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With the persistent advancement of semiconductor technology, the demand for high-efficiency device manufacturing processes has surged. Chemical Mechanical Planarization (CMP) is a cornerstone for achieving angstrom-scale surface uniformity crucial for integrated circuits (IC) and logic devices. Shallow Trench Isolation (STI) CMP involves the selective removal of bulk oxide to electrically isolate active components on wafer surfaces. The modulation of the Ce 3+ to Ce 4+ surface state is essential for improved performance in both CMP and post-CMP (p-CMP) applications. Ce 3+ is ideal for oxide material polishing due to its strong adherence to oxide surfaces, while Ce 4+ is optimal for p-CMP cleaning, given its weak bond to oxide surfaces. Current p-CMP industry-standard methods utilize mechanical approaches, such as polyvinyl alcohol (PVA) brush scrubbing. However, this process induces high levels of shear force (SF), leading to secondary defects on the wafer surface (i.e. scratches, corrosion, increased surface roughness). To address these limitations, non-contact cleaning methods utilizing megasonic energy have emerged, which rely on generating reactive oxygen species (ROS) to induce particle removal. Thus, this study focuses on enhancing ceria particle removal during post-CMP cleaning by employing amine-based chemistries coupled with megasonic energy. While preliminary results imply that the mechanical cavitations induced by megasonic waves improve cleaning efficiency, this method will be optimized via the introduction of amine-based chemistries. Specifically, this work aims to leverage the unique properties of amines coupled with megasonic energy to facilitate enhanced ceria removal through electron donation, inducing a reduction in the oxidation state of ceria from Ce³⁺ to Ce⁴⁺. This approach improves particle removal while limiting secondary defects, enhancing redox activity induced by megasonic waves and chemical interactions. The mechanisms behind this method will be validated with CeO 2 oxidation state kinetics, interfacial frictional changes, wafer surface roughness analysis, and SEM validation of particle removal efficiency.
McDonnell et al. (Fri,) studied this question.