## Tag Archives: polydispersity

## Monte-Carlo: now in 2D!

Small-angle scattering analysis has never been easy for those working with oriented nanostructures (e.g. fibres, processed polymers, rolled metal alloys), whose structure may lead to anisotropic small-angle scattering. Upon the collection of such 2D scattering patterns, one can integrate thin pie-slices of the data to obtain 1D curves and analyse them in the same way […]

## Papers! One of mine and one on detector data read-in

It has been a long time in the making, but now the day has finally come where the 1D Monte Carlo method has been published! To top it off, the publication is open access (courtesy of my current institute: NIMS), and has a wicked showcase document as supplementary material. Feel (very) free to check it […]

## Free Code! McSAS: A Monte-Carlo way for retrieving particle size distributions.

Good news for those of you on the hunt for a way to get polydispersity (size distribution) information from your scattering patterns. Two pieces of good news, to be precise! Firstly, the paper that describes my implementation of the method that does exactly this has just been accepted earlier this month for publication in J. […]

## New video online- presenting observability

Dear readers, First of all, a merry end-of-year thingie (insert name here) to all of you. Last week, I presented a short 15-minute talk at the MRS-J conference in Yokohama. While it was a nice opportunity to present and meet people, it is a relatively small conference. With that in mind, I decided to re-record […]

## Revisiting observability in polydisperse systems: “real” polydispersity

edited on 2011-07-20 14:51 to add equation defining observability Of course I could not leave you hanging after the last post with that question “does the observability still scale with the radius squared for samples with more than two particles?”. Short answer: yes. Long answer: mostly, with some interesting lessons w.r.t. q-angles and limitations. Click […]

## Observability in polydisperse systems. What is all the accuracy for?

Abstract of this post: In this post, I will show that for a spherical two-particle system, the observability of the smaller particle scales with the inverse squared radius, quite different from the scattering power, which scales with the radius to the sixth power (volume squared). This means that scattering data with 1% error can be […]

## Comments on Deschamps, 2011 and A clarification on Guinier for Polydisperse systems

After browsing through a recent Journal of Applied Crystallography, I came across a paper by Deschamps. It indicates to me that there is a slight lack of information communication in some aspects of SAXS. Firstly, it mentions in the introduction that the advanced (Fourier-transform-based) SAXS analysis methods cannot “extract simultaneously the precipitate form factor and […]

## More details for the monte-carlo code

As promised, some more details which hopefully make the monte-carlo code (discussed here) more useful to you; the software documentation. softwaremanual_mcfit In the documentation are also some examples using the scattering pattern generators discussed before. Let me know if you canor cannot get it to work and post your findings here (or father, on the […]

## Notes on Guinier

…well, his famous SAXS analysis method. This documentGuinier_short, copyright Brian Pauw gives a short description and review of the applicability of the Guinier method to polydisperse systems. It also shows, through analysis of simulated data, what q-range should be measured for the Guinier method to be valid. In short, the rule of qmax=1.3/Rg still holds, […]