The use of diamonds to generate precision patterns and precision surfaces on a micrometer or nanometer scale has a history that dates back centuries. Uses of diamond in semi-automated machinery can be traced to ruling machines, pantographs, and ornamental turning with "diamond turning" dating back about a century. Poor behavior in machining more common materials (e.g. ferrous alloys) has limited diamond use in traditional industrial machining. The niche of the single crystal diamond is its edge sharpness and the ability to produce near-optical finish in materials such as aluminum, copper and their alloys; however, due to machine limitations, diamond machining remained a novelty until relatively recently. A convergence of machine technologies developed for both weapons and commercial applications led to modern diamond turning. Current turnkey machines can produce contoured surfaces with surface finish in the range of 5 nm R a and long range accuracy of micrometers or less. Macroscopic scale, three axis, diamond machining is a well-developed technology; machining of features on a micrometer and submicrometer scale is a new and rapidly developing application of single crystal diamond machining. The role of this technology in micro-optics replication has yet to be fully defined.

Line edge roughness (LER) has been identified as a potential source of uncertainty in optical scatterometry measurements. Characterizing the effect of LER on optical scatterometry signals is required to assess the uncertainty of the measurement. However, rigorous approaches to modeling the structures that are needed to simulate LER can be computationally expensive. In this work, we compare the effect of LER on scatterometry signals computed using an effective medium approximation (EMA) to those computed with realizations of rough interfaces. We find that for correlation lengths much less than the wavelength but greater than the rms roughness, an anisotropic EMA provides a satisfactory approximation in the cases studied.

No abstract

Micro-optic components and subsystems are becoming increasingly important in optical sensors, communications, data storage, and many other diverse applications. To adequately predict the performance of the final system, it is important to understand the element's effect on the wavefront as it propagates through the system. The wavefront can be measured using interferometric means, however, random and systematic errors contribute to the measurement. Self-calibration techniques exploit symmetries of the measurement or averaging techniques to separate the systematic errors of the instrument from the errors in the test lens. If the transmitted wavefront of a ball lens is measured in a number of random orientations and the measurements are averaged, the only remaining deviations from a perfect wavefront will be spherical aberration from the ball lens and the systematic errors of the interferometer. If the radius, aperture, and focal length of the ball lens are known, the spherical aberration can be calculated and subtracted, leaving only the systematic errors of the interferometer. We develop the theory behind the technique and illustrate the approach with a description of the calibration of a microinterferometer used to measure the transmitted wavefront error of micro-optics.

A combined Twyman–Green and Mach–Zehnder interferometer especially designed for the characterization of refractive microlenses is presented. This instrument allows for the quantitative characterization of the microlens form, the transmitted wavefront errors, the radius of curvature and the front focal length without removing the sample under test. All of these microlens properties are important when benchmarking different microlens fabrication technologies (Ottevaere et al 2006 J. Opt. A: Pure Appl. Opt. 8 S407–29). The interferometer was calibrated by the random ball test method. This paper describes the optical design and demonstrates the performance with the characterization of the instrument bias and measurements of a typical microlens. The performance is also compared with that of a semi-commercial instrument.

Line width roughness (LWR) has been identified as a potential source of uncertainty in scatterometry measurements, and characterizing its effect is required to improve the method's accuracy and to make measurements traceable. In this work, we extend previous work by using rigorous coupled wave (RCW) analysis on two-dimensionally periodic structures to examine the effects of LWR. We compare the results with simpler models relying upon a number of effective medium approximations. We find that the effective medium approximations yield an approximate order of magnitude indicator of the effect, but that the quantitative agreement may not be good enough to include in scatterometry models.

No abstract

No abstract