A DFT study for the detection of CH2O gas by using ZnONTs

Abstract

In the past few decades, the removal of organic solvents from different substances, especially through the use of nanostructured materials, has been crucial in various industries, including improvement of innovative and adaptable nano adsorbents. Computational approaches are widely recognized as powerful tools for searching molecular systems at atomic level and investigating the characteristics of their interactions. This study utilized the dispersion-corrected DFT approach to gain a detailed comprehension of how CH2O molecules interact with both Pd-doped and pristine ZnO nanotubes (ZnONTs) during the adsorption process. The aim was to achieve a comprehensive comprehension of the adsorption behavior. To accomplish this, an extensive examination of the active sites and optimized geometrical characteristics of interacting systems was conducted. To assess adsorption capacity of Pd-ZnO nanotube and pristine ZnO nanotube for CH2O, binding characteristics of the interacting species have been assessed. This evaluation included analyzing the interaction energy (Eint), charge transfer, electronic properties, and ELF analysis. Moreover, Pd-doping greatly enhances the adsorption strength of ZnONTs, thereby imparting them with superior capability for CH2O adsorption. The significant adsorption strength of CH2O by the sensor under consideration raises the prospect of utilizing these nanotubes as highly effective sensor materials for CH2O detection, which is a matter of great interest. The results of our study provide a foundation for designing innovative and energy-efficient nanosensors that can serve as cost-effective solutions for detecting contaminants in wastewater.