From nanoscale displacement sensing and estimation to nanoscale alignment

Abstract

In this article, the authors present theoretical background and practical procedures for linking displacement sensing and estimation to nanoscale alignment. The authors discuss the application of nanoscale displacement sensing and estimation (nDSE)-based overlay metrology tool. The authors propose a new look at what constitutes displacement and alignment. From there, the authors develop several frameworks to bridge these two concepts based on a set of new pseudodisplacement concepts and on the careful selection of references. Direct displacement-measurement-based alignment (DDMA) is the first method the authors have used to generate reliable alignment results. The authors achieved sub-100-nm (down to 21nm) alignment accuracy. Indirect displacement-measurement-based alignment (IDMA) is the most accurate method in theory. IDMA truly utilizes nDSE to achieve precision coplacement between different layers and processes. IDMA and DDMA, along with a group of other nDSE-based algorithms/procedures, are vibration tolerant, making them ideal as overlay alignment tools for nanoimprint lithography.

Subpixelic Measurement of Large 1D Displacements: Principle, Processing Algorithms, Performances and Software

“…Another approach is to oversample images, but this method increases the computing load dramatically. Authors like Douglas [ 3 ] and Gao et al [ 4 ] use a direct measurement in the frequency domain and, through combination with statistical methods, obtain respectively 3- ó precisions around 5 nm and 3 nm.…”

Twin-scale Vernier Micro-pattern for Visual Measurement of 1-D in-plane Absolute Displacements with Increased Range-to-Resolution Ratio

“…For example, this kind of method has been implemented by Moddemeijer (1991), reporting a resolution of 13.3 nm. Also, authors like Douglas (1993) and Gao et al (2006) have combined correlation with statistical methods. As a result, resolutions around the 10 nm and 1 nm, respectively, were achieved.…”

Digital Holography as Computer Vision Position Sensor with an Extended Range of Working Distances

“…Both feature-based and area-based methods have been used at the micro-scale but area-based methods are preferred because they are more accurate and more robust to noises [ 15 ]. Area-based methods like least squares can achieve nanometer resolutions using regular 20x microscopes [ 15 , 16 , 17 , 18 ]. Nevertheless, the measurement range is limited to the field of view, limiting computer vision position sensing of micro-objects to microscopy.…”