Barrier Slurry Innovation for Advanced Node

Cao, Christian; Song, Kerry; Yao, Ying Xue; Jing, Jianfen

doi:10.1149/06001.0573ecst

Cited by 2 publications

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“…22 Cao studied the MRR of TiN, NDC, and Cu and found an optimized slurry formulation that can meet the requirements of the new integration scheme. 16 The formulated slurry results in high MRR of TiN, very low MRR of NDC, and a tunable MRR of Cu.…”

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confidence: 96%

“…Different slurry chemistries result in different MRR of Cu and barrier materials. 12,[14][15][16][17][18][19][20][21] Xu investigated the effect of H 2 O 2 on MRR and found that the MRR of Cu increases till 10 ml of H 2 O 2 per liter of the slurry while it decreases if the concentration of H 2 O 2 is increased beyond 10 ml. 22 Cao studied the MRR of TiN, NDC, and Cu and found an optimized slurry formulation that can meet the requirements of the new integration scheme.…”

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confidence: 99%

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Model-Based Optimization of CMP Process Parameters for Uniform Material Removal Selectivity in Cu/Barrier Planarization

Akbar¹,

Ertunç²

2022

ECS J. Solid State Sci. Technol.

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Chemical mechanical planarization is a process of achieving planar surfaces in the semiconductor manufacturing industry. The planarization of a surface is achieved by material removal from the wafer surface. The material removal depends on material properties and the process input parameters. Several studies have investigated the role of slurry chemistry to achieve a certain material removal selectivity for different materials. Here we propose a methodology of achieving a planar patterned surface of Cu/Mn/MnN using a model-based optimization for mechanical process parameters including applied force, slurry solid concentration, and abrasive particle size. The methodology has been developed via optimization using a genetic algorithm. The proposed methodology suggests that a lower downforce is the key parameter to achieve the desired material removal selectivity and planarity. The first part of the study suggests a low material removal rate (MRR) to achieve a lower standard deviation in MRR. The second part investigates the standard deviation in the thickness removed in the average time needed to remove a known thickness of the materials under consideration. It has been found that the application of lower downforce can also minimize the standard deviation in the thickness removed and a planar patterned surface can be achieved.

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confidence: 96%