Detection of cyanogen (NCCN) on Ga-, In-, and Tl-doped aluminium nitride (AlN) nanotube: insights from quantum chemical calculations

Obinna C. Ngana,Terkumbur E. Gber, Khairia Mohammed Al-Ahmary,Gideon E. Mathias,Aljawhara Almuqrin, Ruth O. Adelagun,Jamelah S. Al-Otaibi, Daniel C. Agurokpon,Innocent Benjamin,Adedapo S. Adeyinka,Hitler Louis

Journal of Nanoparticle Research(2024)

引用 0|浏览4
暂无评分
摘要
Cyanogen gas has been reported to be poisonous and poses a great threat to human life when been exposed to its high concentration. Hence, the need to develop sensor materials that have the potential of detecting cyanogen gas is aroused. In this work, using the density functional theory (DFT)-based HSE, M06-2X, PBE0, and ωB97X-D/6-311G + + (d, p) functionals, the adsorption behaviour of cyanogen gas (CNG) on aluminium nitride (ALN), gallium-doped aluminium nitride (Ga@ALN), indium-doped aluminium nitride (In@ALN), and thallium-doped aluminium nitride (Tl@ALN) nanotubes as a sensor material was investigated. The calculation revealed that cyanogen gas was weakly adsorbed in the complex CNG@TlAlN with adsorption energy (− 23.01 kcal/mol), while stronger adsorption were observed for CNG@AlN (− 23.71 kcal/mol), CNG@InAlN (− 23.63 kcal/mol), and CNG@GaAlN (− 23.52 kcal/mol) at PBE0 functional. The HOMO–LUMO analysis calculations revealed that the complex CNG@InAlN ( E g = 0.2993 eV) has the highest conductivity and sensitivity. QTAIM and NCI examination revealed that the hydrogen bonding demonstrated a significant role in the interaction between the cyanogen gas and all the nanotubes. And, that CNG@AlN (− 67.861 kcal/mol) and CNG@InAlN (− 66.767 kcal/mol) have higher binding energy than other complexes. Based on these theoretical findings, it can be concluded that CNG@AlN and CNG@InAlN nanotubes are promising sensor materials for detecting cyanogen gas. Graphical abstract
更多
查看译文
关键词
Aluminium nitride,Cyanogen gas,Sensor material,Nanotube,Density functional theory,Environmental and health effects
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