Atomic-Scale Chemical Mechanical Polishing: Advances and Challenges for the Post-Moore Era
Atomic-Scale Chemical Mechanical Polishing: Advances and Challenges for the Post-Moore Era
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摘要: Chemical mechanical polishing (CMP) has emerged as a critical technology for local and global surface planarization in integrated circuit (IC) manufacturing for decades. As device dimensions evolve from the submicron level toward the nanoscale and ultimately the atomic scale, CMP stands as a strategic cornerstone for transcending the physical limits of Moore’s law and underpins heterogeneous integration and functional expansion in the post-Moore era. CMP represents a highly complex, interdisciplinary system that integrates fluid mechanics, materials science, tribology, and interfacial chemistry. Its performance is governed by the synergistic optimization of polishing slurry, pads, conditioners, and process parameters. This review systematically summarizes recent advances in atomic-scale CMP across four dimensions: mechanisms, processes, consumables, and equipment. In terms of the atomic-scale removal mechanism, research progress has revealed the coupled roles of chemical-mechanical interactions in atomically precise material removal. On the process side, strategies for optimizing polishing, pad conditioning, and slurry distribution have been developed to enhance uniformity and controllability. Regarding consumables, the codesign of multicomponent slurries and interfacial regulation materials has improved removal selectivity and defect suppression. On the equipment front, fully integrated 12-inch CMP platforms and auxiliary external-field technologies have advanced the precision and efficiency of atomic-scale planarization. Looking ahead, atomic-scale CMP faces several pressing challenges: deciphering multiphysics-coupled removal mechanisms, balancing removal rate selectivity with near-zero damage requirements for emerging material systems, realizing intelligent control across multiple physical fields, and leveraging machine learning to integrate atomistic, molecular, and continuum simulations for process optimization. Collaborative breakthroughs in these areas are expected to overcome current bottlenecks, offering systematic support for the continuous evolution of semiconductor manufacturing in the post-Moore era.Abstract: Chemical mechanical polishing (CMP) has emerged as a critical technology for local and global surface planarization in integrated circuit (IC) manufacturing for decades. As device dimensions evolve from the submicron level toward the nanoscale and ultimately the atomic scale, CMP stands as a strategic cornerstone for transcending the physical limits of Moore’s law and underpins heterogeneous integration and functional expansion in the post-Moore era. CMP represents a highly complex, interdisciplinary system that integrates fluid mechanics, materials science, tribology, and interfacial chemistry. Its performance is governed by the synergistic optimization of polishing slurry, pads, conditioners, and process parameters. This review systematically summarizes recent advances in atomic-scale CMP across four dimensions: mechanisms, processes, consumables, and equipment. In terms of the atomic-scale removal mechanism, research progress has revealed the coupled roles of chemical-mechanical interactions in atomically precise material removal. On the process side, strategies for optimizing polishing, pad conditioning, and slurry distribution have been developed to enhance uniformity and controllability. Regarding consumables, the codesign of multicomponent slurries and interfacial regulation materials has improved removal selectivity and defect suppression. On the equipment front, fully integrated 12-inch CMP platforms and auxiliary external-field technologies have advanced the precision and efficiency of atomic-scale planarization. Looking ahead, atomic-scale CMP faces several pressing challenges: deciphering multiphysics-coupled removal mechanisms, balancing removal rate selectivity with near-zero damage requirements for emerging material systems, realizing intelligent control across multiple physical fields, and leveraging machine learning to integrate atomistic, molecular, and continuum simulations for process optimization. Collaborative breakthroughs in these areas are expected to overcome current bottlenecks, offering systematic support for the continuous evolution of semiconductor manufacturing in the post-Moore era.
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