Chemical mechanical planarization (CMP) of Ru barrier lines is expected to become a critical processing step in the fabrication of the new interconnect-structures. However, due to its noble metal characteristics, Ru induces galvanic corrosion in its adjacent Cu lines in the wet CMP environment, and resists chemical surface modifications that are necessary to support CMP. The present work reports a slurry formulation to address these challenges of Ru-CMP, and explores the considerations for residual Cu removal using the same slurry. This alkaline (pH = 10) slurry with colloidal silica abrasives uses sodium percarbonate as an oxidizer/complexing agent in the CMP of both Ru and Cu. L-ascorbic acid is employed as a surface modifier to regulate the material removal rates of CMP, and benzotriazole is used to control galvanic corrosion of the Ru-Cu couple. With this slurry, wafer polish rates of ∼10 and ∼80 nm min−1 are measured for Ru and Cu, respectively, resulting in defect-free processed samples. Electrochemical measurements of open circuit potentials, potentiodynamic polarization and impedance spectroscopy are performed to investigate the detailed surface reactions of Ru and Cu that facilitate material removal and control corrosion during the CMP of these metals.

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We investigated the thermophysical and electrochemical properties of eight model protic ionic liquids (PILs) primarily because of our interest in their proton conductivity and low volatility. The chemical structures of the cations (ammonium vs imidazolium) and anions (mesylate vs triflate) were found to strongly govern properties such as density, viscosity, ionic conductivity, thermal and electrochemical stability, and phase transition behaviors. Structure–property relations were analyzed on the basis of charge delocalization, cation π-stacking, van der Waals interactions of alkyl tails, and hydrogen bonding interactions between cations and anions. The diffusion coefficients of the free proton, the cation, and the anion were determined by using NMR spectroscopy, and were used to differentiate between the vehicular and Grotthuss mechanisms of diffusion of protons. A correlation, based on the Sutherland–Einstein equation, was developed to predict ionic conductivity by using the room temperature molar volume and the VFT equation for viscosity.

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