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Improving Devices at Nano-Computing Level

At the Virginia Nano-Computing Research Group, our focus is on understanding non-equilibrium properties of nano-scale material structures. Our work applies a combined understanding of fundamental physics , chemistry, material science, and device engineering to explore novel device concepts.

We also explore and utilize high performance computational resources including the use numerical algorithms to advance our understanding of nanoscale science and engineering. To address the challenges of extending today’s electronic devices to the next generation of devices, science can no longer work out of context to engineering, but rather both should work in tandem. The interdisciplinary nature of our approach is necessary to explain the science and push the engineering of future devices.

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Selected Publications

  • Strain effect on band structure of InAlAs digital alloyABS J. Zheng, Y. Tan, Y. Yuan, A. W. Ghosh and J. C. Campbell, Journal of Applied Physics , 125 (8) :082514 (2019).
  • Maximization of thermal conductance at interfaces via exponentially mass-graded interlayersABS Rouzbeh Rastgarkafshgarkolaei, Jingjie Zhang, Carlos A. Polanco, Nam Q. Le, Avik W. Ghosh, Pamela M. Norris, Nanoscale (accepted) (2019).
  • Graphene Transistor Based on Tunable Dirac-Fermion-OpticsABS Ke Wang, Mirza M. Elahi, Lei Wang, K. M. Masum Habib, Takashi Taniguchi, Kenji Watanabe, James Hone, Avik W. Ghosh, Gil-Ho Lee, Philip Kim, Proc. Nat. Acad. Sci. USA (in press) (2019).
  • Machine learning electron correlation in a disordered mediumABS Jianhua Ma, Puhan Zhang, Yaohua Tan, Avik W. Ghosh, and Gia-Wei Chern, Physical Review B , 99 (8) :085118 (2019).

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What do we work on?

Research in our group has the advantage of being both curiosity driven and needs driven. Industry is always looking for ways to design or utilize novel materials and devices for new applications. To that end, our research focuses on three aspects of nanoelectronic modeling and simulation:

1. Fundamental physics of current flow through nanosystems: Traditional CAD tools for electronic conduction are based on macroscopic concepts such as mobility and diffusion that do not apply at these length scales. Our methods include effects due to quantum interference right from the outset, along with inelastic scattering, ‘friction’ and heating due to vibrations and spins, strong non-equilibrium many-body effects, and time-dependent effects due to hysteretic switching, memory and noise.

2. Computational modeling: Here we develop the formal evolution equations into quantitative simulation tools. This includes semi-empirical as well as ‘first principles’ methods for capturing chemistry, bandstructure and transport, describing the nano-channels and contact surfaces atomistically. Special attention is aimed at multiscaling and embedding techniques to describe hetero-interfaces and surface states, as in hybrid molecule-silicon devices.

3. Device engineering: Here we combine the formal equations with numerical simulations to identify performance advantages and limitations of nanoscale devices, such as resonant tunneling diodes, switches, conductors, interconnects, transistors and electronic sensors made out of various materials such as molecules, nanotubes, nanowires, spintronic or magnetic elements and silicon quantum dots. Part of our current interests involve exploring hybrid devices operating on novel principles, such as gate-tunable scattering centers for characterization and detection, conformationally gated molecules for nano-relays, molecular redox centers and motors integrated on a silicon CMOS platform for memory and heat sinking.