Optimization of plasma enhanced chemical vapor deposition process parameters for hardness improvement of diamond-like carbon coatings

Recently there has been a surge in the usage of metaheuristic algorithms to design materials with optimum performance. In this article, one such recently proposed metaheuristic algorithm called RPSOLC (Repulsive Particle Swarm Optimization with Local search and Chaotic perturbation) has been used to design diamond-like carbon (DLC) thin films having better hardness. Based on a Box-Behnken design, 15 independent experiments on DLC deposition are conducted in a PECVD (plasma-enhanced chemical vapor deposition) setup by varying the CH4-Argon flow rate, hydrogen flow rate and the deposition temperature. The nano-hardness of the DLCs are evaluated using nano-indention tests. The hardness is then expressed as the function of the three process parameters using a polynomial regression metamodel. Finally, the metamodel is optimized using RPSOLC and compared with optimal predictions of a traditional GA. It is seen that RPSOLC has faster convergence and is more reliable than the GA. In general, a high H2 flow rate along with low CH4-Ar flow rate and high temperature is found to be beneficial in improving the hardness.