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Effect of EU doping on the optical properties of ZnO nanorods prepared by chemical bath deposition
Yatskiv, Roman ; Bašinová, Nikola ; Grym, Jan ; Vaniš, Jan
We report on the properties of Eu-doped ZnO nanorods prepared by chemical bath deposition from aqueous solutions in an autoclave. The autoclave enables to grow the nanorods above the boiling point of water. The nanorods were characterized by scanning electron microscopy, secondary ion mass spectroscopy, and low temperature photoluminescence spectroscopy. Under the UV light excitation, the nanorods show a strong blue emission at 450 nm, which is associated with the 4f(6)5d - 4f(4) transitions of Eu2+ ions. We discuss the mechanisms responsible for the blue luminescence. We further clarify how the growth parameters affect the morphology and the optical properties of the nanorods. Growth temperatures above the boiling point of water significantly influence the intensity ratio of the near band edge emission to the deep level emission and greatly enhance optical quality of the nanorods.
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The Effect of temperature treatment TiO2 nanoparticles on antibacterial properties
Bytesnikova, Z. ; Valeckova, V. ; Švec, P. ; Richtera, L. ; Šmerková, K. ; Vítek, Petr ; Adam, V.
The synthesis of TiO2 nanoparticles (NPs) under various temperature treatments was described and TiO2 NPs was subsequently tested as an antibacterial agent. Scanning electron microscopy (SEM), Raman spectroscopy, Dynamic light scattering (DLS) were used to confirm structure of TiO2 NPs and detect differences between individual batches treated with different temperature. Antibacterial properties were tested on Escherichia coli (E. coli). TiO2 NPs as photocatalyst was incubated with bacterial cells under ambient light. Changes in temperature treatment can affect diameter size and crystal structure of TiO2 NPs as well as its antibacterial properties.
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An appropriate method for assessing hydrogel pore sizes by cryo-sem
Adámková, Kateřina ; Trudicová, M. ; Hrubanová, Kamila ; Sedláček, P. ; Krzyžánek, Vladislav
The aim of our work was to examine and describe ultrastructure of the agarose hydrogel and any possible structural concentration dependencies, and to assess the distribution and size of pores of agarose hydrogel in dependence on its concentration. Four concentrations were prepared (0.5 %, 1.0 %, 2.0 % and 4.0 % of dry weight content) and cryo-SEM and turbidimetry methods were executed on wet (original) samples in order to image the ultrastructure and measure the pore sizes within. \nReasonable results were obtained for the wet samples as they were closer to their native state they are usually used for applications in. Cryo-SEM and turbidimetry provided comparable results of pore diameters and allowed to compare pore diameters dependant on the concentrations, moreover, it showed more detailed and realistic structure.
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Determination of thickness refinement using STEM detector segments
Skoupý, Radim ; Krzyžánek, Vladislav
Quantitative STEM imaging together with Monte Carlo simulations of electron scattering in solids can bring interesting results about properties of many thin samples. It is possible to determine thickness of a sample, to calculate mass of particles and measure mass per length/area. Appropriate calibration is one of the crucial parts of the method. Even a small error or inaccuracy in detector response to electron beam either blanked or full brings significant error into thickness determination. This problem can be overcome by parallel STEM imaging in more segments of the detector. Comparing more segments gives a possibility to use a signal from different segments for different thicknesses of a sample. Accuracy of individual parts of the detector depends on the captured signal quantity. It is desirable to use such a STEM detector segment that provides the greatest signal change to a unit of thickness. To demonstrate the usage, we used a sample of Latex nanospheres placed on thin carbon lacey film, diameter of the nanospheres was around 600 nm in order to compare the results from different detector segments. Thanks to the known thickness of the sample (calculated from its geometrical shape), it is possible to estimate the optimal acquisition settings and post processing steps with the known and the true state of the sample.
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