CeO2 nanoparticles synthesized by a microwave-assisted hydrothermal method: evolution from nanospheres to nanorods

Ceria (CeO2) plays a vital role in emerging technologies for environmental and energy-related applications. The catalytic efficiency of ceria nanoparticles depends on its morphology. In this study, CeO2 nanoparticles were synthesized by a microwave-assisted hydrothermal method under different synthesis temperatures. The samples were characterized by X-ray diffraction, transmission electron microscopy, Raman scattering spectroscopy, electron paramagnetic resonance spectroscopy and by the Brunauer-Emmett-Teller method. The X-ray diffraction and Raman scattering results indicated that all the synthesized samples had a pure cubic CeO2 structure. Rietveld analysis and Raman scattering also revealed the presence of structural defects due to an associated reduction in the valence of the Ce4+ ions to Ce3+ ions caused by an increasing molar fraction of oxygen vacancies. The morphology of the samples was controlled by varying the synthesis temperature. The TEM images show that samples synthesized at 80 degrees C consisted of spherical particles of about 5 nm, while those synthesized at 120 degrees C presented a mix of spherical and rod-like nanoparticles and the sample synthesized at 160 degrees C consisted of nanorods with 10 nm average diameter and 70 nm length. The microwave-assisted method proved to be highly efficient for the synthesis of CeO2 nanoparticles with different morphologies.

Gaussian deconvolution: a useful method for a form-free modeling of scattering data from mono- and multilayered planar systems

A new method for analysis of scattering data from lamellar bilayer systems is presented. The method employs a form-free description of the cross-section structure of the bilayer and the fit is performed directly to the scattering data, introducing also a structure factor when required. The cross-section structure (electron density profile in the case of X-ray scattering) is described by a set of Gaussian functions and the technique is termed Gaussian deconvolution. The coefficients of the Gaussians are optimized using a constrained least-squares routine that induces smoothness of the electron density profile. The optimization is coupled with the point-of-inflection method for determining the optimal weight of the smoothness. With the new approach, it is possible to optimize simultaneously the form factor, structure factor and several other parameters in the model. The applicability of this method is demonstrated by using it in a study of a multilamellar system composed of lecithin bilayers, where the form factor and structure factor are obtained simultaneously, and the obtained results provided new insight into this very well known system.

Incorporating IT & AT Convergence into Lean Thinking/Six Sigma via the Smarter Operation Transformation (SOT) Methodology

The growing demands for industrial products are imposing an increasingly intense level of competitiveness on the industrial operations. In the meantime, the convergence of information technology (IT) and automation technology (AT) is showing itself to be a tool of great potential for the modernization and improvement of industrial plants. However, for this technology fully to achieve its potential, several obstacles need to be overcome, including the demonstration of the reasoning behind estimations of benefits, investments and risks used to plan the implementation of corporative technology solutions. This article focuses on the evolutionary development of planning and adopting processes of IT & AT convergence. It proposes the incorporation of IT & AT convergence practices into Lean Thinking/Six Sigma, via the method used for planning the convergence of technological activities, known as the Smarter Operation Transformation (SOT) methodology. This article illustrates the SOT methodology through its application in a Brazilian company in the sector of consumer goods. In this application, it is shown that with IT & AT convergence is possible with low investment, in order to reduce the risk of not achieving the goals of key indicators.