Abstract

Ellipsometry is widely used to characterize the thickness and optical parameters of thin films deposited, for example, in industrial processes. It is based on the measurement of polarization change upon reflection of, for example, visible light at a material sample. Commercially available devices are designed for stationary applications and often rely on precise geometric adjustment of the optical setup to maximize the measurement precision. In this work, a simplified spectral ellipsometer is proposed and tested with the aim of flexible implementation in space-limited applications in thermonuclear fusion research: on the one hand, as a hand-held device for large thickness scans of coatings deposited on first-wall components inside the vacuum vessel of fusion experiments and, on the other hand, for in situ monitoring of plasma deposited coatings on diagnostic vacuum windows, reducing their transmission in the optical spectral range, which hampers spectroscopic diagnostics in long-pulse plasma experiments. The simplicity of the hardware setup is partially compensated by complex Bayesian inference of the coating parameters, which incorporates all uncertainties of the measurement and the model and provides a quantitative assessment of the final uncertainties of inferred coating parameters. The Bayesian inference based on synthetic observations is also used to optimize the diagnostic design, identifying the limiting parameters and quantifying their impact on final accuracy. For real-time analysis of layer thickness on first-wall components in fusion devices measured with the hand-held device, a neural network based analysis has been implemented, and promising test results are presented.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.