4.6 Article

Structural Modelling of Silicon Carbide-Derived Nanoporous Carbon by Hybrid Reverse Monte Carlo Simulation

期刊

JOURNAL OF PHYSICAL CHEMISTRY C
卷 117, 期 27, 页码 14081-14094

出版社

AMER CHEMICAL SOC
DOI: 10.1021/jp403929r

关键词

-

资金

  1. Australian Research Council (ARC), under the Discovery Scheme
  2. Australian Government

向作者/读者索取更多资源

An atomistic model of the nanoparticle size Silicon Carbide Derived Carbon (SiC-CDC) is constructed using the Hybrid Reverse Monte Carlo HRMC) simulation technique through a two-step modeling procedure. Pore volume and three-membered ring t aints are utilized, in addition to the commonly used structure actor and energy constraints in the HRMC modeling to overcome the challenges arising from uncertainties involved for determining the structure. The final model is characterised for its important structural features including pore volume, surface area, pore size distribution, physical pore accessiblity, and structural defects. It is shown that the microporous structure of Sic-CDC 800 possesses a high pore volume and surface area, making it potentially a good candidate for gas adsorption applications. The HRMC model reveals the SiC-CDC 800 structure to be highly amorphous, largely comprising twisted graphene sheets. It is found that these distorted graphene-like carbon sheets comprising the carbon structure present a higher value for the solid-fluid potential strength compared to that of graphite, which is crucial in correct interpretation of experimental adsorption data. Furthermore, the constructed model is validated by comparing predictions of Ar, CO2 and CH4 adsorption against experimental data over a wide range of temperatures and pressures. It is demonstrated that our model is able to predict the experimental isotherms of different simple gases over various thermodynamic conditions with acceptable accuracy. The model also suggests the presence of ultramicroscopy that is accessible to CO2 but only partially accessible to CH4.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据