18 resultados para strontium
Resumo:
The performance of La((1-y))Sr(y)Ni(x)Co((1-x))O(3) perovskites for the water gas shift reaction (WGSR) was investigated. The samples were prepared by the co- precipitation method and were performed by the BET method, XRD, TPR, and XPS. The catalytic tests were performed at 300 and 400 A degrees C and H(2)O(v)/CO = 2.3/1 (molar ratio). The sample with the highest surface area is La(0.70)Sr(0.30)NiO(3). The XRD results showed the formation of perovskite structure for all samples, and the La(0.70)Sr(0.30)NiO(3) sample also presented peaks corresponding to La(2)NiO(4) and NiO, indicating that the solubility limit of Sr in the perovskite lattice was surpassed. The replacement of Co by Ni favored the reduction of the species at lower temperatures, and the sample containing Sr presented the highest amount of reducible species, as identified by TPR results. All samples were active, the Sr containing perovskite appearing the most active due to the highest surface area, presence of the La(2)NiO(4) phase, and higher content of Cu in the surface, as detected by XPS. Among the samples containing Co, the most active one was that with x = 0.70 (60% of CO conversion).
Resumo:
The performance of La(2-x)M(x)CuO(4) perovskites (where M = Ce, Ca or Sr) as catalysts for the water-gas shift reaction was investigated at 290 degrees C and 360 degrees C. The catalysts were characterized by EDS, XRD, N(2) adsorption-desorption, XPS and XANES. The XRD results showed that all the perovskites exhibited a single phase (the presence of perovskite structure), suggesting the incorporation of metals in the perovskite structure. The XPS and XANES results showed the presence of Cu(2+) on the surface. The perovskites that exhibited the best catalytic performance were La(2-x)Ce(x)CuO(4) perovslcites, with CO conversions of 85%-90%. Moreover, these perovskites have higher surface areas and larger amounts of Cu on the surface. And Ce has a higher filled energy level than the other metals, increasing the energy of the valence band of Ce and providing more electrons for the reaction. Besides, the La(1.80)Ca(0.20)CuO(4) perovskite showed a good catalytic performance.
Resumo:
To identify chemical descriptors to distinguish Cuban from non-Cuban rums, analyses of 44 samples of rum from 15 different countries are described. To provide the chemical descriptors, analyses of the the mineral fraction, phenolic compounds, caramel, alcohols, acetic acid, ethyl acetate, ketones, and aldehydes were carried out. The analytical data were treated through the following chemometric methods: principal component analysis (PCA), partial least square-discriminate analysis (PLS-DA), and linear discriminate analysis (LDA). These analyses indicated 23 analytes as relevant chemical descriptors for the separation of rums into two distinct groups. The possibility of clustering the rum samples investigated through PCA analysis led to an accumulative percentage of 70.4% in the first three principal components, and isoamyl alcohol, n-propyl alcohol, copper, iron, 2-furfuraldehyde (furfuraldehyde), phenylmethanal (benzaldehyde), epicatechin, and vanillin were used as chemical descriptors. By applying the PLS-DA technique to the whole set of analytical data, the following analytes have been selected as descriptors: acetone, sec-butyl alcohol, isobutyl alcohol, ethyl acetate, methanol, isoamyl alcohol, magnesium, sodium, lead, iron, manganese, copper, zinc, 4-hydroxy3,5-dimethoxybenzaldehyde (syringaldehyde), methaldehyde (formaldehyde), 5-hydroxymethyl-2furfuraldehyde (5-HMF), acetalclehyde, 2-furfuraldehyde, 2-butenal (crotonaldehyde), n-pentanal (valeraldehyde), iso-pentanal (isovaleraldehyde), benzaldehyde, 2,3-butanodione monoxime, acetylacetone, epicatechin, and vanillin. By applying the LIDA technique, a model was developed, and the following analytes were selected as descriptors: ethyl acetate, sec-butyl alcohol, n-propyl alcohol, n-butyl alcohol, isoamyl alcohol, isobutyl alcohol, caramel, catechin, vanillin, epicatechin, manganese, acetalclehyde, 4-hydroxy-3-methoxybenzoic acid, 2-butenal, 4-hydroxy-3,5-dimethoxybenzoic acid, cyclopentanone, acetone, lead, zinc, calcium, barium, strontium, and sodium. This model allowed the discrimination of Cuban rums from the others with 88.2% accuracy.