Using the evaluation program you can evaluate the previously prepared and uploaded data for the microstructural parameters using the method of Convolutional Multiple Whole Profile fitting. The options of the evaluation program are:

1.

Specification of the sample name.

2.

Selection of the crystal system. The possible selections are: cubic (default) or hexagonal. In the following the parentheses indicate the case of hexagonal system.

3.

Setting the values of the input parameters. The value of the lattice constant(s), the absolute value of the Burgers-vector, C_h00 (or C_hk0) and the wavelength of the measuring instrument has to be specified.

4.

Specification of the instumental profiles. You can select if you have instrumental profiles, and you can specify the name of the instrumental profile directory.

5.

Specification of the interval used for fitting and plotting. Here you can specify the lower and upper limit of the interval used for fitting and plotting (in Two theta degrees).

6.

Selection of the size function. The possible selections are: no size effect, spherical size function (default) or ellipsoidal size function.

7.

Specification of the sampling of the theoretical Fourier transforms. The intensity limit of the normalized theoretical Fourier transforms can be specified. Please note that you need to specify this limit only in case if you don't have instrumental profiles.

8.

Specification of the sampling of the simulated powder pattern data. The value of N1, N2 and the profile cutting parameter should be specified here.

9.

Specification of the initial values of the parameters. The initial values of the fitting parameters has to be specified. They are always saved for subsequent runs. You have the option to fix the value of any parameter, this means that the value of that parameter will not be refined during the fitting procedure. Fixing the value of d*e means that the value of the parameter M^* is fixed. Use this option if the program enters into an asymptotic minimum (the values of rho and R_e^* tend to infinity and zero, respectively, and the asymptotic standard errors of the parameters d and e become extremely large, larger than 100%).

10.

Peak parameter refinement and weighting. Here you can choose if you want to refine the peak positions and peak intensities. If the peaks have very different intensities, you can set here to use weights in the fitting algorithm.

11.

Fit control. The limit of stopping is the convergence criterium of the Marquardt-Levenberg algorithm: the fitting is stopped if the specified maximal number of iterations (default: 200) is reached or Delta Chi²/Chi² between two iteration steps is less than the specified limit (default: 10^-9).