26 - 29 June 2023
Munich, Germany
Conference 12618 > Paper 12618-4
Paper 12618-4

AI-guided numerical-aperture-controlled scatterometry for measurement of deep HAR and thin-film structures with a large depth variation

On demand | Presented live 26 June 2023

Abstract

This research means to solve the challenges in measuring deep high-aspect-ratio (HAR) and thin-film structures in 3D integrated circuits. As the semiconductor industry reaches its physical limitations in device scaling, advanced technologies such as advanced lithography and packaging have become crucial in extending Moore's law. This has led to the use of denser nano-to-sub-micron structures in three-dimensional integrated circuits (3D-IC), resulting in smaller, more functional devices. However, measuring these complex and deep HAR and thin-film structures with a large depth range from a few nanometers to a few hundred micrometers using a single optical system is challenging. To address this need, this article presents an AI-guided scatterometry method using numerical aperture control to achieve a large measurement range. The system uses broadband light to generate multi-wavelength reflection responses from the samples. With the help of an electromagnetic simulation tool and an artificial neural network model, the depth resolution can be improved through inverse modeling. The results demonstrate the ability to measure a wide range of samples with depths ranging from nanometers to micrometers scale, including sub-micron HAR openings and ultra-thin films, as long as the measurement bias is controlled within acceptable limits.

Presenter

National Taiwan Univ. (Taiwan)
One of the team members from National Taiwan University, department of mechanical engineering, Precision Metrology Lab, OCD metrology research team led by professor Liang-Chia Chen.
Presenter/Author
National Taiwan Univ. (Taiwan)
Author
National Taiwan Univ. (Taiwan)
Author
National Taiwan Univ. (Taiwan)
Author
Yen-Hung Hung
National Taiwan Univ. (Taiwan)
Author
National Taiwan Univ. (Taiwan)