Layout optimization for multilayer overlay targets

L. A. Binns; N. P. Smith; C. P. Ausschnitt; J. Morningstar; W. Muth; J. Schneider; R. Yerdon

doi:10.1117/12.659060

14 March 2006 Layout optimization for multilayer overlay targets

L. A. Binns, N. P. Smith, C. P. Ausschnitt, J. Morningstar, W. Muth, J. Schneider, R. Yerdon

Proceedings Volume 6155, Data Analysis and Modeling for Process Control III; 61550F (2006) https://doi.org/10.1117/12.659060
Event: SPIE 31st International Symposium on Advanced Lithography, 2006, San Jose, California, United States

Abstract

A novel overlay target developed by IBM and Accent Optical Technologies, Blossom, allows simultaneous overlay measurements of multiple layers (currently, up to 28) with a single target. This is achieved by a rotationally symmetric arrangement of small (4 micron) targets in a 50 micron square area, described more fully in a separate paper. In this paper, we examine the lessons learned in developing and testing the Blossom design. We start by examining proximity effects; the spacing of adjacent targets means that both the precision-like Total Measurement Uncertainty (TMU) and accuracy of a measurement can be affected by proximity of features. We use a mixture of real and modelled data to illustrate this problem, and find that the layout of Blossom reduces the proximity-induced bias. However, we do find that in certain cases proximity effects can increase the TMU of a particular measurement. The solution is to ensure that parts of the target that interact detrimentally are maximally separated. We present a solution to this, viewing the problem as a constrained Travelling Salesman Problem. We have imposed some global constraints, for example printing front-end and back-end layers on separate targets, and consistency with the overlay measurement strategy. Initially, we assume that pairwise measurements are either critical or non-critical, and optimize the layout so that the critical layers are both not placed adjacent to any prior or intermediate-layer features. We then build upon this structure, to consider the effect of low-energy implants (that cannot be seen once processed) and site re-use possibilities. Beyond this, we also investigate the impact of more strategic optimizations, for example, tuning the number of features on each layer. In each case, we present on-product performance data achieved, and modelled data on some additional target variants / extreme cases.

Citation Download Citation

L. A. Binns, N. P. Smith, C. P. Ausschnitt, J. Morningstar, W. Muth, J. Schneider, and R. Yerdon "Layout optimization for multilayer overlay targets", Proc. SPIE 6155, Data Analysis and Modeling for Process Control III, 61550F (14 March 2006); https://doi.org/10.1117/12.659060

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