RESUMEN
Endogenous volatile organic compounds (VOCs) in human exhaled gases can reflect human health status and be used for clinical diagnosis and health monitoring. Acetone is the sign VOC gases of diabetes mellitus. In order to find a potential material for the detection of acetone in the application of the clinical diagnosis of diabetes mellitus. The adsorption properties, including adsorption energy, adsorption distance, charge transfer, density of states, electron localization function and electrons density difference, of acetone on BN monolayer doped with Ni were comprehensively investigated based on density functional theory. The results show that there could be chemisorption between acetone and Ni-BN monolayer and Ni-BN monolayer is probably suitable gas sensitive material for the detection of acetone in the application of diabetes mellitus monitoring and clinical diagnosis.
Asunto(s)
Acetona , Diabetes Mellitus , Humanos , Diabetes Mellitus/diagnóstico , Adsorción , Gases , Modelos TeóricosRESUMEN
Ex-service SF6 adsorbents in SF6 gas-insulated electric equipment contain many toxic substances. Inside, HF and H2S are two typical toxic gases. Based on the first principle, the interaction process between HF/H2S and α-Al2O3 (0001) surfaces was calculated using the density functional theory (DFT). The results showed that the adsorption of HF on α-Al2O3 (0001) is stronger than that of H2S. Under the five adsorption sites, the adsorption effect of HF-H and HF-F was similar. At O-2 site, the adsorption energy of H2S-H adsorption configuration is significantly higher than that of the other four sites. The density of states (DOS) indicated that new peaks appeared after adsorption. The DOS and partial density of states (PDOS) indicated that the adsorption of HF and H2S occurs via chemical adsorption. The DOS and PDOS shifted to the right when the S atom was approaching, proving that the system shifts to instability. Compared with the energy gap of α-Al2O3 (0001), HF and H2S adsorption systems decreased significantly. The energy gap of the HF adsorption system was 1.173 eV larger than that of the H2S system and the geometry was relatively stable, which is consistent with the DOS and PDOS adsorption calculation results. Thus, the adsorption of HF and H2S on α-Al2O3 (0001) surfaces was clearly different. The findings of this study may provide theoretical guidance for the adsorption of other gases or developing a new adsorbent.
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Endogenous volatile organic compounds (VOCs) can reflect human health status and be used for clinical diagnosis and health monitoring. Dimethylamine and ammonia are the signature VOC gases of nephropathy. In order to find a potential gas sensitivity material for the detection of both signature VOC gases of nephropathy, this paper investigated the adsorption properties of dimethylamine and ammonia on Al- and Ga-doped BN monolayers based on density functional theory. Through analyzing the adsorption energy, adsorption distance, charge transfer, density of states, and HOMO/LUMO, the results indicated that the adsorption effect of Al- and Ga-doped BN monolayers to dimethylamine and ammonia is probably good, and these nanomaterials have the potential to be applied for nephropathy monitoring and clinical diagnosis.
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HF, CS2, and COF2 are three important decomposition components of the SF6 gas insulation medium. In this paper, the gas sensitivity of Pt doped on (8, 0) single-walled carbon nanotube (SWCNT) to HF, CS2, and COF2 is investigated based on density functional theory. The binding energy, charge transfer, density of states, and frontier molecular orbital theory are discussed. It is found that all processes of HF, CS2, and COF2 adsorbed on Pt-SWCNT are exothermic. Pt-SWCNT donated 0.182 electrons to CS2 molecules during the interaction process but acts as an electron acceptor during adsorption of HF and COF2 on it. After comprehensive consideration of binding energy and charge transfer, the response of Pt- SWCNT to CS2 may be the best, and those to HF and COF2 are almost the same. In addition, after the adsorption of the three kinds of gases on Pt-SWCNT, the order of the conductivity of the Pt-SWCNT material is CS2 > COF2 ≈ HF via frontier molecular orbital theory analysis. The Pt-SWCNT material is probably more suitable as a gas sensor for the detection of CS2 in the application of gas-insulated equipment.
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In order to find promising sensor materials for HF, CS2, and COF2 detection to realize the online internal insulation defect diagnosis of a SF6 gas electrical device, the gas sensing property, binding energy, adsorption distance, charge transfer, and density of states distribution, of Pt-doped anatase TiO2 (101) surfaces on HF, CS2, and COF2 gas molecules was calculated and analyzed in this paper based on the density functional theory. The work suggested that the Pt-TiO2 surface has a nice gas sensing upon CS2 and COF2 because of the increase of the conductivity of the Pt-TiO2 surface and the suitable adsorption parameter after CS2 and COF2 adsorbing on it. However, this material is not suitable as a gas sensor for HF gas. All of the works provide theoretical adsorption information of Pt-TiO2 as a gas sensor material for HF, CS2, and COF2 detection.
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SF6 has been utilized widely as an electrical insulation medium because of its excellent arc extinguishing performance and insulation characteristics. In this paper, the adsorption property of two kinds of key SF6 carbon-containing decomposition components (CS2 and COF2) on nitrogen-doped anatase TiO2(101) (N-TiO2) surfaces was simulated and analyzed based on density functional theory. The results demonstrated that N-TiO2 shows good gas sensitivity toward CS2 with the increase of conductivity but is insensitive toward COF2. In addition, the gas-sensing property of CS2 on N-TiO2 is stronger than that of COF2. This work provides the theoretical information on such a gas-sensitive material for key SF6 carbon-containing decomposition components, supporting its utilization as a chemical sensor applied in condition monitoring and defect diagnosis in SF6 gas-insulated equipment based on decomposition component analysis.