2022
DOI: 10.1007/s40145-022-0570-x
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Precise control of surface oxygen vacancies in ZnO nanoparticles for extremely high acetone sensing response

Abstract: ZnO has been studied intensely for chemical sensors due to its high sensitivity and fast response. Here, we present a simple approach to precisely control oxygen vacancy contents to provide significantly enhanced acetone sensing performance of commercial ZnO nanopowders. A combination of H2O2 treatment and thermal annealing produces optimal surface defects with oxygen vacancies on the ZnO nanoparticles (NPs). The highest response of ∼27,562 was achieved for 10 ppm acetone in 0.125 M H2O2 treated/annealed ZnO N… Show more

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Cited by 39 publications
(19 citation statements)
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“…Point defects prefer to segregate on the surface, which may contribute to the excellent physical and chemical properties of nanomaterials and/or film 21,45–47 . Such preference can be analyzed quantitatively for oxygen vacancy by calculating its segregation energy E seg using the following equation: Esegbadbreak=Efsurfacegoodbreak−Efbulk,$$\begin{equation}{E}_{{\mathrm{seg}}} = E_f^{{\mathrm{surface}}} - E_f^{{\mathrm{bulk}}},\end{equation}$$where, Efsurface$E_f^{{\mathrm{surface}}}$ and Efbulk$E_f^{{\mathrm{bulk}}}$ are the formation energies of V O on the surface and in the corresponding bulk, respectively.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Point defects prefer to segregate on the surface, which may contribute to the excellent physical and chemical properties of nanomaterials and/or film 21,45–47 . Such preference can be analyzed quantitatively for oxygen vacancy by calculating its segregation energy E seg using the following equation: Esegbadbreak=Efsurfacegoodbreak−Efbulk,$$\begin{equation}{E}_{{\mathrm{seg}}} = E_f^{{\mathrm{surface}}} - E_f^{{\mathrm{bulk}}},\end{equation}$$where, Efsurface$E_f^{{\mathrm{surface}}}$ and Efbulk$E_f^{{\mathrm{bulk}}}$ are the formation energies of V O on the surface and in the corresponding bulk, respectively.…”
Section: Resultsmentioning
confidence: 99%
“…32 In addition, when the radius of rare-earth ions decreases, the computed formation energies E f of V Point defects prefer to segregate on the surface, which may contribute to the excellent physical and chemical properties of nanomaterials and/or film. 21,[45][46][47] Such preference can be analyzed quantitatively for oxygen vacancy by calculating its segregation energy E seg using the following equation:…”
Section: Stability and Segregation Of The V O In (110) Surfacementioning
confidence: 99%
“…Where C (ppm) , ρ (g•ml −1 ), d, V x (μl), M (g•mol −1 ) and V (L) are the concentration of the target gas, the density of the liquid to be measured, the purity of the liquid, the volume of the test liquid, the molecular weight of the liquid, and the volume of the gas test chamber, respectively. For n-type semiconductors, for reducing gases, the gas sensing response of the sensor is defined as ΔR/R g , where ΔR = R a -R g [32], and When the gas-sensitive semiconductor sensor begins to come into contact with the detected gas, the element begins to respond and this is indicated by a change in resistance measured in the test system. It takes time from the beginning of the element's response to the detected gas until the resistance has changed to a steady state value, which is defined as the time it takes for the resistance to reach 90% of its steady state value [31].…”
Section: Fabrication and Performance Test Of Gas Sensormentioning
confidence: 99%
“…This obviously limits the further application of such sensors. At the same time, some toxic and harmful gases are harmful to our health even at low concentrations (Lee et al, 2022), so it is imperative to solve the reversibility problem of MoTe 2 gas sensors so that they can detect gases quickly, sensitively and selectively (Zheng et al, 2021). In recent years, technicians have explored various methods to improve the gas-sensing properties of MoTe 2 with fast adsorption/desorption kinetics, such as surface modification of the material, application of gate bias (Feng et al, 2017), have achieved ideal gas sensing performance, but these methods also face a choice between performance and cost.…”
Section: Introductionmentioning
confidence: 99%