International
Tables for
Crystallography
Volume C
Mathematical, physical and chemical tables
Edited by E. Prince

International Tables for Crystallography (2006). Vol. C. ch. 2.6, p. 103

Section 2.6.1.6.4. Direct structure analysis

O. Glattera

2.6.1.6.4. Direct structure analysis

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It is impossible to determine the three-dimensional structure ρ(r) directly from the one-dimensional information I(h) or p(r). Any direct method needs additional a priori information – or assumptions – on the system under investigation. If this information tells us that the structure only depends on one variable, i.e. the structure is in a general sense one dimensional, we have a good chance of recovering the structure from our scattering data.

Examples for this case are particles with spherical symmetry, i.e. ρ depends only on the distance r from the centre, or particles with cylindrical or lamellar symmetry where ρ depends only on the distance from the cylinder axis or from the distance from the central plane in the lamella. We will restrict our discussion here to the spherical problem but we keep in mind that similar methods exist for the cylindrical and the lamellar case.

Spherical symmetry . This case is described by equations (2.6.1.51)[link] and (2.6.1.52)[link]. As already mentioned in §2.6.1.3.2.2[link], we can solve the problem of the calculation of ρ(r) from I(h) in two different ways. We can calculate ρ(r) via the distance distribution function p(r) with a convolution square-root technique (Glatter, 1981[link]; Glatter & Hainisch, 1984[link]). The other way goes through the amplitude function A(h) and its Fourier transform. In this case, one has to find the right phases (signs) in the square-root operation [\{A(h)=\pm [I(h)^{1/2}]\}]. The box-function refinement method by Svergun, Feigin & Schedrin (1984[link]) is an iterative technique for the solution of the phase problem using the a priori information that ρ(r) is equal to zero for [r \ge R_{\max}] (Dmax/2). The same restriction is used in the convolution square-root technique. Under ideal conditions (perfect spherical symmetry), both methods give good results. In the case of deviations from spherical symmetry, one obtains better results with the convolution square-root technique (Glatter, 1988[link]). With this method, the results are less distorted by non-spherical contributions.

Multipole expansions . A wide class of homogeneous particles can be represented by a boundary function that can be expanded into a series of spherical harmonics. The coefficients are related to the coefficients of a power series of the scattering function I(h), which are connected with the moments of the PDDF (Stuhrmann, 1970b[link],c[link]; Stuhrmann, Koch, Parfait, Haas, Ibel & Crichton, 1977[link]). Of course, this expansion cannot be unique, i.e. for a certain scattering function I(h) one can find a large variety of possible expansion coefficients and shapes. In any case, additional a priori information is necessary to reduce this number, which in turn influences the convergence of the expansion. Only compact, globular structures can be approximated with a small number of coefficients.

This concept is not restricted to the determination of the shape of the particles. Even inhomogeneous particles can be described using all possible radial terms in a general expansion (Stuhrmann, 1970a[link]). The information content can be increased by contrast variation (Stuhrmann, 1982[link]), but in any event one is left with the problem of how to find additional a priori information in order to reduce the possible structures. Any type of symmetry will lead to a considerable improvement. The case of axial symmetry is a good example. Svergun, Feigin & Schedrin (1982[link]) have shown that the quality of the results can be further improved when upper and lower limits for ρ(r) can be used. Such limits can come from a known chemical composition.

References

First citation Glatter, O. (1981). Convolution square root of band-limited symmetrical functions and its application to small-angle scattering data. J. Appl. Cryst. 14, 101–108.Google Scholar
First citation Glatter, O. (1988). Comparison of two different methods for direct structure analysis from small-angle scattering data. J. Appl. Cryst. 21, 886–890.Google Scholar
First citation Glatter, O. & Hainisch, B. (1984). Improvements in real-space deconvolution of small-angle scattering data. J. Appl. Cryst. 17, 435–441.Google Scholar
First citation Stuhrmann, H. B. (1970a). Interpretation of small-angle scattering functions of dilute solutions and gases. A representation of the structures related to a one-particle-scattering function. Acta Cryst. A26, 297–306.Google Scholar
First citation Stuhrmann, H. B. (1970b). Ein neues Verfahren zur Bestimmung der Oberflächenform und der inneren Struktur von gelösten globulären Proteinen aus Röntgenkleinwinkelmessungen. Z. Phys. Chem. 72, 177–184.Google Scholar
First citation Stuhrmann, H. B. (1970c). Die Bestimmung der Oberflächenform von gelöstem Myoglobin aus Röntgenkleinwinkelmessungen. Z. Phys. Chem. 72, 185–198.Google Scholar
First citation Stuhrmann, H. B. (1982). In Small-angle X-ray scattering, edited by O. Glatter & O. Kratky, Chap. 6. London: Academic Press.Google Scholar
First citation Stuhrmann, H. B., Koch, M. H. J., Parfait, J., Haas, J., Ibel, K. & Crichton, R. R. (1977). Shape of the 50S subunit of Escherichia coli ribosomes. Proc. Natl Acad. Sci. USA, 74, 2316–2320.Google Scholar
First citation Svergun, D. I., Feigin, L. A. & Schedrin, B. M. (1982). Small-angle scattering: direct structure analysis. Acta Cryst. A38, 827–835. Google Scholar
First citation Svergun, D. I., Feigin, L. A. & Schedrin, B. M. (1984). The solution of the one-dimensional sign problem for Fourier transforms. Acta Cryst. A40, 137–142.Google Scholar








































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