Predicting photolithography performance in silico for a given materials combination is essential for developing better patterning processes. However, it is still an extremely daunting task because of the entangled chemistry with multiple reactions among many material components. Herein, we investigated the EUV-induced photochemical reaction mechanism of a model photoacid generator (PAG), triphenylsulfonium cation, using atomiC–Scale materials modeling to elucidate that the acid generation yield strongly depends on two main factors: the lowest unoccupied molecular orbital (LUMO) of PAG cation associated with the electron-trap efficiency ‘before C–S bond dissociation’ and the overall oxidation energy change of rearranged PAG associated with the proton-generation efficiency ‘after C–S bond dissociation’. Furthermore, by considering stepwise reactions accordingly, we developed a two-parameter-based prediction model predicting the exposure dose of the resist, which outperformed the traditional LUMO-based prediction model. Our model suggests that one should not focus only on the LUMO energies but also on the energy change during the rearrangement process of the activated triphenylsulfonium (TPS) species. We also believe that the model is well suited for computational materials screening and/or inverse design of novel PAG materials with high lithographic performances.

The ongoing miniaturization of semiconductor devices necessitates continuous advancements in lithographic processes, which are critical for high-precision circuit formation. To prevent substrate damage during the etching step, a spin-on hardmask (SOH) layer is often introduced between the photoresist (PR) and the substrate. However, residual metal ions in SOH solutions can adversely affect integrated circuit performance, underscoring the need for efficient and chemically compatible removal strategies. This study investigates the adsorption of metal ions (Al³⁺, Cr³⁺, Cu²⁺, Fe³⁺, Ni²⁺, and Ti⁴⁺) from SOH solutions using mesoporous silica materials—MCM-41 and SBA-15—functionalized with various groups (–OH, –NH₂, –SH, and –CH₃). Adsorption performance was evaluated under solvent-only, monomer-containing, and polymer-containing conditions. Among the tested materials, amine-functionalized mesoporous silica exhibited the highest adsorption efficiency, with SBA-15-NH₂ showing relatively effective and uniform performance in polymer-containing systems. Isotherm analysis supported a monolayer chemical adsorption mechanism, suggesting the significance of surface functional groups in the adsorption process. These findings demonstrate the potential of functionalized mesoporous silica as a promising candidate for trace metal ion removal in semiconductor manufacturing, offering enhanced yield and improved process reliability.