A novel method combining Monte Carlo–FEM simulations and experiments for simultaneous evaluation of the ultrathin film mass density and Young׳s modulus. (January 2016)

• Record Type: Journal Article
• Authors: Zapoměl, J.; Stachiv, I.; Ferfecki, P.
• Is Part Of: Mechanical systems and signal processing. Volume 66/67(2016)
• Page Start: 223
• Page End: 231
• Publication Date: 2016-01
• Subjects: Film measurement -- Film material parameters -- Finite element method -- Monte Carlo probabilistic method -- Resonance frequency -- Computational simulations; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2015.06.022
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: In this paper, a novel procedure of simultaneous measurement of the ultrathin film volumetric density and the Young׳s modulus utilizing the Monte Carlo probabilistic method combined with the finite-element method (FEM) and the experiments carried out on the suspended micro-/nanomechanical resonator with a deposited thin film under different but controllable axial prestresses is proposed and analyzed. Since the procedure requires detection of only two bending fundamental resonant frequencies of a beam under different axial prestress forces, the impacts of noise and damping on accuracy of the results are minimized and thus it essentially improves its reliability. Then the volumetric mass density and the Young׳s modulus of thin film are evaluated by means of the FEM based computational simulations and the accuracies of the determined values are estimated utilizing the Monte Carlo probabilistic method which has been incorporated into the computational procedure. Highlights: Simultaneous measurement of two material constants of a thin film. Detection of only the lowest resonant frequencies having the highest accuracy. Changing the detected frequencies by axial force that is not a material parameter. Determination of accuracy by consideration of all principle measurement errors. Utilizing a stochastic approach (as in nature) to the accuracy evaluation.