English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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.

Solubility Prediction of Organic Ionic Compounds with Computational Methods for Photoresist Application