measurement accuracy

Does it matter? part 3: Natural background radiation

2012/08/06 // 0 Comments

[With thanks to dr. Masato Ohnuma for bringing this to my attention] It is all around us, and occasionally all through us, and every now and then, your small-angle scattering detector might see them: photons from nature. Do we need to consider these all-natural organic photons in the data corrections we do, or can we safely neglect them as “present in homeopathic concentrations”? The short answer: we absolutely need to take it into account! The slightly longer answer is a bit more nuanced. Natural background should work the same as a darkcurrent measurement, it is detected independent of the state of the X-ray generator or sample transmission, indeed, it bypasses most of these. It should only be a function of time and location (and maybe wind direction…). Considering that some of this radiation might come from the giant nuclear reactor in the sky, could it be significantly dependent on time as well? At hand we have: 1) a SAXS instrument in a state of [...]

Ruler vs. Silver behenate: Trust but verify

2012/06/18 // 4 Comments

One of the most important parameters you need when analyzing small-angle scattering patterns is the distance from the sample to the detector, as this defines the scattering wave vector q. This is often determined using the same approach as for wide-angle diffraction: measurement of a standard crystalline sample. Whereas in the past, stretched rat tail collagen was l’objet du jour, these days people prefer the much more sensible silver behenate. This saves you from having to find a suitable rat donor, preparing the tail, and stretching it just so that it would give you the right answer (as the degree of stretching would affect the distance). Silver behenate is easier to apply, easy to get and shows a nice round crystalline peak for all but the smallest angles. For a while now, though, I and some others have measured the sample-to-detector distance with a ruler when measuring. There are several benefits to this. Firstly, it is dead simple to do (there is no need to recode my [...]

Nothing new here

2012/03/22 // 0 Comments

So it seems science has beaten us to the punch once again. Remember last week’s optimistic story on how you can make better use of your (measurement) time? Turns out it has been done (at least once) before. The year was 1993, the authors were M. Steinhart and J. Pleštil, and they did the same from a different perspective [1]. Credit where credit is due, their yet un-cited paper contains a good study of measurement stability and its effects on inferred information, and indeed has the equation for effective time-expenditure available (though written up in a confusing way). So all sadness on our side aside (as there is now no short-sweet-and-quick publication possible on this), please use your time wisely and cite that 1993 paper as it deserves. Do not let good methods like this be covered by years of dust. To give you some more ammunition for your citation-gun, here is a good paper detailing dead-time correction, and how Poisson statistics fail when these corrections are applied [...]

Making better use of your time: optimizing measurement time

2012/03/14 // 1 Comment

Often, especially when measuring on big facilities, you are given a limited amount of time. So when it comes to measuring the sample and the background, this limited time has to be divided between a measurement of the sample, and a measurement of the background. Normally, one would spend about 50% of the time on a sample, and 50% on the background, or even more time on the background “because the counts are so low” (I know, I did the same!). There must be a better way to calculate the optimum division of time! So me and a colleague, Samuel Tardif, spent a little bit of time jotting down some equations, and plotting the result. The result is that for large differences in the signal-to-noise ratio (c.q. sample count rate to background count rate), significant reductions in uncertainty can be obtained through better division of time for any small-angle scattering measurement. In the case of a Bonse-Hart camera or a step-scan small-angle scattering measurement, each [...]

Data processing flowchart and news on an old publication

2012/02/29 // 1 Comment

Short news first; by going through the motions and waiting for Elsevier to get back to me, I have gotten permission (for the royal sum of 0.00 eurodollars) to repost one more paper from Polymer on my site. So that has now gone in the 2010 publications page here. Then it is time to give you something. For those who have to do their own data processing and would like to get my way of doing it, I have attached my data processing flowchart to this post. It is not a perfect method, but as far as I can tell it works quite well. If you are interested in getting the actual Python code that does all this work, drop me a line. Since the code is quite new, it does not support many strange detectors, so if support needs to be built for a particular detector, I’ll be happy to spend some of my time looking at whether it can be done. So there:imp_imagecorrect_and_imgint. Let me know if there are improvements, obscurities or if you have any other comments on [...]