Structures, Circuits and Architectures for Molecular Scale Integrated Sensing and Computing

Abstract

Nanoscale devices offer the technological advances to enable a new era in computing. Device sizes at the molecular-scale have the potential to expand the domain of conventional computer systems to reach into environments and application domains that are otherwise impractical, such as single-cell sensing or micro-environmental monitoring.New potential application domains, like biological scale computing, require processing elements that can function inside nanoscale volumes (e.g. single biological cells) and are thus subject to extreme size and resource constraints. In this thesis we address these critical new domain challenges through a synergistic approach that matches manufacturing techniques, circuit technology, and architectural design with application requirements. We explore and vertically integrate these three fronts: a) assembly methods that can cost-effectively provide nanometer feature sizes, b) device technologies for molecular-scale computing and sensing, and c) architectural design techniques for nanoscale processors, with the goal of mapping a potential path toward achieving molecular-scale computing.We make four primary contributions in this thesis. First, we develop and experimentally demonstrate a scalable, cost-effective DNA self-assembly-based fabrication technique for molecular circuits. Second, we propose and evaluate Resonance Energy Transfer (RET) logic, a novel nanoscale technology for computing based on single-molecule optical devices. Third, we design and experimentally demonstrate selective sensing of several biomolecules using RET-logic elements. Fourth, we explore the architectural implications of integrating computation and molecular sensors to form nanoscale sensor processors (nSP), nanoscale-sized systems that can sense, process, store and communicate molecular information. Through the use of self-assembly manufacturing, RET molecular logic, and novel architectural techniques, the smallest nSP design is about the size of the largest known virus.