Affiliations: Struttura Dipartimentale di Matematica e Fisica,
Università di Sassari, Sassari, Italy | Istituto di Struttura della Materia, CNR, Rome, Italy
Note: [] Corresponding author: A. Brunetti, Struttura Dipartimentale di
Matematica e Fisica, Università di Sassari, Via Vienna, Sassari, Italy.
E-mail: brunetti@uniss.it
Abstract: Accurate and precise estimates of X-Ray diffraction peak parameters
is mandatory, when small dynamic changes of lattice parameters have to be
quantitatively analyzed. To follow in real time such changes, a large set of
patterns must be usually collected, so that the position of certain peaks of
interest can be tracked. To calculate the positions, a fitting procedure of the
peaks is required and several algorithms are reported in the literature for
this purpose. However, these algorithms are mainly focused on the determination
of parameters based on a model of the cell geometry. Here, we present a new
algorithm allowing to carry out the fitting procedure on a portion only of the
pattern, with neither tight constraints on the dataset, nor restrictive
hypotheses on the sample structure. In our case, a coarse estimate of the
detector resolution and of the positions of the peaks to fit are the only
initial conditions required. This method can be regarded as a hybrid technique,
as it makes use of a genetic algorithm approach, mixed with an intensive
multiple random generation of the population, that makes it similar to a Monte
Carlo technique. Moreover, adaptive genetic operators have been implemented in
the data processing code. These properties result in a fast and efficient
algorithm, a fundamental requirement when, as in the present case, the Energy
Dispersive X-ray Diffraction method is applied to observe structural changes,
which implies the acquisition of many patterns in a relatively short time. The
result of this application is shown by some practical examples.
