Efficient production of activated carbon with well-developed pore structure based on fast pyrolysis-physical activation

Journal of the Energy Institute(2024)

引用 0|浏览5
暂无评分
摘要
As the most commonly used method for industrial activated carbon preparation, physical activation is usually accompanied by significant loss of raw materials, especially when the pore structure of activated carbon is well developed. This not only reduces yields, but also increases costs. To enhance both yield and pore structure of activated carbon, we proposed a facile and scalable method called "fast pyrolysis-physical activation". After fast pyrolysis, although the initial pore volume of the semi-coke decreases, the rapid release of volatiles promotes the increase of mesopore and macropore volumes and the development of micron-scale cracks, which is beneficial for CO2 mass transfer and reduces diffusion resistance. Therefore, compared to slow pyrolysis, the activated carbon produced through this method has a higher pore volume (increased by 25.9%∼30.0%) and a larger SBET (increased by 26.7%∼38.3%), while the yield remains almost unchanged. Consequently, due to the increase in pore volume and high yield of the activated carbon, the CO2 adsorption capacity (25 °C, 1 bar) of ACB-K700 increases from 2.02 mmol/g to 2.37 mmol/g compared to ACB-M700, and the total CO2 adsorption capacity of activated carbon prepared from the same mass of raw coal (1 g) increases from 1.07 mmol to 1.16 mmol. Due to the pre-formed pores inside the semi-coke, the gas activator molecules are able to penetrate deep into the particles, which not only reduces the ineffective etching that occurs on the surface, but also promotes the development of pore structure. In conclusion, this study provides a new pore development model for physical activation, and also provides a new method to produce activated carbon rapidly and massively, while the pore structure is well developed.
更多
查看译文
关键词
Coal-based activated carbon,Fast pyrolysis,Physical activation,Pore structure,Carbon yield
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要