Efficient circuit-level modelling of ballistic CNT using piecewise non-linear approximation of mobile charge density
Kazmierski, Tom, Zhou, Dafeng and Al-Hashimi, Bashir (2008) Efficient circuit-level modelling of ballistic CNT using piecewise non-linear approximation of mobile charge density. In, DATE08 , 146-151.
This paper presents a new carbon nanotube transistor (CNT) modelling technique which is based on an efficient numerical piece-wise non-linear approximation of the non-equilibrium mobile charge density. The technique facilitates the solution of the self-consistent voltage equation in a carbon nanotube such that the CNT drain-source current evaluation is accelerated by more than three orders of magnitude while maintaining high modelling accuracy. The model is currently limited to ballistic transport but can be extended to non-ballistic modes of transport when a suitable theory is developed while researchers study phenomena that sometimes prevent electrons in a carbon nanotube from going ballistic. Our results show that while the accuracy and speed of the proposed model vary with the number of piece-wise segments in the mobile charge approximation, it is possible to obtain a speed-up of more than 1000 times while maintaining the accuracy within less than 2% in terms of average RMS error compared with the state of the art theoretical reference CNT model implemented in FETToy. This numerical efficiency makes our model particularly suitable for implementation in circuit-level, eg. SPICE-like, simulators where large numbers of such devices may be used to build complex circuits.
|Item Type:||Conference or Workshop Item (Paper)|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Electronic & Software Systems
Faculty of Physical Sciences and Engineering > Electronics and Computer Science > EEE
|Date Deposited:||11 Dec 2007 09:45|
|Last Modified:||27 Mar 2014 20:09|
|Further Information:||Google Scholar|
|ISI Citation Count:||0|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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