Estimating uncertainties on data values has always been an important and under-emphasized part of small-angle scattering. Uncertainties are critical to your data: they tell you what is most likely a real difference, and what is probably just measurement noise. Fortunately, many datasets come complete with data uncertainties, but there are still quite a few cases where this is not the case, or where the provided uncertainty estimates are unrealistic. So what can we do?
Today is another holiday in Japan. There is a tendency here for the national holidays to be on Mondays or Fridays, and there is typically about one per month of those. So I hope you do not mind, but I would like to move the weekly update date to Tuesdays instead.
Mind you, this will be Tuesday in Japan, so if you are reading this in America, you can still read the updates on Monday.
I will not take this opportunity to relax this week, there will be an update tomorrow. Yesterday, a funny thought struck me with respect to error estimation, and I have been playing around a bit to test it. So tomorrow you will have all kinds of error estimating goodness!
See you then!
Today is a day of relief for Dr. Julian Stirling and his eight co-authors (with many looking forward to the response, including Raphaël Lévy). The paper released today opposes ten years of prolific work from a group claiming to have made and observed stripes on the surface of nanoparticles (c.f. Figure 0, Figure 1 in this post). While most of the work revolves around scanning probe microscopy (SPM), small-angle scattering also played a minor role (c.f. Figure 2 and this paper). This, coupled with modern approaches to publication, led to my inclusion in the (otherwise amazing) list of authors. Here is how this came to be.
[ed1: Progress on the Everything SAXS book has been good: a framework is now in place with chapters, the revision ID on the title page and even a Makefile and readme. The time approaches to enter some content!
ed2: Something cool approaches (next week).]
Most of the times we are scrounging for crumbs on the lab floor, sticking parts together with chewing gum and cardboard, but every now and then a small wad of crumpled dollar bills is pushed into ones hand with a hushed whisper: “spend it now!”. Read more »
For a while now, I have wanted to write a book about SAXS, introducing the topics, explaining the details, and including many of the more popular posts from this site. Unfortunately, no lucrative old-style book contracts have been proffered, so I will resort to another approach: a living Git-book.
A remark in a recent paper by Dr. Yojiro Oba (currently at KURRI) caught my attention. It discusses which shape assumption can be appropriate to fit a scattering pattern of polydisperse systems. In the paper, the shape assumption is spherical (based on TEM evidence), and a further remark goes as follows:
“ Since no q−a (a < 4) behaviour is observed, the possibility of anisotropic shapes such as a rod, disc, and ellipsoid of revolution is denied. ”
That is an elegant way of putting it (note that it is an unidirectional exclusion and does not work the other way), and it sounds about right. So let’s test this with some simulations. These, of course, cannot prove that the statement is true, but can only disprove the statement. Read more »
Contrast variation is commonly used in SANS to highlight a single segment of a mutli-part structure. In SANS it is easy to do this because a wide range of scattering length densities can be accessed by simple mixing of water and deuterated water. In SAXS this is not so easy. A recent arXiv paper  by Raul Garcia-Diez, however, shows one method for getting it done in SAXS. Read more »
This has been a very interesting last couple of days. I was unable to join Zoë Schnepp and Martin Hollamby for our SAXS beamtime at Diamond. Instead, I decided to try and join in from abroad. The plans were ambitious: to do on-the-fly high-quality data correction and analysis. In the end there we achieved partial success.