Thin Film Growth Simulation Using Cellular Automata, State Space, and Neural Nets Methods

Simulation of thin film growth is an essential aspect of developing new materials engineered to specific properties and defining the processing sequence required to produce the film. Software available to simulate such growth requires high end computer performance, and the programs are designed for use by experts in thin film growth who are interested in studying the mechanisms of nucleation and growth. Identifying processing parameters and control parameters suited to producing films is not a focus of these computer programs. Thus, the first issue is reducing the computational burden in simulation. The second issue is ease of use and suitability of display of the simulation in a timely manner for the user. AvXm proposes to demonstrate that the NanoModeler system as a thin film simulation system is suitable for enhancing the design of engineered materials and for developing process sequences for manufacturing the films. Important aspects of the NanoModeler system are the visual display, simple user interface, substrate design capability, archiving capability of simulations, and reduction of computational complexity. The unique combination of methods we have created represents a new approach to simulation not available presently on desktop level computers.