Review on atomistic and quantum mechanical simulation approaches in chemical mechanical planarization

Abstract

Chemical mechanical planarization (CMP) faces critical challenges including non-uniform material removal, surface defect generation, and complex tribochemical interactions that limit process control at advanced semiconductor nodes. This review examines computational simulation approaches that address these challenges through atomistic and quantum mechanical methods. Significant progress has been achieved using Fukui function analysis for additive screening, density functional theory (DFT) for surface passivation mechanisms, and molecular dynamics (MD) simulations for CMP processes. These simulation approaches have generated quantitative insights into key CMP metrics: surface roughness reduction from ∼5 nm to sub-1 nm scales, material removal rates ranging from 100 to 1000 Å/min depending on slurry chemistry, and subsurface damage layer thickness characterization. Mechanistically, simulations reveal three primary pathways: chemical dissolution through surface oxidation, mechanical abrasion via particle-surface interactions, and synergistic tribochemical reactions combining both effects. DFT calculations elucidate electronic structure-property relationships governing selectivity between different materials, while MD simulations capture real-time surface evolution and particle dynamics. Reactive force field methods bridge quantum mechanical accuracy with classical simulation timescales, enabling comprehensive mechanistic understanding across multiple length scales. Future research directions include development of machine learning-accelerated simulations, integration of multiphysics models connecting molecular-scale phenomena to wafer-scale uniformity, and predictive frameworks for novel slurry chemistries. Enhanced computational methods targeting industrial-scale process optimization and real-time process control represent critical advancement opportunities for next-generation CMP technology development.