Rapid detection of impurity particles in etching solutions using electrospray-differential mobility analysis

Particle defects, caused by impurity particles presenting in the chemical solution used in the semiconductor processing, directly impact yield and quality in the semiconductor industry. Early detection and removal of these particles at the chemical supply stage, for example, the etching solution, are crucial. This study presents a new methodology, based on electrospray-differential mobility analysis (ES-DMA), for detecting and quantifying specific organic impurity particles in etching solutions, a highly challenging task with existing methods to date. The results demonstrate that co-solvent with moderate volatility (e.g., H₂O and dimethyl sulfoxide in this study) in the simulated etching solution can be effectively removed for subsequent analysis by generating fine, uniform droplets using electrospray ionization (ES). Using this approach, we successfully identified and quantified model organic impurity particles, including polyethylene glycol (PEG100K; hydrophilic and neutrally-charged) and bovine serum albumin (BSA; amphoteric). The technique achieved detection of ultrafine particles smaller than 10 nm, with a detection limit as low as 10 ppm, even in the presence of high-concentration nonvolatile solutes (e.g., 2 wt% citric acid, used as the representative etchant). These results demonstrate the capability of this ES-DMA method to isolate and analyze specific organic impurity types within complex chemical matrices. Overall, this approach shows strong potential for enhancing quality control in semiconductor manufacturing by enabling early-stage identification of trace-level organic contaminants, leading to better quality control in advanced manufacturing.