INVESTIGADORES
LEDESMA Brenda Cecilia Soledad
congresos y reuniones científicas
Título:
Experimental Desing Optimization of the Tetralin Hydrogenation over Pt-Ir/SBA-15.
Autor/es:
VERÓNICA VALLÉS; BRENDA LEDESMA; LORENA RIVOIRA; JORGELINA CUSSA; OSCAR ANUNZIATA; ANDREA BELTRAMONE
Lugar:
Cuernavaca
Reunión:
Congreso; International Symposium on Advances in Hydroprocessing of Oil Fractions (ISAHOF 2015); 2015
Institución organizadora:
Mexican Institute of Petroleum, Mexico
Resumen:
The oil refining industry has a difficult challenge to meet the increasingly stringent regulations on environmental issues. Contaminants such as sulfur, nitrogen, fused ring aromatic com-pounds or metals are the principal to remove to achieve "green" fuels. The hydrotreating (HDT) is one of the processes most used in the refinery to remove these contaminants. To op-timize the gas oil hydrotreater, it is crucial to understand the aromatic hydrogenation reaction chemistry occurring in the gas oil hydrotreater. To find alternative processes, it is necessary to develop new and more active catalysts to replace the current ones. Bimetallic Pt?Pd catalysts have received considerable attention, because they show high actvity in a variety of catalytic applications [1,2]. From a fundamental point of view, exploring bimetallic catalysts also allows better understanding of mechanisms and variables involved in the catalytic reactions. The fea-tures of the catalysts here studied are going to be correlated with their catalytic performance in the hydrogenation of tetralin. The final goal is to find the optimal proportion of each metal in order to be more active and the best reaction conditions. The statistical experiments design is the process of planning an experiment to obtain appropriate data that can be analyzed by statistical methods, to produce concrete and valid conclusions [3]. One of the main advan-tages in the response curve is to visualize the response for all levels of the experimental factors Experiment design response surface methodology (RSM) is used in this work to model and to optimize the process.