Electrochemical deposited (ECD) thick film copper on silicon substrate is one of the most challenging technological brick for semiconductor industry representing a relevant improvement from the state of art because of its excellent electrical and thermal conductivity compared with traditional compound such as aluminum. The main technological factor that makes challenging the industrial implementation of thick copper layer is the severe wafer warpage induced by Cu annealing process, which negatively impacts the wafer manufacturability. The aim of presented work is the understanding of warpage variation during annealing process of ECD thick (~20 µm) copper layer. Warpage has been experimental characterized at different temperature by means of Phase-Shift Moiré principle, according to different annealing profiles. A linear Finite Element Model (FEM) has been developed to predict the geometrically stress-curvature relation, comparing results with analytical models.

Analysis of Warpage Induced by Thick Copper Metal on Semiconductor Device

Calabretta M.
Primo
;
2021-01-01

Abstract

Electrochemical deposited (ECD) thick film copper on silicon substrate is one of the most challenging technological brick for semiconductor industry representing a relevant improvement from the state of art because of its excellent electrical and thermal conductivity compared with traditional compound such as aluminum. The main technological factor that makes challenging the industrial implementation of thick copper layer is the severe wafer warpage induced by Cu annealing process, which negatively impacts the wafer manufacturability. The aim of presented work is the understanding of warpage variation during annealing process of ECD thick (~20 µm) copper layer. Warpage has been experimental characterized at different temperature by means of Phase-Shift Moiré principle, according to different annealing profiles. A linear Finite Element Model (FEM) has been developed to predict the geometrically stress-curvature relation, comparing results with analytical models.
2021
9783030705657
9783030705664
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3347382
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