The effect of chemical composition on the structure, chemistry and mechanical properties of magnetron sputtered W-B-C coatings: Modeling and experiments

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Authors

MIRZAEI Saeed ALISHAHI Mostafa SOUČEK Pavel ŽENÍŠEK Jaroslav HOLEC David KOUTNÁ Nikola BURŠÍKOVÁ Vilma STUPAVSKÁ Monika ZÁBRANSKÝ Lukáš BURMEISTER Frank BLUG Bernhard CZIGÁNY Zsolt BALÁZSI Katalin MIKŠOVÁ Romana VAŠINA Petr

Year of publication 2020
Type Article in Periodical
Magazine / Source Surface & coatings technology
MU Faculty or unit

Faculty of Science

Citation
web https://www.sciencedirect.com/science/article/pii/S0257897219312642
Doi http://dx.doi.org/10.1016/j.surfcoat.2019.125274
Keywords Magnetron sputtering; Mechanical properties; Fracture resistance; W-B-C; Ab initio
Description Ternary W-B-C coatings were non-reactively deposited in order to enhance the envelope of the mechanical properties of the binary transition metal borides and carbides with a focus on fracture resistance. The study investigated the influence of the atomic composition on the chemistry, microstructure, and mechanical properties of W-B-C coatings. The content of tungsten was found to be a key parameter influencing the energy flux delivered to the growing coating and therefore influencing the structure of the coating. Increased tungsten content led to a denser structure of the coating, but also to the amorphization of the microstructure. An increase in the WB bond fraction was observed as the tungsten content increased and correspondingly, the content of carbon decreased. Increasing the ratio of stronger boride bonds associated with stiff materials with high Young's modulus such as WB resulted in the enhanced mechanical properties of the coatings. A theoretical method for the comparison of experimentally derived bonding with ab initio simulations of randomly distributed amorphous materials was proposed. The method was applicable for amorphous coatings while the coatings with WC1-x nanocrystals exhibited the greatest discrepancies between the calculated and the experimentally derived bond fractions. This indicates that our proposed model is an appropriate tool for prediction of the bonding state of amorphous coatings.
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