Ativação da ligação c-h no metano por espécies MOm n+ (M = Nb, Fe; m = 0, 1; n = 0, 1, 2): estrutura eletrônica, mecanismo de reação e reatividade

The need for renewal and a more efficient use of energy resources has provided an increased interest in studies of methane activation processes in the gas phase by transition metal oxides. In this respect, the present work is an effort to assess , by means of a computational standpoint, the reactivity of NbOm n+ and FeOm n+ (m = 1, 2, n = 0, 1, 2) oxides in the activation process of the methane C-H bond, which corresponds to the first rate limiting step in the process of converting methane to methanol. These oxides are chosen, primarily, because the iron oxides are the most experimentally studied, and iron ions are more abundant in biological mediums. The main motive for choosing niobium oxides is the abundance of natural reserves of this mineral in Brazil (98%), especially in Minas Gerais. Initially, a thorough investigation was conducted, using different theoretical methods, to analyze the structural and electronic properties of the investigated oxides. Based on these results, the most reliable methodology was selected to investigate the activation process of the methane C-H bond by the series of iron and niobium oxides, considering all possible reaction mechanisms known to activate the C-H bond of alkanes. It is worth noting that, up to this moment and to our knowledge, there are no papers, in literature , investigating and comparing all the mechanisms considered in this work. I n general, the main results obtained show different catalytic tendencies and behaviors throughout the series of monoxides and dioxides of iron and niobium. An important and common result found in the two studies is that the increase in the load on the metal center and the addition of oxygen atoms to the metal, clearly favor the initial thermodynamics of the reaction, i.e., favor the approach of the metal center to methane, distorting its electron cloud and, thereby, decreasing its inertia. Comparing the two sets of oxides, we conclude that the iron oxides are the most efficient in activating the methane C-H bond. Among the iron oxides investigated, FeO + showed better kinetic and thermodynamic performance in the reaction with methane, while from the niobium oxides and ions NbO 2+ and NbO2 2+, showed better catalytic efficiency in the activation of the methane C-H bond.

Componentes principais na elaboração de índices de provas de desempenho em bovinos

The principal component analysis assists the producers in making decision of which evaluated features must be maintained in performance tests indexes, according to the variation present in these animals evaluated. The objective in this study was to evaluate a set of characteristics measured in a performance test in semifeedlot cattle of the Simmental and Angus breeds, by means principal component analysis (PC), aim to identify the features that represent most of the phenotypic variation for preparation of indexes. It was used data from 39 Angus and 38 Simmental bulls from the Santa Éster farm, located in Silvianópolis - MG. The performance test period was from october 2014 to february 2015. The features evaluated in the test were: final weight (FW), average daily gain weight (GW), respiratory rate (RR), haircoat temperature (HT) and rectal (RT), hair number (HN), hair length (HL), hair thickness (HT), muscularity (MUSC), racial characteristics, angulation, reproductive and balance (BAL), height of the front and back, width and length of croup, body length, depth and heart girth, subcutaneous fat thickness and rump (FTR), loin eye area and marbling (MAR). It was used PRINCOMP from SAS program for procedure the PC analysis. It was found that of the 27 features evaluated, the first four PC for Simmental breed explained 74% total variation data. The four PC selected with the corresponding weighting coefficients formed the following index: (0.27 * FW) + (0.47 * MUSC) + (0.50 * HL) + (0.39 * HT). Since the characteristics related to the adaptability of great importance for the studied breed, it was decided to keep the index of evidence for the Angus breed, the feature hair number, because there is a feature that presented a great variability and occupied one of the first principal component. Thus, the Angus index was composed by five features, with 79% total variation data, resulting in the following formula: (0.26 * FW) + (0.33 * BAL) + (0.58 * MAR) - (0.43 * FTR) – (0.38 * HN). By the principal component analysis it was possible to minimize the features number to be evaluated on performance tests from that farm, making the animal selection rapidly and accurate.