Methanol Conversion to Hydrocarbons (MTH) Over H-ITQ-13 (ITH) Zeolite

Product flexibility is key to meeting fluctuating chemicals demands in the future. In this contribution, the methanol to hydrocarbons (MTH) reaction was investigated over two Ge-containing H-ITQ-13 samples, one with needle-like (H-ITQ-13(N), with (Si+Ge)/Al) = 42) and another with plate-like (H-ITQ-13(P), with (Si+Ge)/Al > 100) morphology. The samples were characterised using XRD, BET, SEM/EDS and FTIR spectroscopy, and their MTH performance was compared with the performance of H-ZSM-5 and H-ZSM-22. Similar specific surface areas (413 and 455 m² g^?1 for H-ITQ-13(N) and (P), respectively) and similar acid strength (Δν ~ ?327(?310) cm^?1) was observed for the two H-ITQ-13 samples. Testing of H-ITQ-13(N) at weight hourly space velocity (WHSV) = 2–8 h^?1 at 350–450 °C revealed that C₅₊ alkenes were the main products (35–45 % selectivity at 400 °C), followed by propene and butene. A low but significant selectivity for aromatic products was observed (6–8 % selectivity at 400 °C). Product selectivity was found to be independent of deactivation. The methanol conversion capacity of H-ITQ-13(N) was 120–150 g methanol g^?1 catalyst at 400 °C. Testing H-ITQ-13 at high (30 atm) and ambient pressure, respectively, at 350 °C showed that a high pressure led to enhanced C₅₊ selectivity, but close to a tenfold decrease in methanol conversion capacity. H-ITQ-13(P) was tested at 400 °C and 2 h^?1. It gave lower conversion than H-ITQ-13(N). Furthermore, when compared at the same conversion level, H-ITQ-13(P) gave higher C₅₊ alkene selectivity, lower aromatics selectivity, and a higher propene to ethene ratio than H-ITQ-13(N). The H-ITQ-13 samples yielded a product spectrum intermediate of H-ZSM-22 and H-ZSM-5. The effluent product cut-off of H-ITQ-13 was similar to that of H-ZSM-5 with tetramethylbenzene as the largest significant product, while H-ZSM-22 produced mainly linear and branched alkenes. The lifetime of H-ITQ-13(N) was clearly enhanced compared to H-ZSM-22, but inferior to H-ZSM-5.     

Viscosity virtual sensor to control combustion in fossil fuel power plants

Thermo-electrical power plants utilize fossil fuel oil to transform the calorific power of fuel into electric power. An optimal combustion in the boiler requires the fuel oil to be in its best conditions. One of fuel's most important properties to consider is viscosity. Viscosity has influence on the optimal combustion between fuel and air. Hardware viscosity meters for fuel oils are expensive and unreliable to operate in power plant conditions. Chemical laboratory measures viscosity accurately with special apparatus, but they cannot be used in a real time process. This paper describes the development of a virtual sensor that estimates fuel oil viscosity in the combustion process of a power plant. A virtual sensor or soft sensor is a computer program that estimates the value of a certain variable based on related measurements and a model of the process where the variable participates. In this project, a probabilistic model is constructed using automatic learning algorithms with historical data and experts' advice. The learning and validation experiments are described and discussed. The virtual sensor is installed in the Tuxpan Power Plant in Veracruz, Mexico.     

Optimization of Sesame Oil Extraction by Screw-Pressing at Low Temperature

Box-Behnken designs were used to optimize a process for sesame oil extraction by screw-pressing at low temperature (50 °C). Experimental designs included seed moisture content (SMC), pressing speed (PS), and restriction die (RD) as the main processing parameters. Extractions at pilot plant scale showed a peak in oil recovery (OR, 71.1 ± 2.80%) at 12.3% SMC, 4 mm RD, and 20 rpm PS. Theoretical models were scanned against experimental data in order to scale up the proposed oil extraction process to industrial scale. A fitted model for OR showed a maximum predicted value similar to the highest experimental value (74.4 ± 1.23%) under the following conditions: 8.03% SMC, 10 mm RD, and 20 rpm PS. Chemical quality parameters of oils obtained at both pilot and industrial scales were in the ranges stated in Codex (FAO/WHO) standards for non-refined sesame oil.     

User encoding for clustering in very sparse recommender systems tasks

Multimedia Tools and Applications - Recommender Systems are a very useful tool which let companies and service providers focus in the preferences of their customers, helping them to avoid an...     

Molecular Recognition in C-Type Lectins: The Cases of DC-SIGN,Langerin, MGL,and L-Sectin

Carbohydrates play a pivotal role in intercellular communication processes. In particular, glycan antigens are key for sustaining homeostasis, helping leukocytes to distinguish damaged tissues and invading pathogens from healthy tissues. From a structural perspective, this cross-talk is fairly complex, and multiple membrane proteins guide these recognition processes, including lectins and Toll-like receptors. Since the beginning of this century, lectins have become potential targets for therapeutics for controlling and/or avoiding the progression of pathologies derived from an incorrect immune outcome, including infectious processes, cancer, or autoimmune diseases. Therefore, a detailed knowledge of these receptors is mandatory for the development of specific treatments. In this review, we summarize the current knowledge about four key C-type lectins whose importance has been steadily growing in recent years, focusing in particular on how glycan recognition takes place at the molecular level, but also looking at recent progresses in the quest for therapeutics.