Spatially-resolved in-situ structural study of organic electronic devices with nanoscale resolution: the plasmonic photovoltaic case study.

A novel high spatial resolution synchrotron X-ray diffraction stratigraphy technique has been applied in-situ to an integrated plasmonic nanoparticle-based organic photovoltaic device. This original approach allows for the disclosure of structure-property relations linking large scale organic devices to length scales of local nano/hetero structures and interfaces between the different components.

Selective energy dispersive diffraction peak fitting by using genetic algorithm.

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.

Angular calibration in energy dispersive X-Ray diffraction by using genetic algorithms.

In Energy Dispersive X-Ray diffraction measurements, the estimate of momentum transfer q, on which the diffracted intensity depends, should be as accurate as possible. Since q, in turn, depends on both the energy and the scattering angle, an error on the latter due to an incorrect positioning of the sample, to the asymmetric angular spread induced by the collimation slits or, in general, to any uncertainty on the geometric setup, results in an uncertainty on the q value. Here, a new self calibration method to correct such errors, based on a genetic algorithm is presented. It is robust, fast and completely automatic. Results obtained by carrying out Energy Dispersive X-Ray Diffraction measurements on reference samples are reported and discussed. They show how the application of such genetic algorithm may provide a fast esteem of the two parameters required when multiple angle pattern collection is performed, namely the effective starting angle and the angular step. In this way, reliable q-values of all the diffraction pattern features (Bragg peaks for crystalline, and diffused bumps for non-crystalline samples) are obtained.

AFM for diagnosis of nanocrystallization of steels in hardening processes.

INTRODUCTION: The aim of this study is to investigate the nanocrystallization of steels caused by the transformation from the austenitic to the martensitic phase induced by a severe plastic deformation (SPD) treatment. In this framework, we applied an air blast shot peening treatment, which is a simple protocol widely used for industrial purposes. METHODS: AISI 286 and AISI 316 specimens were peened for different times and polished using diamond pastes in order to remove corrugations higher than 1 mum. The characterization of the steel surfaces was performed by atomic force microscopy (AFM) operating in contact mode. Additional EDXD measurements were performed to confirm the phase transition. RESULTS AND DISCUSSION: An AFM-based characterization at nanometric level of the steel surfaces is provided. When the peening exceeds a threshold time that, as expected, depends on the steel composition, a uniform nanostructuration is detected. It is well known that such rearrangement is associated to the growth of a martensitic phase. To date, AFM has been employed in this field only for few applications and to solve specific problems. On the other hand, our results demonstrate that this is a useful technique for the characterization of hardened surfaces, especially when non-destructive sample preparation treatments are required. Moreover, we show that AFM can be a useful tool also for in situ industrial diagnostics of metallic parts.