On the surface area per volumetric loading: Its pronounced improvement in densely-packed SWCNT by double-function purification

MICROPOROUS AND MESOPOROUS MATERIALS(2024)

引用 0|浏览2
暂无评分
摘要
Volumetric loading is often a critical parameter in process design rather than weight. In this work, we have assessed the volumetric textural parameters of purified single-walled carbon nanotube materials (SWCNT). Purification is a necessary step in the SWCNT manufacturing process as they contain a metal residue inherent to their synthesis. Nitric acid treatment was applied for both metal removal and carbon structural/textural modification. Results show that the volumetric BET area is enhanced in ca. 500% with respect to the non-purified SWCNT (ca. 160% per mass), where both volumetric microporosity and external surfaces are enhanced. For such optimal material, the SWCNT structure remains well-defined though changes are observed (densification, more interstitial space, cutting of the tubes and amorphous carbon being formed). Three intrinsic factors contribute to the volumetric BET's enhancement: the bulk density and the mass-based surface parameters; microporous and external surfaces. The bulk density is enhanced due to a structural densification, thus more carbon is available per volume despite heavier metals (Ni, Y) being removed. One indirect factor, the MOx-removal effect, affects both intrinsic surface parameters. After studying this effect in depth, it was found that the microporosity is truly and largely enhanced due to newly-formed interstitial space. The external surface area is slightly improved but to a much lesser extent than microporosity. Overall, the factors dominating the volumetric BET for our system and applied experimental conditions are the bulk density, microporosity and MOx- removal effect. Concerning the conventional mass-based BET, microporosity and MOx-removal effect are the dominating factors. The study also reveals that mes-oporosity control in these materials is possible, in comparison to previous studies.
更多
查看译文
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