book chapter · 2018
Molecular Electronic Computing Architectures
James M. Tour, Dustin K. James
Cited by 0Abstract and details only
Abstract
This chapter discusses several general architectural approaches that researchers are considering to build computers based on molecular-scale electronics and the advances made in these several areas in the years 1998 to 2001. It focuses upon the progress made in measuring the electrical characteristics of molecular switches and in designing logic devices using molecular electronics components. Technology development and industrial competition have been driving the semiconductor industry to produce smaller, faster, and more powerful logic devices. Carbon nanotubes are known to exhibit either metallic or semiconductor properties. Avouris and coworkers at IBM have developed a method of engineering both multiwalled nanotubes and single-walled carbon nanotubes using electrical breakdown methods. Molecular electronics as a field of research is rapidly expanding with almost weekly announcements of new discoveries and breakthroughs. Many cycles of testing and feedback analysis must occur with a working nanocell before we know the programming of the nanocell is successful.
Cite this paper
Tour, J. M., & James, D. K. (2018). Molecular Electronic Computing Architectures. https://doi.org/10.1201/9781315221670-2
Tour, James M., and Dustin K. James. “Molecular Electronic Computing Architectures.” 2018, pp. 2–1, https://doi.org/10.1201/9781315221670-2.
Tour, James M., and Dustin K. James. 2018. “Molecular Electronic Computing Architectures.” https://doi.org/10.1201/9781315221670-2.
Tour, J.M. and James, D.K. (2018) ‘Molecular Electronic Computing Architectures’. Available at: https://doi.org/10.1201/9781315221670-2.
@incollection{tour2018molecular,
title = {{Molecular Electronic Computing Architectures}},
author = {Tour, James M. and James, Dustin K.},
pages = {2--1},
year = {2018},
doi = {10.1201/9781315221670-2}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
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