A particle scale micro-CT approach for 3D in-situ visualizing the Pb (II) adsorption in different crop residue-derived chars

[Display omitted] •A novel particle scale micro-CT 3D in-situ visualization method was developed.•K-means unsupervised machine learning CT image segmentation algorithm was developed.•CT thresholds for coconut shell, rice husk, and wheat straw derived chars were given.•Qualitative 3D in-situ Pb (II) adsorption profiles in char particles were visualized.•Normalized 3D in-situ Pb (II) content profiles in char particles were exhibited. It is crucial to develop a new characterization method to provide insight into the complex adsorption mechanism of crop residue-derived char. This study established a novel 3D in-situ visualization method for qualitative and semi-quantitative characterizing Pb (II) adsorption profiles in crop residue-derived char particles. First, coconut shell activated carbon, rice husk biochar, and wheat biochar after Pb (II) adsorption was used for X-ray micro-CT imaging. Then, the K-means clustering algorithm was developed for segmenting the volume image of samples, and the optimized segmentation thresholds for the 3 samples were 6000HU, 7000HU, and 1300HU, respectively. The rendered images for qualitative illustrating the adsorption profile of Pb (II) were presented. Finally, based on the derived quantitative formula, the Pb (II) distribution in the biochar particle was presented for the first time. This method provided a new perspective and methodology for analysis and simulations of the adsorption behavior of heavy metals onto chars.