DENSITY FUNCTIONAL THEORY BASED INVESTIGATIONS OF NANOMATERIALS FOR THE DETECTION OF TOXIC GASES

Abstract

Air pollution caused by the release of hazardous toxic gases such as C₂H₄, CH₄, CO₂, CO, and H₂ during thermal runaway in lithium-ion batteries, along with industrial emissions like COCl₂ and CNCl, poses a significant threat to human health and environmental safety. The effective detection and monitoring of these gases require the development of highly sensitive, selective, and reliable gas sensing technologies capable of real-time operation. In this work, a comprehensive investigation of chemoresistive gas sensors is presented, with a particular focus on two-dimensional (2D) materials as promising candidates for next-generation sensing applications. These materials exhibit unique advantages, including a high surface-to-volume ratio, tunable electronic properties, and abundant active sites, which enhance gas adsorption and sensing performance.The study begins with an overview of the fundamental working principles of chemoresistive gas sensors, which rely on gas adsorption, charge transfer, and modulation of electrical conductivity in n-type and p-type semiconductors. Various 2D materials, including graphene, transition metal dichalcogenides, g-C₃N₄, MXenes, and hexagonal boron nitride (hBN), are systematically analysed in terms of their sensing mechanisms, advantages, and limitations. Strategies such as elemental doping, surface functionalization, and substrate engineering are highlighted as effective approaches to improve sensitivity, selectivity, and response dynamics. To gain atomistic insights into gas–surface interactions, Density Functional Theory (DFT) is employed as the primary computational framework. The theoretical foundation of DFT, based on the Hohenberg–Kohn theorems and the Kohn–Sham formalism, enables accurate modelling of many-electron systems using electron density as the central variable. The role of exchange–correlation functionals and their limitations, particularly in predicting band gaps, are also discussed, establishing the basis for first-principles calculations carried out in this work. Subsequently, DFT-based investigations are conducted to study the adsorption behaviour of toxic gases on pristine and Cu-modified hBN systems. For COCl₂ detection, pristine hBN exhibits weak physisorption with low adsorption energy and poor recovery characteristics. However, Cu incorporation through substitutional doping and surface adsorption significantly enhances gas interaction, leading to chemisorption and improved sensing performance. Electronic structure analyses, including Density of States (DOS), Hirshfeld charge, charge density difference, Electron Localization 7 Function (ELF), and Reduced Density Gradient (RDG), confirm strong charge transfer, band gap reduction, and enhanced conductivity. Similarly, for CNCl gas, Cu decoration improves adsorption strength and induces notable changes in electronic properties, including a significant work function variation of 31.54%, indicating high sensor sensitivity. Furthermore, the adsorption of lithium-ion battery thermal runaway gases (C₂H₄, CO, CO₂, H₂, and CH₄) is investigated. While pristine hBN shows weak physisorption, Cu-doped hBN exhibits strong chemisorption, enhanced charge transfer, and significant band gap modulation, confirming its superior sensing performance. RDG analysis reveals the transition from weak van der Waals interactions in pristine systems to strong attractive interactions in Cu-doped configurations. Recovery time analysis further supports the practical applicability of these materials. In addition, the electronic properties of Cu-doped and Cu-adsorbed MoS₂ nanowires are examined. Substitutional doping is found to induce significant charge redistribution, improve electrical conductivity, and enhance electron emission characteristics, as evidenced by work function variation and Bader charge analysis. These results demonstrate the effectiveness of doping in tailoring material properties for sensing and nanoelectronics applications. Overall, we conclude from our present research work that Cu-functionalized 2D materials, particularly hBN and MoS₂-based systems, as highly promising candidates for efficient, low-cost, and high performance gas sensors. The integration of DFT-based insights with material engineering strategies provides a robust pathway for the design of advanced sensing devices aimed at environmental monitoring, industrial safety, and early detection of hazardous gases, contributing to improved public health and sustainable development.