Crystallite size and microstrain: XRD line broadening analysis of AgSiN thin films. Issue 6 (6th November 2018) - Mohamad Zaidi, Umi Zalilah; Bushroa, A.R.; Ghahnavyeh, Reza Rahbari; Mahmoodian, Reza
Abstract : Purpose: This paper aims to determine the crystallite size and microstrain values of AgSiN thin films using potential approach called approximation method. This method can be used as a replacement for other determination methods such as Williamson-Hall (W-H) plot and Warren-Averbach analysis. Design/methodology/approach: The monolayer AgSiN thin films on Ti6Al4V alloy were fabricated using magnetron sputtering technique. To evaluate the crystallite size and microstrain values, the thin films were deposited under different bias voltage (−75, −150 and −200 V). X-ray diffraction (XRD) broadening profile along with approximation method were used to determine the crystallite size and microstrain values. The reliability of the method was proved by comparing it with scanning electron microscopy graph and W-H plot method. The second parameters' microstrain obtained was used to project the residual stress present in the thin films. Further discussion on the thin films was done by relating the residual stress with the adhesion strength and the thickness of the films. Findings: XRD-approximation method results revealed that the crystallite size values obtained from the method were in a good agreement when it is compared with Scherer formula and W-H method. Meanwhile, the calculations for thin films corresponding residual stresses were correlated well with scratch adhesion critical loads with the lowest residual stress was noted for sample with lowest microstrain and has thickest thickness among the three samples. Practical implications: The fabricated thin films were intended to be used in antibacterial applications. Originality/value: Up to the knowledge from literature review, there are no reports on depositing AgSiN on Ti6Al4V alloy via magnetron sputtering to elucidate the crystallite size and microstrain properties using the approximation method.