Paper
2 February 1988 Repeatability Estimate Of Interference Optical Filters Using Thin Films Process Modeling
R. Machorro
Author Affiliations +
Abstract
A real deposition of optical interference filters involves many, often interconnected parameters l, which may change from one run to the next; thus the performance of the resulting filters is, in general, non repeatable. We have developed a model for a thin film process2, using a Monte-Carlo technique that makes it possible to emulate the operator response to the optical monitor, the evaporation plant and the physical properties of materials as a function of the operating point during deposition, according to previous experimental data. Until now a visual estimation of the espectral response after several simulations is ussually done, providing a qualitative way to control some critical parameters. In this paper we show the correlation of the standard deviation of an evaluating factor of the performance of the filter. This quality factor and its uncertainty are convenient in estimating the reliability of certain experimental procedures in the real process, allowing the operator to control a given parameter which influences more dramatically the performance of the deposited filter. It is not simple to stablish a criterium for performance repeatability for an ideal filter with a single quality factor because, depending on the application, the spectral re-sponse requirements are different. We propose a general purpose criterium of repeatability as well as a discussion of the widely accepted definition of "ideal filter".
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
R. Machorro "Repeatability Estimate Of Interference Optical Filters Using Thin Films Process Modeling", Proc. SPIE 0821, Modeling of Optical Thin Films, (2 February 1988); https://doi.org/10.1117/12.941856
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KEYWORDS
Optical filters

Thin films

Optical properties

Refractive index

Computer simulations

Monte Carlo methods

Multilayers

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