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Titlebook: Research on Chemical Mechanical Polishing Mechanism of Novel Diffusion Barrier Ru for Cu Interconnec; Jie Cheng Book 2018 Springer Nature

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31#
發(fā)表于 2025-3-26 22:30:51 | 只看該作者
32#
發(fā)表于 2025-3-27 03:22:56 | 只看該作者
Material Removal Mechanism of Cu in KIO4-Based Slurry,actor during Cu CMP in a KIO.-based slurry is the chemical-mechanical synergistic effect. A high MRR and ideal surface quality could be obtained when abrasion-enhanced corrosion and corrosion-enhanced abrasion effects are high and balanced. Therefore, the weak alkaline slurries are the ideal polishing slurry during the P3 stage of Cu polishing.
33#
發(fā)表于 2025-3-27 08:09:33 | 只看該作者
34#
發(fā)表于 2025-3-27 12:54:16 | 只看該作者
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發(fā)表于 2025-3-27 13:42:33 | 只看該作者
36#
發(fā)表于 2025-3-27 17:51:04 | 只看該作者
37#
發(fā)表于 2025-3-27 22:31:46 | 只看該作者
Jie Chengk, they are derived in a unified way using pseudo maximum li.Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too
38#
發(fā)表于 2025-3-28 03:38:46 | 只看該作者
Jie Chengk, they are derived in a unified way using pseudo maximum li.Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too
39#
發(fā)表于 2025-3-28 08:15:49 | 只看該作者
Jie Chengk, they are derived in a unified way using pseudo maximum li.Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too
40#
發(fā)表于 2025-3-28 11:16:04 | 只看該作者
Jie Chengk, they are derived in a unified way using pseudo maximum li.Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too
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