Investigation of the tribo-mechanical properties of sputtered a-C:Si films using design of experiments

Abstract

Adding silicon to sputtered amorphous carbon films is a promising approach to enhance tribo-mechanical properties. Although most works analyse the influence of one specific deposition parameter, the Design of Experiments is a more suitable method to investigate the cause-effect relation between the parameters on the properties of silicon-containing amorphous carbon (a-C:Si) films. In a sputtering process, the cathode power of the silicon target and the bias voltage were simultaneously varied from 217 to 783 W and −83 to −197 V, based on the Central Composite Design. The modification of the chemical composition was evaluated by means of glow-discharge optical emission spectroscopy. To analyse the influence of the silicon content and bias voltage on the tribo-mechanical properties, the hardness and elastic modulus were determined by nanoindentation, while the friction and wear behaviour were investigated in tribometer tests utilizing 100Cr6 counterparts.The silicon content increases linearly from 8.6 to 31.7 at.-% with an increasing cathode power without any impact of the bias voltage. However, an interaction between the two parameters is observed for the mechanical properties. At a high Si content and high bias voltage, the a-C:Si films show a high hardness of 22.0 ± 1.0 GPa and a high elastic modulus of 231.7 ± 10.6 GPa. In contrast, the lowest hardness of 18.1 ± 0.7 GPa and lowest elastic modulus of 203.2 ± 9.6 GPa are obtained at a low Si content and low bias voltage. The lowest coefficient of friction of 0.083 ± 0.029 as well as the lowest wear coefficients of 0.094 ± 0.025 × 10−5 mm3/N × m were obtained by a-C:Si films with a small amount of silicon. It was determined that the tribo-mechanical properties of a-C:Si films are interactively influenced by the silicon content and bias voltage. In this context, the Central Composite Design is an efficient method to obtain fundamental knowledge concerning the interrelation between these parameters.