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Ion beam figuring of high-slope surfaces based on figure error compensation algorithm.
Dai, Yifan; Liao, Wenlin; Zhou, Lin; Chen, Shanyong; Xie, Xuhui.
Afiliação
  • Dai Y; National University of Defense Technology, DeYa Road, Changsha, Hunan, China 410073.
Appl Opt ; 49(34): 6630-6, 2010 Dec 01.
Article em En | MEDLINE | ID: mdl-21124541
In a deterministic figuring process, it is critical to guarantee high stability of the removal function as well as the accuracy of the dwell time solution, which directly influence the convergence of the figuring process. Hence, when figuring steep optics, the ion beam is required to keep a perpendicular incidence, and a five-axis figuring machine is typically utilized. In this paper, however, a method for high-precision figuring of high-slope optics is proposed with a linear three-axis machine, allowing for inclined beam incidence. First, the changing rule of the removal function and the normal removal rate with the incidence angle is analyzed according to the removal characteristics of ion beam figuring (IBF). Then, we propose to reduce the influence of varying removal function and projection distortion on the dwell time solution by means of figure error compensation. Consequently, the incident ion beam is allowed to keep parallel to the optical axis. Simulations and experiments are given to verify the removal analysis. Finally, a figuring experiment is conducted on a linear three-axis IBF machine, which proves the validity of the method for high-slope surfaces. It takes two iterations and about 9 min to successfully figure a fused silica sample, whose aperture is 21.3 mm and radius of curvature is 16 mm. The root-mean-square figure error of the convex surface is reduced from 13.13 to 5.86 nm.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Appl Opt Ano de publicação: 2010 Tipo de documento: Article País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Appl Opt Ano de publicação: 2010 Tipo de documento: Article País de publicação: Estados Unidos