Project Title

Simulation of Thin Film Growth during Magnetron Sputtering

Presentation Author(s) Information

Joel SaucedoFollow

Faculty Mentor(s) Name(s)

Hasita Mahabaduge

Abstract

Sputtering is a fabrication technique for semiconductors. Thin film growth during plasma vapor deposition is a stochastic process which can be modeled by probabilities and randomly generated energies. The goal of this project is to use Monte Carlo methods to simulate the growth of thin films during magnetron sputtering. The Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. Python programming language was used to simulate the motion of constituent atoms to form a thin film during magnetron sputtering by applying the Monte Carlo methods. A random integer was generated representing the energy that each incoming atom has. The binding of the desired atom to the substrate to form a thin film was decided by the amount of energy each incoming atom has. Using python, the time taken to form a thin film of a desired thickness, was estimated. The formation of island growth in thin films was observed during the simulations. It was also observed that increasing the energy barrier and the size of the substrate resulted in longer run times needed to complete a matrix.

This document is currently not available here.

Share

COinS
 

Simulation of Thin Film Growth during Magnetron Sputtering

Sputtering is a fabrication technique for semiconductors. Thin film growth during plasma vapor deposition is a stochastic process which can be modeled by probabilities and randomly generated energies. The goal of this project is to use Monte Carlo methods to simulate the growth of thin films during magnetron sputtering. The Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. Python programming language was used to simulate the motion of constituent atoms to form a thin film during magnetron sputtering by applying the Monte Carlo methods. A random integer was generated representing the energy that each incoming atom has. The binding of the desired atom to the substrate to form a thin film was decided by the amount of energy each incoming atom has. Using python, the time taken to form a thin film of a desired thickness, was estimated. The formation of island growth in thin films was observed during the simulations. It was also observed that increasing the energy barrier and the size of the substrate resulted in longer run times needed to complete a matrix.