Solubility prediction of organic ionic compounds with computational methods for photoresist application

1Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.

Abstract

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 ΔGAB○, ΔGA○ and ΔGB○ 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.

Cite

CITATION STYLE

APA

Ryu, E. H., Kim, M. Y., Yoon, Y. J., Im, K. H., Jeong, H. M., Jeon, H., … Kim, H. (2016). Solubility prediction of organic ionic compounds with computational methods for photoresist application. Journal of Photopolymer Science and Technology, 29(5), 731–736. https://doi.org/10.2494/photopolymer.29.731

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free