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October 18, 2025Biomacromolecules

Predicting the Solubility of Lignin via Machine Learning

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Authors

CZChanghang ZhangCSChenxin SunXWXinyu Wu

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Overview

This analysis predicts solubility in various solvents using machine learning and GPC data, indicating structural influence on solubility.

Key Points

  • The machine learning model accurately predicts lignin solubility, with R2 values reaching 0.987.
  • Utilizing structural features and quantum chemical data enhances solubility predictions for lignins across solvents.
  • SHAP analysis reveals the importance of individual molecular features in understanding lignin's solubility characteristics.
  • Insights gained may aid in the selection of soluble green solvents and improve lignin's practical applications.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/68f3eb011cfc5ad53f2909b7https://doi.org/10.1021/acs.biomac.5c00874
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