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Abstrakty
The aim of this paper is to analyse high-resolution optical images of the surface layers of titanium oxide and copper oxide. The materials were produced using the PREVAC Modular Platform for layer deposition located at the University of Rzeszów. Images with a magnification of 50x were obtained using an optical microscope. On the basis of the results obtained, the quality of the layers was evaluated based on the image analysis. The quantitative method of analysis was applied, as a result of which the conditions of the manufacturing process for which the obtained layers had the highest homogeneity were indicated. The minimum range of grey shade counting was from 65 to 150 and the maximum range from 135 to 220. The standard deviation was from 8 to 40%.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
39--51
Opis fizyczny
Bibliogr. 9 poz., fot., rys., tab., wykr.
Twórcy
autor
- University of Rzeszów, Tadeusza Rejtana 16C, 35-959 Rzeszów
autor
- Department of Biophysics, Faculty of Mathematics and Natural Sciences, University of Rzeszów, 1 Pigonia Street, 35-317 Rzeszów, Poland
autor
- Department of Experimental Physics, Faculty of Mathematics and Natural Sciences, University of Rzeszów, Pigonia 1 Street, Rzeszów 35-317, Poland
autor
- Lodz University of Technology, Wólczańska 211/215, 90-924 Lodz
autor
- University of Rzeszów, Tadeusza Rejtana 16C, 35-959 Rzeszów
Bibliografia
- 1. https://www.dcode.fr/image-histogram [access:18.05.2018].
- 2. Scuderi V., Amiard G., Sanz R., Boninelli S., Impellizzeri G., Privitera V.: TiO2 coated CuO nanowire array: Ultrathin p-n heterojunction to modulate cationic/anionic dye photo-degradation in water,, Applied Surface Science” 416, p. 885-890, 2017.
- 3. Rokhmat M., Wibowo E., Sutisna, Khairurrijal, Abdullah M.: Performance Improvement of Ti02/Cu0 Solar Cell by Growing Copper Particle Using Fix Current Electroplating Method, Procedia Engineering” 170, p. 72-77, 2017.
- 4. Boissenin M., Wedekind J., Selvan A. N, Amavasai B. P., Caparrelli F., Travis J. R: Computer vision methods for optical microscopes „Image and Vision Computig” 25, p. 1107-1116, 2007.
- 5. Pires L. F, Borges F. S., Passoni S., Pereira A. B.: Soil Pore Characterization Using Free Software and a Portable Optical Microscope „Pedosphere” 23, p. 503-510, 2013.
- 6. Delbem I. D., Galéry R., Brandão P. R. G., PeresA. E. C.: Semi-automated iron ore characterisation based on optical microscope analysis: Quartz/resin classification, „Minerals Engineering” 82, p. 2-13, 2015.
- 7. Kottler V., Essaidi N., Ronarch N., Chappert C., Chen Y.: Dichroic imaging of magnetic domains with a scanning near-field optical microscope „Journal of Magnetism and Magnetic Materials” 165, p. 398-400, 1997.
- 8. Sekatskii S. K., Mironov B. N, Lapshin D. A, Dietler G., Let V. S.: Analysis of fiber probes of scanning near-field optical microscope by field emission microscopy, „Ultramicroscopy” 89, p. 83-87, 2001.
- 9. Wieclawek W.: Information granules in image histogram analysis „Computerized Medical Imaging and Graphics” 65, p. 129-141, 2018.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b998400e-473a-48ee-96ff-6bcba885ca8e