Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Chinese Optics Letters
  • Vol. 12,
  • Issue 5,
  • pp. 053101-
  • (2014)

Optimization of thickness uniformity of coatings on spherical substrates using shadow masks in a planetary rotation system

Not Accessible

Your library or personal account may give you access

Abstract

A model is developed to improve thickness uniformity of coatings on spherical substrates rapidly and automatically using fixed shadow masks in a planetary rotation system. The coating thickness is accurately represented by a function composed of basic thickness, self-shadow effect, and shadow mask function. A type of mask with parabolic contours is proposed, and the thickness uniformity of coatings on spherical substrates can be improved in a large range of ratios of clear aperture (CA) to radius of curvature (RoC) by optimizing shadow masks using a numerical optimization algorithm. Theoretically, the thickness uniformity improves to more than 97.5% of CA/RoC from -1.9 to 1.9. Experimentally, the thickness uniformities of coatings on a convex spherical substrate (CA/RoC = 1.53) and on a concave spherical substrate (CA/RoC=-1.65) improve to be better than 98.5% after corrected by the shadow masks.

© 2014 Chinese Optics Letters

PDF Article
More Like This
Theoretical design of shadowing masks for uniform coatings on spherical substrates in planetary rotation systems

Cunding Liu, Mingdong Kong, Chun Guo, Weidong Gao, and Bincheng Li
Opt. Express 20(21) 23790-23797 (2012)

Optimization of thickness uniformity of optical coatings on a conical substrate in a planetary rotation system

Chun Guo, Mingdong Kong, Cunding Liu, and Bincheng Li
Appl. Opt. 52(4) B26-B32 (2013)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.