HE Qiongqiong, LI Xinyuan, MIAO Zhenyong, HAN Chao, WANG Guoqiang, XU Yuan, ZHANG Mingliang. Structure control of activated coke from low-rank coal and evaluation of adsorption characteristics of organic pollutants based on machine learning[J]. Journal of China Coal Society, 2021, 46(S2): 1077-1087.
Citation: HE Qiongqiong, LI Xinyuan, MIAO Zhenyong, HAN Chao, WANG Guoqiang, XU Yuan, ZHANG Mingliang. Structure control of activated coke from low-rank coal and evaluation of adsorption characteristics of organic pollutants based on machine learning[J]. Journal of China Coal Society, 2021, 46(S2): 1077-1087.

Structure control of activated coke from low-rank coal and evaluation of adsorption characteristics of organic pollutants based on machine learning

  • In the adsorption process of organic pollutants on hierarchical pore adsorbents,the microporous structure largely determines the specific surface area of the adsorbent and provides adsorption sites for adsorbates. Mesopores and macropores can provide mass transfer channels and adsorption space for adsorbates,so the optimized configuration of the micropore⁃mesopore⁃macropore hierarchical pore structure is very important to improve the adsorption effect of the adsorbent. A series of low⁃rank active cokes were prepared from Wanli long⁃flame coal(WL)and Zhaotong lignite(ZT)as raw materials. The physicochemical structures of different active cokes were characterized by scanning electron microscopy(SEM),N2 adsorption and Fourier transform infrared spectroscopy(FTIR). The effect of carboni⁃ zation and activation of low⁃rank coal on its pore structure and chemical structure was systematically studied, and the multi⁃porous activated semi⁃coke was prepared and matched with the selected organic pollutants to achieve the best adsorption effect. Finally,machine learning methods are used to predict the adsorption effect of activated coke and analyze the importance of each factor. The results show that the pore structure of activated coke is fully developed. Ac⁃ tivated coke with the different levels of pore structure development shows some differences in adsorption performance to the organics with different molecular weights. The adsorption capacity of Wanli ( Zhaotong ) activa⁃ ted coke for four organic pollutants,i.e.,indole,acid red A,Congo red and direct light fast blue B2RL,can reach 117.11(135.80),104.24(138.56),239.44(313.94) and 214.86(183.74) mg/ g respectively. With the analysis of main factors based on machine learning,it can be seen that when the activated coke adsorbs small molecule pollu⁃ tants,the specific surface area and pore volume have a dominant effect on the adsorption capacity. When adsorbing large molecule pollutants,the pore volume and average pore size have a greater influence. Based on the molecular structure and size characteristics of the adsorbate,the structure matching of the adsorbent’s hierarchical pores and the adsorbate provides a new idea for the preparation of cheap adsorbents.
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