Skip to main content
eScholarship
Open Access Publications from the University of California

Nanotechnology Applications in Self-Assembly and DNA Computing

  • Author(s): Akin, Hayri Engin
  • Advisor(s): Ozkan, Mihrimah
  • et al.
Abstract

Nanotechnology spans and merges very diverse areas from device physics to molecular self-assembly, from development of new materials with nanoscale dimensions to manipulating existing materials on atomic scale. DNA nanotechnology is the field of nanotechnology that uses the unique structure and properties of DNA as a structural material or computational medium. DNA nanotechnology has various applications but mostly is used in DNA computing and molecular self-assembly. In this dissertation these two areas are investigated. Under DNA-based nanofabrication, construction of functional materials as building blocks for nanoelectronics and optimal DNA sequence design for assembly are researched. Conjugation of carbon nanotubes as well as end-to-end assembly of nanowires with DNA is demonstrated, electrical measurements are investigated, and the process is carried on an electronic microarray platform. This electronic microarray platform is adopted to perform DNA computing, which is the biggest accomplishment of this dissertation. The information present in an image is encoded through various DNA strands and decoded on a CMOS-enabled platform to recreate the original image. Satisfiability problems were solved via 2 different methods. It is notable that the proposed approach eliminated the need for PCR and enzymes, resulting in a decreased error rates and cost. Overall, this technique shows significant advantages over previous experimental techniques such as short operating time, reusable surface and simple experimental steps. Finally, microelectronics and molecular biology techniques are integrated for showing the feasibility of Hopfield neural network using DNA molecules. Six-dimensional Hopfield associative memory storing various memories is demonstrated as an archetype neural network using DNA. The results are read on an electronic microarray platform, which opens the semiconductor processing knowledge for fast and accurate hybridization rates. The research undertaken under the umbrella of this dissertation is expected to have broad implications for next-generation functional materials such as nanoscale building blocks. The proposed surface-based DNA computation approach will bring the hybrid concept of silicon-compatible DNA computing to realization. Integration of a CMOS platform and DNA for a completely non-biological purpose has the potential to greatly affect the future applications.

Main Content
Current View