Reduction of tobacco smoke components yield in commercial cigarette brands by addition of HUSY, NaY and Al-MCM-41 to the cigarette rod

The effect of two zeolites, HUSY, NaY and a mesoporous synthesized Al-MCM-41 material on the smoke composition of ten commercial cigarettes brands has been studied. Cigarettes were prepared by mixing the tobacco with the three powdered materials, and the smoke obtained under the ISO conditions was analyzed. Up to 32 compounds were identified and quantified in the gas fraction and 80 in the total particulate matter (TPM) condensed in the cigarettes filters and in the traps located after the mouth end of the cigarettes. Al-MCM-41 is by far the best additive, providing the highest reductions of the yield for most compounds and brands analyzed. A positive correlation was observed among the TPM and nicotine yields with the reduction obtained in nicotine, CO, and most compounds with the three additives. The amount of ashes in additive free basis increases due to the coke deposited on the solids, especially with Al-MCM-41. Nicotine is reduced with Al-MCM-41 by an average of 34.4% for the brands studied (49.5% for the brand where the major reduction was obtained and 18.5 for the brand behaving the worst). CO is reduced by an average of 18.6% (ranging from 10.3 to 35.2% in the different brands).

Functionalization of carbon nanotubes using aminobenzene acids and electrochemical methods. Electroactivity for the oxygen reduction reaction

Functionalized carbon nanotubes (CNTs) using three aminobenzene acids with different functional groups (carboxylic, sulphonic, phosphonic) in para position have been synthesized through potentiodynamic treatment in acid media under oxidative conditions. A noticeable increase in the capacitance for the functionalized carbon nanotubes mainly due to redox processes points out the formation of an electroactive polymer thin film on the CNTs surface along with covalently bonded functionalities. The CNTs functionalized using aminobenzoic acid rendered the highest capacitance values and surface nitrogen content, while the presence of sulfur and/or phosphorus groups in the aminobenzene structure yielded a lower functionalization degree. The oxygen reduction reaction (ORR) activity of the functionalized samples was similar to that of the parent CNTs, independently of the functional group present in the aminobenzene acid. Interestingly, a heat treatment in N2 atmosphere with a very low O2 concentration (3125 ppm) at 800 °C of the CNTs functionalized with aminobenzoic acid produced a material with high amounts of surface oxygen and nitrogen groups (12 and 4% at., respectively), that seem to modulate the electron-donor properties of the resulting material. The onset potential and limiting current for ORR was enhanced for this material. These are promising results that validates the use of electrochemistry for the synthesis of novel N-doped electrocatalysts for ORR in combination with adequate heat treatments.

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.

Synthesis of palladium nanoparticles over graphite oxide and carbon nanotubes by reduction in ethylene glycol and their catalytic performance on the chemoselective hydrogenation of para-chloronitrobenzene

Pd nanoparticles have been synthesized over carbon nanotubes (CNT) and graphite oxide (GO) by reduction with ethylene glycol and by conventional impregnation method. The catalysts were tested on the chemoselective hydrogenation of p-chloronitrobenzene and the effect of the synthesis method and surface chemistry on their catalytic performance was evaluated. The catalysts were characterized by N2 adsorption/desorption isotherms at 77 K, TEM, powder X-ray diffraction, thermogravimetry, infrared and X-ray photoelectron spectroscopy and ICP-OES. It was observed that the synthesis of Pd nanoparticles employing ethylene glycol resulted in metallic palladium particles of smaller size compared to those prepared by the impregnation method and similar for both supports. The presence of oxygen groups on the support surface favored the activity and diminished the selectivity. It seems that ethylene glycol reacted with the surface groups of GO, this favoring the selectivity. The activity was higher over the CNT-based catalysts and both catalysts prepared by reduction in ethylene glycol were quite stable upon recycling.