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May 29, 2026Langmuir0 citations

Applications, Progress, and Challenges of Surfactants in Chemical Mechanical Polishing for Copper Interconnects

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MWMengqi Wang牛牛新环JZJiakai Zhou

Key Points

  • The aim is to review the applications and challenges of surfactants in chemical-mechanical polishing for copper interconnects.
  • Summarizes classification, mechanisms, and recent progress of surfactants in CMP.
  • Highlights synergistic effects of compound systems in enhancing slurry stability.
  • Outlines future research prospects including environmentally sustainable surfactants and AI-assisted design.
  • Optimized surfactant design improves material removal rate and surface roughness.
  • Achieves nanometer-scale surface roughness while maintaining high MRR.
  • Identifies significant challenges such as dishing, erosion, and slurry instability.

Abstract

With the continuous advancement of integrated circuits (ICs), copper (Cu) interconnects require chemical-mechanical polishing (CMP) with high planarization accuracy, low defect density, and strict corrosion control. Surfactants are crucial components in Cu interconnect CMP slurries because they can regulate abrasive dispersion, modify interfacial interactions, enhance wettability, and form adsorption films that inhibit Cu corrosion. These functions directly affect the material removal rate (MRR) and surface roughness. However, Cu interconnect CMP still faces significant challenges, including dishing and erosion, slurry instability, and the balance between high MRR and surface quality. Recent studies indicate that optimized surfactant molecular design and synergistic compound systems can regulate interfacial reactions and improve slurry stability, achieving nanometer-scale surface roughness while maintaining a high MRR. This review summarizes the classification, mechanisms, and recent progress of surfactants in Cu interconnect CMP, highlights the synergistic effects of compound systems and outlines future research prospects, including the development of environmentally sustainable surfactants, multiscale quantum chemistry and molecular dynamics simulations, and data-driven artificial intelligence (AI)-assisted design.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/6a192cd5fab5b468c4415a64https://doi.org/10.1021/acs.langmuir.6c01478
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