Title of article :
Extraction of step-repulsion strengths from terrace width distributions: statistical and analytical considerations
Author/Authors :
Richards، نويسنده , , H.L. and Cohen، نويسنده , , S.D. and Einstein، نويسنده , , T.L. and Giesen، نويسنده , , M.، نويسنده ,
Issue Information :
هفته نامه با شماره پیاپی سال 2000
Pages :
16
From page :
59
To page :
74
Abstract :
Recently it has been recognized that the so-called generalized Wigner distribution may provide at least as good a description of terrace width distributions (TWDs) on vicinal surfaces as the standard Gaussian fit and is particularly applicable for weak repulsions between steps, where the latter fails. Subsequent applications to vicinal copper surfaces at various temperatures confirmed the serviceability of the new analysis procedure but raised some theoretical questions. Here we address these issues using analytical, numerical, and statistical methods. We propose an extension of the generalized Wigner distribution to a two-parameter fit that allows the terrace widths to be scaled by an optimum effective mean width. We discuss quantitatively the approach of a Wigner distribution to a Gaussian form for strong repulsions, how errors in normalization or mean affect the deduced interaction, and how optimally to extract the interaction from the variance and mean of the TWD. We show that correlations reduce by two orders of magnitude the number of independent measurements in a typical scanning tunneling microscopy image. We also discuss the effect of the discreteness (‘quantization’) of terrace widths, finding that for high misorientation (small mean width) the standard continuum analysis gives faulty estimates of step interactions.
Keywords :
and topography , Roughness , surface structure , Vicinal single crystal surfaces , Copper , morphology , Equilibrium thermodynamics and statistical mechanics , Stepped single crystal surfaces
Journal title :
Surface Science
Serial Year :
2000
Journal title :
Surface Science
Record number :
1678824
Link To Document :
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