生物炭
吸附
材料科学
弹丸
原位
背景减法
图像分割
生物系统
分割
算法
化学
化学工程
数学
计算机科学
复合材料
人工智能
像素
工程类
有机化学
热解
生物
作者
Kunlin Song,Haoxiang Xiong,Xin Zhao,Jieyu Wang,Zengling Yang,Lujia Han
标识
DOI:10.1016/j.biortech.2024.130440
摘要
The non-homogeneous structure and high-density ash composition of biochar matrix pose significant challenges in characterizing the dynamic changes of heavy metal adsorption onto biochar with micro-computed tomography (Micro-CT). A novel in-situ registration subtraction image segmentation method (IRS) was developed to enhance micro-CT characterization accuracy. The kinetics of Cu(II) adsorption onto pellet biochar derived from corn stalks were tested. Respectively, the IRS and traditional K-means algorithms were used for image segmentation to the in-situ three-dimensional (3D) visual characterization of the Cu(II) adsorption onto biochar. The results indicated that the IRS algorithm reduced interference from high-density biochar composition, and thus achieved more precise results (R2 = 0.95) than that of K-means (R2 = 0.72). The visualized dynamic migration of Cu(II) from surface adsorption to intraparticle diffusion reflexed the complex mechanism of heavy metal adsorption. The developed Micro-CT method with high generalizability has great potential for studying the process and mechanism of biochar heavy metal adsorption.
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