Tamás Ungár

Prof. Tamás Ungár

Department of Materials Physics, Eötvös Loránd University Budapest, PO Box 32, H-1518 Budapest, Hungary
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orcid

Research Focus & Metrics

Academic Career Length

34Years (1993-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 1999 in Journal of Applied Crystallography
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Journal Article
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TUTamás Ungár
Tamás Ungár
IDI. Dragomir
I. Dragomir
ÁRÁ. Révész
Á. Révész
ABA. Borbély
A. Borbély

22 May 2001 in Journal of Applied Crystallography
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Journal Article
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TUTamás Ungár
Tamás Ungár
Jenő GubiczaJenő Gubicza
Jenő Gubicza
GRG. Ribárik
G. Ribárik
ABA. Borbély
A. Borbély

25 September 2001 in Journal of Applied Crystallography
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Journal Article
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GRG. Ribárik
G. Ribárik
TUTamás Ungár
Tamás Ungár
Jenő GubiczaJenő Gubicza
Jenő Gubicza

1 December 2005 in Powder Diffraction
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TUTamás Ungár
Tamás Ungár
GTG. Tichy
G. Tichy
Jenő GubiczaJenő Gubicza
Jenő Gubicza
RHR. J. Hellmig
R. J. Hellmig
Crystallite size determined by X-ray line profile analysis is often smaller than the grain or subgrain size obtained by transmission electron microscopy, especially when the material has been produced by plastic deformation. It is shown that besides differences in orientation between grains or subgrains, dipolar dislocation walls without differences in orientation also break down coherency of X-rays scattering. This means that the coherently scattering domain size provided by X-ray line profile analysis provides subgrain or cell size bounded by dislocation boundaries or dipolar walls.

18 September 2002 in Journal of Applied Crystallography
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IDI. C. Dragomir
I. C. Dragomir
TUTamás Ungár
Tamás Ungár

17 July 2020 in Crystals
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GRGábor Ribárik
Gábor Ribárik
BJBertalan Jóni
Bertalan Jóni
TUTamás Ungár
Tamás Ungár
The analysis of line broadening in X-ray and neutron diffraction patterns using profile functions constructed on the basis of well-established physical principles and TEM observations of lattice defects has proven to be a powerful tool for characterizing microstructures in crystalline materials. These principles are applied in the convolutional multiple-whole-profile (CMWP) procedure to determine dislocation densities, crystallite size, stacking fault and twin boundary densities, and intergranular strains. The different lattice defect contributions to line broadening are separated by considering the hkl dependence of strain anisotropy, planar defect broadening and peak shifts, and the defect dependent profile shapes. The Levenberg–Marquardt (LM) peak fitting procedure can be used successfully to determine crystal defect types and densities as long as the diffraction patterns are relatively simple. However, in more complicated cases like hexagonal materials or multiple-phase patterns, using the LM procedure alone may cause uncertainties. Here, we extended the CMWP procedure by including a Monte Carlo statistical method where the LM and a Monte Carlo algorithm were combined in an alternating manner. The updated CMWP procedure eliminated uncertainties and provided global optimized parameters of the microstructure in good correlation with electron microscopy methods.