Rapid detection of harmful airborne substances caused by daily activities and industrial activity is vital. In the current study, the applicability of s-triazine based g-CN nanosheet as a potential sensor for environmentally dangerous gases, NO, NO, NO, SO, SO, and SO, was investigated using the density functional theory and non-equilibrium Green's function (NEGF) method. Sulfur-containing gases exhibited stronger interactions with the surface. The obtained adsorption energies are in the range of −0.21 to −1.13 eV, which is associated with charge transfer in the range of −0.09 to −0.29 e. The molecules' overall structures are preserved during the adsorption process. The sensitivity of the surface to the adsorbed molecules was confirmed by analyzing the work function changes and calculating the transmission coefficients using the NEGF approach. All adsorbate species, except SO, have short recovery times of up to 3.9 s at room temperature, proving the efficiency of this surface as a viable sensor material. Furthermore, by analyzing the humidity impact, the g-CN ability as a sensor in more realistic conditions was also validated. The results indicate that the g-CN surface can be an excellent candidate for toxic gas detection with high selectivity and sensitivity.

中文翻译：

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基于均三嗪的 g-C3N4 表面对污染物气体的高敏感性

快速检测日常活动和工业活动引起的有害空气传播物质至关重要。在当前的研究中，使用密度泛函理论和非平衡格林理论研究了基于均三嗪的 g-CN 纳米片作为环境危险气体 NO、NO、NO、SO、SO 和 SO 的潜在传感器的适用性函数（NEGF）方法。含硫气体与表面表现出更强的相互作用。获得的吸附能在-0.21至-1.13 eV范围内，这与-0.09至-0.29 eV范围内的电荷转移相关。在吸附过程中分子的整体结构得以保留。通过分析功函数变化并使用 NEGF 方法计算传输系数，确认了表面对吸附分子的敏感性。除 SO 外，所有吸附物在室温下的恢复时间都较短，可达 3.9 秒，证明了该表面作为可行传感器材料的效率。此外，通过分析湿度影响，g-CN 作为传感器在更现实的条件下的能力也得到了验证。结果表明，g-CN表面可以成为具有高选择性和灵敏度的有毒气体检测的优秀候选者。