石墨烯掺杂和气体吸附对石墨烯等离子体共振和吸附物红外吸收峰位置的影响

Jongpil Ye
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摘要

石墨烯等离子体共振的峰位可控制为与气体分子红外吸收光谱的峰位重叠,从而实现石墨烯纳米带的高灵敏度检测和识别。在本研究中,我们利用密度泛函理论和有限差分时域法研究了 SO2、SO3、H2S 和 NH3 等气体分子在石墨烯上的吸附情况,并描述了其对两个峰相对位置的影响。结果表明,与其他情况相比,吸附在正掺杂石墨烯上的 SO2 和 SO3 的结合能更强,电荷转移量更大。正掺杂石墨烯上的 SO2 和 SO3 吸附物对电子的接受会使石墨烯等离子共振峰及其拉伸和摆动红外吸收峰发生重移。然而,前者的红移幅度更大,导致正掺杂石墨烯的峰位匹配带宽度比对掺杂石墨烯更窄。与 SO2 和 SO3 相比,无论掺杂类型如何,NH3 和 H2S 的电荷转移量都相对较小,从而减轻了掺杂类型的依赖性。与 p 掺杂石墨烯相比,NH3 在 n 掺杂石墨烯上的摇摆峰进一步蓝移,使得它们的峰位匹配带宽度更加接近。这些结果表明,要优化基于石墨烯等离子体的气体传感和识别性能,应考虑掺杂和吸附对这两种峰值的影响。
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Effects of graphene doping and gas adsorption on the peak positions of graphene plasmon resonance and adsorbate infrared absorption
The peak positions of graphene plasmon resonance can be controlled to overlap with those of the infrared absorption spectra of gas molecules, allowing highly sensitive detection and identification by graphene nanoribbons. In this study, we investigate the adsorption of gas molecules, including SO2, SO3, H2S, and NH3, on graphene and characterize its effects on the relative positions of the two peaks using density functional theory and the finite difference time domain method. It is demonstrated that the binding energies are stronger, and the amounts of charge transfer are greater in the case of SO2 and SO3 adsorbed on n-doped graphene than in other cases. Electron acceptance by SO2 and SO3 adsorbates on n-doped graphene redshifts the graphene plasmon resonance peaks and their stretching and wagging infrared absorption peaks. However, the former is significantly further redshifted, leading to narrower peak-position-matching ribbon widths in n-doped graphene than in p-doped graphene. The amounts of charge transfer are relatively small regardless of the doping type in the case of NH3 and H2S, mitigating the doping-type dependence compared to SO2 and SO3. The wagging peaks of NH3 on n-doped graphene are shown to be further blueshifted than on p-doped graphene, rendering their peak-position-matching ribbon widths further closer to each other. These results suggest that the effects of doping and adsorption on the two types of peaks should be considered to optimize the performance of graphene plasmon-based gas sensing and identification.
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