search of cheap and high accuracy devices for fast bio-molecular identification. In the realm of DNA and protein sequencing, there has been an increasing interest in the use of nanopores in solid-state materials because of their distinct advantage over biological pores in terms of flexibility in pore design and mechanical strength. Two-dimensional (2D) solid state materials such as graphene and Molybdenum di-sulphide (MoS2) in particular have attracted attention because of their atomically thin layered structure and electrically active characteristics, predisposing them to offer single base resolution and simultaneously multiple modalities of detecting biomolecular translocation. 2D nanopore devices promise seamless integration with semiconductor electronics and are poised to revolutionize a variety of technologies such as genomics, point-of-care diagnostics and digital data storage to name a few. The past year has witnessed a flurry of activity to experimentally realize nanopore Field Effect Transistors (FETs) and understand the fundamental sensing mechanism in such devices. Currently, the dominant consensus from theoretical calculations has involved the electrostatic modulation of the FET current due to the translocating biomolecules. In this talk, we review and provide insights into this sensing principle by modeling the electron flow through
2D material nanopore FETs. We describe a method to systematically characterize nanopores FETs by contrasting the changes in the FET behavior before-and-after nanopore drilling and DNA translocation. We outline measurable predictions of high-resolution FET based sensing of DNA-protein complexes and damaged DNA. We compare these FET signals to the corresponding ionic current signals calculated from all-atom Molecular dynamics simulations. Further, we also outline possible techniques to improve the detection SNR by augmenting pore and device design with statistical signal processing algorithms. Finally,
we propose a scalable device design of nanopore FETs to detect and identify translocations of single-biomolecules in a massively parallel scheme.