Structure-property relationships in lignin-based porous carbon materials for water purification

Water pollution is a global challenge and requires sustainable countermeasures.

A promising approach is to develop biobased porous materials as filters to adsorb the hazardous components in the wastewater.

Lignin, a main component in plants, has a high carbon content and thus serves as an ideal source to produce carbon materials for efficient water treatment.

However, the diverse botanical origin of lignin leads to a series of fabrication challenges for the desired structures and raises the difficulty of tuning the properties.

Such an elusive structure-property relationship of lignin-based porous carbon materials ought to be clarified to guide the development of better absorption materials.

In this project, we propose to integrate advanced in situ characterization at synchrotron radiation facilities and machine learning-based data analysis strategies to investigate this topic, especially during water purification.

By using lignin from two raw resources of hardwood and softwood, the derived carbon materials will be fabricated into three formats: powder, fiber, and foam.

The diverse material forms and advanced characterization techniques will provide a large volume of structural data for machine learning to improve the structural modeling and quantitatively classify the structure-property relationship of lignin-based carbon materials. The results of the project will help both academia and industry to optimize their lignin-relevant research.