Sulfur dioxide capture by deep eutectic solvents: Proposing purely predictive absorption models

Area of Science:

• Environmental Chemistry
• Green Chemistry
• Chemical Engineering

Background:

• Sulfur dioxide (SO2) emissions from industrial combustion contribute to acid rain and environmental damage.
• Deep Eutectic Solvents (DESs) are emerging green solvents with potential for SO2 capture.
• Experimental measurement of SO2 solubility in DESs is costly and time-consuming.

Purpose of the Study:

• To develop accurate and predictive thermodynamic models for SO2 absorption in DESs.
• To provide efficient tools for assessing DESs as SO2 absorbents.
• To support environmental regulations by facilitating SO2 emission control strategies.

Main Methods:

• Development of two group contribution (GC) and atomic contribution (AC) models.
• Utilized a comprehensive dataset of 997 SO2 absorption data points for 65 different DESs.
• Validated model performance across wide ranges of temperatures and pressures.

Main Results:

• Both developed GC and AC models demonstrated reliable and predictive performance.
• Achieved average absolute relative deviations (AARD%) of 10.3% for the GC model and 11.7% for the AC model.
• Established the first general predictive models for SO2 absorption in various DESs in the open literature.

Conclusions:

• The developed models provide accurate predictions of SO2 solubility in DESs.
• These models can significantly reduce the need for extensive experimental testing.
• The findings support the use of DESs for effective SO2 emission control in industrial processes.