Accurate and Interpretable Prediction of CO₂ Solubility in Physical Absorbents Based on Sequential Models

Methanol-based physical absorption processes for industrial decarbonization usually require harsh low-temperature conditions, highlighting the need for screening efficient absorbents under mild conditions. Machine learning has accelerated solvent screening; however, challenges in prediction accuracy