QENS Data Interpretation

As in many other scattering techniques it is difficult or even impossible to get information directly from QENS data. A standard approach is to create a model, which is normally a mathematical expression of how the particles are moving, interacting or other hypothesis about the sample we want to investigate. From this model we can calculate what the QENS data should look like. This theoretical QENS data can then be compared to the experimental data. If the theoretical data and the experimental data matches, the model is a good description of system we are measuring. If the two data do not match, then the model is not a good description of the system. We can then make adjustment to the model, and check if that solved the problem so the model is a good description. We can keep making adjustments to the model until we have a good description of the system, or if we are unable to describe the experimental data using the model we have to make a new model and try again. This is called model fitting or model refinement and is perhaps one of the most fundamental parts of experimental scientific work. From the model we can now learn something about our sample like the relaxation rate of the polymers in the sample.

There are general observations that can be made without fitting a model if the system is simple enough. One simple relation is between the velocities if the particles in for an example a polymer sample. The faster the particle moves the higher the possible energy transfers are.

This means that the QENS peak will be wider in ΔE plot if the particles in the sample move faster, since we have a larger range of energy transfers happening. The energy resolution of the neutron instrument has to be taken into account when looking at QENS data. The resolution is the minimum energy change that the instrument can measure, so any change lower than the resolution we cannot distinguish.

Two plots showing an example of QENS data. On the x-axis are ΔE. The first plot has a high peak that represents the recorded data. The second plot shows three peaks; the elastic signal, which is a quite high peak, the Quasi Elastic signal, which is a very low and flat peak, and a third peak that reaches the highest point, which is representing the total signal.

Figure. Example of QENS data