scatterBrain SEC SAXS Data Reduction

Owned by SAXS Cluster (Unlicensed)
Nov 09, 2021
3 min read

There may be several steps required during data reduction for many samples run at the SAXS beamline. For example, samples run through a size exclusion chromatography (SEC) setup require several processing steps. Typically, each sample run using SEC will generate hundreds of images, only some of which will correspond to when the sample scattering. These images are also likely to be noisy, requiring several to be averaged together. A selection of the features in scatterBrain allow the user to identify which images correspond to the sample, average images, perform buffer subtraction and export the final data. This case study presents these steps as an example of how features can be used to assist in data reduction.


  • The Contour Plot is used to highlight when the sample is coming off the SEC column

  • To further highlight which files correspond to the sample, a buffer image is applied as a background for the Contour Plot. An image shortly after the SEC run started is used as the buffer background as no sample is expected this early

  • A box is drawn around the peak to zoom in on the Contour Plot and further highlight which files correspond to the sample

  • A record is made of which files correspond to the sample peak for further plotting (starting around 0168 in this case). Note: Image numbers may be offset from the Contour Plot Y-axis values. In this case the first file plotted, corresponding to a value of 1 in the Y-axis, ended in 0064. Therefore 63 must be added to locate the specific files corresponding to the peak

  • A range of images are selected in the Image Window to be loaded for display in the Plot Window. This range should cover the full appearance of the peak from pure buffer to peak maximum. As the peak is at a maximum in images with an index near 0231, a range 0175 to 240 is plotted to show buffer to peak maximum

  • The Plot Window is used to identify which files may be averaged together. Selecting files in the Plot Window highlights them in bold, allowing identification of the peak maximum and last buffer before the sample.

  • A selection of images immediately before the sample peak and selection of images collected at the peak maximum are identified and summed to reduce noise. As many images as possible are summed for the sample peak and a similar number are summed for the buffer. scatterBrain sums images, rather than averaging them, as normalisation accounts for this in a similar manner to a long exposure time. The file names for these summed images are chosen to readily allow future identification of their source

  • When the summed images are produced they are automatically plotted in the Plot Window. The summed buffer is used for background subtraction by dragging the sample filename onto the buffer filename.

  • The final sample data is exported. In this case, the option 'Save EACH profile to individual files' is selected to produce a single text file with 3 columns of data, i.e. Q, I and E.

  • The Experiment File is saved to allow future access to the summed images.