Solubility prediction of organic ionic compounds in both aqueous and organic solvents is important for understanding and optimizing lithographic performances. In this study, we proposed computational methods to predict solubility of organic ionic compounds. To compare the predicted solubility with the experimental one, we applied a multiple linear regression model by changing a set of explanatory variables. We conclude that the variables of solvation free energies of cation-anion pair, cation and anion, which are �� �� ○ , �� � ○ and �� � ○ respectively, will be sufficient to describe the relationship between the predicted and experimental solubility values. We expect that the more accurate empirical model for quantitative prediction of solubility of organic ionic compounds by expanding these regression models and further optimizing the parameters based on larger set of experimental values will be reserved.

Organic ionic compounds, such as photo-acid generators (PAGs) and photo-decomposable quenchers (PDQs), are solvated in organic solvents. During this process, organic ionic comounds can be solvated only in an associated salt form or both in an associated salt form and a dissociated ionic form. In order to understand this behavior, we carried out (1) the binding energy calculation of photo-acid generator (see, Figure 1) in various solvents, (2) the Job plots with 1 H NMR spectroscopy for detecting the dissociated anions of organic ionic compounds by a bidentated hydrogen bonding, and (3) GCIB-SIMS analysis to monitor the distribution of cations and anions along the depth of coated photoresist layer. Based on the computational and experimental results, we propose that organic ionic compounds are solvated in both an associated salt form and a dissociated ionic form in equilibrium state resulting in ion exchange of cations and anions in mixed organic ionic compounds.