The Research Of Simulation Of Single Electron Devices And Their Application In The Cellular Neural Network

Nanotechnology is the high-tech and front edge technology in 21st century, and the main content of science development in nowadays. The development of nanotechnology has great effect on the other subjects,industries and the whole society. And the nanoelectronics is the most important component of the nanotechnology, it represents the development of the microelectronics and may become the foundation of the next generation electronic science and technology. Along with the development of the VLSI, the characteristic size of the electronic devices is getting much smaller, and down from micron scale to nanometer scale. When the system size become so small as the wavelength of electron, novel physical effects will emerge due to quantum mechanical nature. New challenge and opportunity for researching new devices will be brought from these new phenomena and new effects. Single-electron tunneling devices have been proposed as one promising candidate for future nanoelectronic integrated circuits. This paper investigated several nanodevices such as the Quantum dot Cellular Automata (QCA) and the Single Electron Transistor (SET), and studied the modeling of the QCA and SET, and their applications in the circuits of Cellular Neural Network(CNN).First, we made an intensive study of the two methods of the SET numerical simulation, Master equation method and Monte Carlo method. After comparing their advantage and disadvantage, we chose the Master equation method as the main method to build the SET equivalent model, and then we simulated this SET model by a classical circuit simulation packages based on SPICE. Also we studied the characters of the CNN,and made a CNN cell model by the SET SPICE model ,and then simulated the single CNN cell and a CCD cellular neural network which is made up of these CNN cell. In addition, we studied another single electron device-QCA, and built a CNN model by QCA cells, then simulated the CCD cellular neural network by the simulation software QCADesigner. The results of simulation proved that the implement of the CNN using single electron devices have good prospects, and it is suitable for the development of the integrate circuits towards low power dissipation and good frequency property.