Prediction of CO2 solubility in multicomponent electrolyte solutions up to 709 bar: Analogical bridge between hydrophobic solvation and adsorption model

Pil Rip Jeon, Chang Ha Lee

Research output: Contribution to journalArticle

Abstract

Prediction of CO2 solubility in electrolyte solution is important for the design of various industrial processes using CO2. A large amount of experimental data is needed to predict the solubility accurately, as a consequence of the complex composition of electrolyte solution. 1384 experimental CO2 solubility data in various electrolyte solutions (containing mostly Na+, Ca2+, Mg2+, K+, SO4 2−, and Cl) from 30 references were used as training and validation data for developing a solubility model. According to the analogy between the hydrophobic solvation of CO2 and the adsorption phenomena, the novel solubility model with only four parameters (m0, α, k0, and k1) was developed to predict the CO2 solubility in solution with various ions. The model was correlated with the CO2 pressure and system temperature. The effect of dissolved electrolytes on the CO2 solubility was indicated by the concentration of electrostricted water molecule (ha) in the model, which was calculated using the concentration and hydration number of dissolved ions. The developed model with four parameters—obtained from experimental CO2 solubility data in water and single-salt solutions—reproduced the CO2 solubility well in complex electrolyte solutions, including the solutions after CO2–brine–rock reactions. Of the 1384 data, 94% were within a 95% prediction interval of the model. The model parameters can be used to estimate the heat of CO2 solvation, maximum CO2 solubility in water, and decay constant of the CO2 solubility with respect to the ha value. The developed model was further validated with single-salt solutions containing minor ions such as Li+ or Br.

Original languageEnglish
Article number123459
JournalChemical Engineering Journal
DOIs
Publication statusAccepted/In press - 2019 Jan 1

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Environmental Chemistry
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering

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