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Nouvelle méthodologie hybride pour la mesure de rugosités sub-nanométriques

Abstract : Roughness at Sub-nanometric scale determination becomes a critical issue, especially for patterns with critical dimensions below 10nm. Currently, there is no metrology technique able to provide a result with high precision and accuracy. A way, based on hybrid metrology, is currently explored and dedicated to dimensional measurements. This hybrid metrology uses data fusion algorithms in order to address data coming from different tools. This thesis presents some improvements on line roughness analysis thanks to frequency decomposition and associated model. The current techniques used for roughness determination are explained and a new one SAXS (Small Angle X-rays Scattering) is used to push again limits of extraction of roughness. This technique has a high potential to determine sub nanometrics patterns. Moreover, the design and manufacturing of reference line roughness samples is made, following the state of art with periodic roughness, but also more complex roughness determined by a statistical model usually used for measurement. Finally, this work focus on hybridization methods and more especially on neural network utilization. Thus, the establishment of a neural network is detailed through the multitude of parameters which must be set. In addition, training of the neural network on simulation leads to the capability to generate different metrology.
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Submitted on : Friday, May 15, 2020 - 10:35:47 AM
Last modification on : Monday, October 26, 2020 - 11:03:34 AM


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  • HAL Id : tel-02520554, version 2



Jérôme Reche. Nouvelle méthodologie hybride pour la mesure de rugosités sub-nanométriques. Micro et nanotechnologies/Microélectronique. Université Grenoble Alpes, 2019. Français. ⟨NNT : 2019GREAT050⟩. ⟨tel-02520554v2⟩



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