A machine-learning framework for interpretable prediction of cellulose degree of polymerization retention in green solvents

Key Points

• The study aims to predict the degree of polymerization retention of cellulose when dissolved in green solvents using a machine-learning approach.
• Developed a machine-learning framework for prediction.
• Analyzed the dissolution and degradation behavior of cellulose in various green solvents.
• Interpreted the machine-learning model to enhance understanding of cellulose properties.
• The machine-learning model effectively predicted cellulose retention during dissolution in green solvents.
• Findings indicate significant variation in retention linked to solvent type and conditions.