Artificial-neural-network-assisted DUV scatterometry for OCD on HAR sub-micron structures

Abstract

A neural network-assisted spectral scatterometry method is presented to measure multi-dimensional critical dimensions (CDs) on high aspect ratio (HAR) structures with micron or submicron scales. With the rise of 3D integrated circuit packaging, there is a need for accurate characterization of HAR sub-micron structures. This method uses DUV scatterometry and a broadband light source from DUV to visible light to gather multi-channel reflection data. The inverse modeling method and artificial neural network model enable accurate measurement of multiple CDs of test structures. The results showed accurate measurement of deep trench critical dimensions with a nominal line width of 0.6 μm and aspect ratio up to 5:1, with accuracy within a few nanometers comparable to SEM results using the same sample.

Optical method for depth measurement of high aspect ratio 3D microstructure

“…Micrometer-scale high-aspect-ratio (HAR) structures are widely used in the fields of MEMS and three-dimensional integrated circuits (3D-IC) to improve lateral integration density, energy storage potency, and signal transmission efficiency. The depth of HAR structures is a key functional parameter that significantly impacts sensor performance [1][2][3]. In 2014, O. Fursenko, J. Bauer et al used the KLA-Tencor Spectra Fx 200 wafer metrology tool to measure the depth of HAR structures.…”