A comprehensive analytical capacitance model of a two dimensional nanodot array [cellular neural net application]

This paper introduces a new comprehensive analytical capacitance model for nanoscale architectures based on nanoscale metallic/semiconducting dots. The model takes into account a detailed charge interaction of the components and shows their implications on power and performance with reference to a nanoscale cellular neural network (CNN) without any loss of generality. Our proposed model, as opposed to a numerical simulator, provides an analytical technique to perform a quick but an accurate estimate of the functional capacitances and thereby evaluate some key performance parameters such as switching delay, power dissipation and energy-delay product of a CNN, or in general a nanodot based circuit. Moreover, this model can be used as a guideline to determine the boundary of transition from continuous charge to discrete charge regimes in nanodot based electronic implementations.