D. Bailo

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.

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.

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.

Assessment of Three Spectroscopic Techniques for Rapid Estimation of Calcite in Copper Ore

This paper presents the assessment of three spectroscopic techniques, i.e., Raman spectroscopy (RS), ultraviolet fluorescence (UVF) spectroscopy, and energy-dispersive X-ray diffraction (ED-XRD), for measuring calcite (CaCO3) concentration in copper ore. The results for the three methods are compared in terms of their correlation coefficient R2 and prediction error (root-mean-square error of prediction, RMSEP). These approaches substantially shorten the measurement time with respect to current laboratory procedures from 300 min down to 1,15, and 9 min for RS, ED-XRD, and UVF, respectively, while preserving a good accuracy level (RMSEP <; 0.577). Prediction models were calibrated and validated for the three techniques, using the correlation coefficients Rc2 and Rv2, the error of prediction (RMSEP), and the error of calibration (root-mean-square error of calibration, RMSEC). Rv2 values of 0.90,0.88, and 0.94 were obtained for the RS, UVF, and ED-XRD models, respectively. The calibration and validation were performed for calcite concentrations ranging from 2.9% to 10.7%, and although the ED-XRD model performed slightly better than its RS counterpart, the time taken by the latter is significantly shorter than that by the other two, representing a good candidate for online estimation of calcite concentration.

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.

Remote Laboratory System: A Model Proposal and Implementation on X-Ray Laboratory Machines

This work presents the development and implementation of a remote X-ray laboratory, located at CNR â?? ISM, Rome, Italy. The remote laboratory model is based on a innovative, flexible and scalable modular architecture which makes it easier to update, expand or deal with problems. The developed system, accessible for control only to authenticated users, provides a remote control of the laboratory equipment, a real time visual feedback of the machinery and the opportunity to retrieve and make a preliminary analysis of stored data. These features offer the possibility to researchers of carrying out real research experiments remotely, avoid the exposure to ionizing radiation produced by the X-Ray equipment. The system also provides the opportunity of carrying out experiments programmatically, optimizing the use of available machine time and providing the possibility of running experiments in special environment-dependent conditions. Eventually, the system allows researchers located outside of laboratory site to run experiments in a collaborative way.