post-CMOS Devices Research Articles

Modeling Interconnects for Post-CMOS Devices and Comparison With Copper Interconnects

Power dissipation in charge-based technology is the biggest roadblock toward miniaturizing circuits. Quantum-mechanical tunneling and subthreshold leakage current will ultimately limit scaling of silicon field-effect transistors. To continue Moore's law scaling, it is imperative that devices working with a state variable other than electron charge are sought for. Examples of alternate state variables include electron spins, pseudo-spins in graphene, direct and indirect excitons, plasmons, and phonons. At the same time, interconnection aspects of devices utilizing novel state variables must be considered early on. This paper provides a framework to quantify energy dissipation in interconnects for novel state variables. Models for energy per bit are then used along with previously derived models for delay of interconnects for novel state variables to compare performance and energy dissipation of novel interconnects with complementary metal-oxide-semiconductor (CMOS) interconnects. Comparison results provide important insights into material, device, and circuit implications of post-CMOS technologies.

Graphene Process Integration for Post-CMOS Devices

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Probing quantum coherent states in bilayer graphene

An active area of post-CMOS device research is to study the possibility of realizing and exploiting exotic quantum states in nanostructures. In this paper we consider one such system, two layers of graphene separated by an oxide insulator. This system has been predicted to have an excitonic condensate that survives above room temperature. We describe a computational technique—path integral quantum Monte Carlo (PIMC)—that directly simulates many-body quantum phenomena, including excitonic condensation. Starting from a simplified quasiparticle model, the many-body PIMC simulations show excitonic pairing and a confirm a superfluid phase that persists above room temperature. We then present an atomistic PIMC model that captures more details of graphene than our quasiparticle model, and discuss how to extract parameters for a non-equilibrium Green’s function calculation.