Journal
BIORESOURCE TECHNOLOGY
Volume 344, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.biortech.2021.126269
Keywords
Micro-CT; Three-dimensional in-situ visualization; Biochar; Pb (II) adsorption; Unsupervised machine learning; Normalization
Funding
- program for the Agriculture Research System of China [CARS-36]
- Changjiang Scholars, and Innovative Research Team in University of Education Ministry of China [IRT_17R105]
- Innovative Research Team of Agriculture and Rural Affairs Ministry of China
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A novel 3D in-situ visualization method was established in this study to qualitatively and semi-quantitatively characterize Pb (II) adsorption profiles in crop residue-derived char particles. Utilizing X-ray micro-CT imaging and the K-means clustering algorithm, the distribution of Pb (II) adsorption in different char particles was demonstrated.
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.
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