Triphenylmethane-Derived Levelers for High-Speed Redistribution Layer Copper Electroplating of Tailored Surface Morphologies

Abstract

Redistribution Layer (RDL), composed of layered dielectrics and electroplated copper materials, is a basic structure to rearrange numerous I/O pads on the chip surface in wafer-level advanced packaging. As the key chemicals in electrolyte baths, electroplating additives have undergone continuous development to meet the industrial needs for high-speed and fine-line/fine-pitch applications. Meanwhile, the intricate relationships between additive chemical structures and electroplated copper properties are yet to be well understood. In this work, a pair of triphenylmethane-based dye molecules, i.e., gentian violet (GV) and methyl green (MG), was comparatively investigated as levelers for high-speed RDL copper electroplating. Compared to GV, significantly stronger electrochemical polarization and tunable deposit morphology can be achieved by MG with just one extra quaternized amine terminal. Combining quantum chemical computations, in situ spectroelectrochemical analyses, and microstructural characterization, it is found that MG possesses enhanced electrostatic adsorption, surface coverage and multi-additive synergies, enabling tailored copper trace morphology. This study elaborates the adsorption mechanism and screening criteria of triphenylmethane-derived levelers, and presents a candidate additive structure for high-speed copper electroplating.

Keywords

Redistribution layer / Copper electroplating leveler / Theoretical computation / In situ spectroelectrochemical analysis / Microstructural characterization

Acknowledgements

This work was financially supported by National Natural Science Foundation of China (Grant Nos. 62304143, 22425204, 22288102 and 22472143), Natural Science Foundation of Xiamen, China (Grant No. 20241302), and the autonomous deployment project of State Key Laboratory of Materials for Integrated Circuits (No. SKLJC-Z2024-C03).

Conflict of Interests

We wish to confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

Author Contributions

Zi-Hao Song: Methodology, Validation, Formal analysis, Investigation, Data curation, Writing- Original Draft. Wei-Bin Wang: Methodology, Validation, Formal analysis, Investigation, Data curation, Writing- Original Draft. Xiao-Hui Liu: Validation, Investigation, Formal analysis. Xiao-Min Han: Validation, Investigation, Formal analysis. Yi Zhou: Validation, Formal analysis. Rui Huang: Validation, Formal analysis. Yan-Xia Jiang: Validation, Formal analysis. Zhe Li: Conceptualization, Methodology, Formal analysis, Investigation, Writing- Original Draft, Writing- Review & Editing, Supervision, Project Administration, Funding acquisition. Xiao-Wei Liu: Methodology, Formal analysis, Supervision. Meiling Xiao: Methodology, Formal analysis, Investigation, Supervision. Hong-Gang Liao: Methodology, Formal analysis, Investigation, Supervision, Funding acquisition. Wei-Lin Xu: Project Administration, Funding acquisition. Rong Sun: Project Administration, Funding acquisition.

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding authors on reasonable request.

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