Abstract
In this study, the effects of different precursor concentrations on the growth and characteristics properties of the zinc oxide (ZnO) nanorods (NRs) synthesized by using modified and conventional chemical bath deposition (CBD) methods were investigated. The morphologic, structural and optical properties of synthesized ZnO NRs with different precursor concentrations were studied using various characterization techniques. The experimental results show that the varying precursor concentration of the reactants has a remarkable and significant effect on the growth and characteristics properties of ZnO NRs. In addition, the characteristic properties of ZnO NRs grown using the modified method showed significantly improved and enhanced properties. The average length of grown ZnO NRs increased with increased precursor concentration; it can be seen that longer ZnO NRs have been investigated using the modified CBD methods. The ZnO NRs synthesized at 0.05 M using the modified method were grown with high aspect ratios than the ZnO NRs grown using conventional means which were 25 and 11, respectively. The growth rate increased with increased precursor concentration; it can be observed that a higher growth rate was seen using the modification CBD method. Furthermore, XRD results for the two cases reveal that the grown ZnO samples were a nanorod-like in shape and possessed a hexagonal wurtzite structure with high crystal quality. No other phases from the impurity were observed. The diffraction peaks along (002) plane became higher, sharper and narrower as precursor concentration increased, suggesting that the crystalline quality of ZnO NRs grown using the modified method was more enhanced and better than conventional methods. However, optical studies show that the transmittance at each concentration was more than two times higher than the transmittance using the modified CBD method. In addition, optical studies demonstrated that the ZnO NRs grown by using modified and conventional methods had a direct Eg in the range of (3.2–3.26) eV and (3.15–3.19) eV, respectively. It was demonstrated in two methods that ZnO NRs grown at a precursor concentration 0.05 M gave the most favorable result, since the NRs had best characteristic properties.
Highlights
Zinc oxide (ZnO) is one of the versatile n-type and technologically significant semiconducting material due to its unique properties such as; wide direct energy band gap (3.37 eV), Crystals 2020, 10, 386; doi:10.3390/cryst10050386 www.mdpi.com/journal/crystalsCrystals 2020, 10, 386 transparency in the visible range, plenty in nature, non-toxic, high-electrochemical stability and resistivity control over range 10−3 to 105 Ω cm [1]
From the morphologic graphs of zinc oxide (ZnO) NRs, two different preparation methods are shown in Figures 2a–d and 2e–h concerning the influence of several precursor concentrations on the surface morphology
The experimental results of the two growth chemical bath deposition (CBD) methods demonstrate that the precursor concentration has significant and remarkable effect on the synthesis of ZnO NRs
Summary
Zinc oxide (ZnO) is one of the versatile n-type and technologically significant semiconducting material due to its unique properties such as; wide direct energy band gap (3.37 eV), Crystals 2020, 10, 386; doi:10.3390/cryst10050386 www.mdpi.com/journal/crystalsCrystals 2020, 10, 386 transparency in the visible range, plenty in nature, non-toxic, high-electrochemical stability and resistivity control over range 10−3 to 105 Ω cm [1]. ZnO has wide exciton-binding energy (60 meV), high mechanical stability, high chemical stability, thermal stability, biocompatibility, excellent optical and electrical properties and [2] These properties make the ZnO material useful for many optoelectronic devices such as ultraviolet light sensors, gas sensors, dye-sensitized solar cells, transparent conducting layers, photocatalysts, blocking layer in flexible organic solar cell, light-emitting devices and thin-film transistors [3,4,5,6,7]. Simultaneous improvement of these growth parameters toward achieving NRs arrays with in-demand properties is a formidable task
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