Three-way catalysts: past, present and future

In this article, the past and the state-of-the-art in Three-Way Catalyst (TWC) technology are reviewed. The main chemical reactions occurring in a gasoline engine are discussed and also the main reactions taking place in a TWC placed in the tailpipe, namely CO and hydrocarbons oxidation and nitrogen oxides reduction to molecular nitrogen. The main components of a TWC (substrates, noble metals and cerium oxides) and their role in the different chemical reactions occurring in a TWC are described. Finally, the problem of diesel vehicles gas aftertratment is described, and the current state-of-the art in catalytic converters for these vehicles are commented.

Atmospheric PM and volatile organic compounds released from Mediterranean shrubland wildfires

Wildfires produce a significant release of gases and particles affecting climate and air quality. In the Mediterranean region, shrublands significantly contribute to burned areas and may show specific emission profiles. Our objective was to depict and quantify the primary-derived aerosols and precursors of secondary particulate species released during shrubland experimental fires, in which fire-line intensity values were equivalent to those of moderate shrubland wildfires, by using a number of different methodologies for the characterization of organic and inorganic compounds in both gas-phase and particulate-phase. Emissions of PM mass, particle number concentrations and organic and inorganic PMx components during flaming and smouldering phases were characterized in a field shrubland fire experiment. Our results revealed a clear prevalence of K+ and SO42- as inorganic ions released during the flaming-smouldering processes, accounting for 68 to 80% of the inorganic soluble fraction. During the residual-smouldering phases, in addition to K+ and SO42-, Ca2+ was found in significant amounts probably due the predominance of re-suspension processes (ashes and soil dust) over other emission sources during this stage. Concerning organic markers, the chromatograms were dominated by phenols, n-alkanals and n-alkanones, as well as by alcohol biomarkers in all the PMx fractions investigated. Levoglucosan was the most abundant degradation compound with maximum emission factors between 182 and 261 mg kg-1 in PM2.5 and PM10 respectively. However, levoglucosan was also observed in significant amounts in the gas-phase. The most representative organic volatile constituents in the smoke samples were alcohols, carbonyls, acids, monocyclic and bicyclic arenes, isoprenoids and alkanes compounds. The emission factors obtained in this study may contribute to the validation and improvement of national and international emission inventories of this intricate and diffuse emission source.

A Comparative Study of Registration Methods for RGB-D Video of Static Scenes

The use of RGB-D sensors for mapping and recognition tasks in robotics or, in general, for virtual reconstruction has increased in recent years. The key aspect of these kinds of sensors is that they provide both depth and color information using the same device. In this paper, we present a comparative analysis of the most important methods used in the literature for the registration of subsequent RGB-D video frames in static scenarios. The analysis begins by explaining the characteristics of the registration problem, dividing it into two representative applications: scene modeling and object reconstruction. Then, a detailed experimentation is carried out to determine the behavior of the different methods depending on the application. For both applications, we used standard datasets and a new one built for object reconstruction.

Behavior of different soot combustion catalysts under NOx/O2. Importance of the catalyst–soot contact

Four different catalysts (Pt/Al2O3, Ce0.8Zr0.2O2, PrO2−x and SrTiCuO3) have been investigated on a laboratory scale to evaluate their potential as diesel soot combustion catalysts under different experimental conditions, which simulate the situation found in a continuous regeneration technology trap (dual-bed configuration of catalyst and soot) or a catalyst-coated filter system (single-bed configuration, both catalyst and soot particles mixed under loose-contact mode). Under dual-bed configuration, the behavior of the catalysts towards soot combustion are very similar, despite the differences observed in the NO2 production profiles. However, under single-bed configuration, there are important differences in the soot combustion activities and in the NO2 slip profiles. The configurations chosen have an enormous impact on CO/(CO + CO2) ratios of combustion products as well. The most active catalyst under NOx + O2 is PrO2−x combining a high contribution of active oxygen-assisted soot combustion as well as high NO2 production activity along the catalytic bed.

Evaluation of hectorites, synthesized in different conditions, as soot combustion catalysts after impregnation with copper

Two microporous hectorites were prepared by conventional and microwave heating, and a delaminated mesoporous hectorite by an ultrasound-assisted synthesis. These three hectorites were impregnated with copper. The characterization techniques used were XRD, N2 adsorption, TEM and H2 reduction after selective surface copper oxidation by N2O (to determine copper dispersion). The catalytic activity for soot combustion of the copper-free and the copper-containing hectorites was tested under a gas mixture of 500 ppm NOx/5% O2/N2 (and 5% O2/N2 in some cases), evaluating their stability through three consecutive soot combustion experiments. The delaminated hectorite showed the highest surface area (353 m2/g) allowing the highest dispersion of copper. This copper-containing catalyst was the most active for soot combustion among those prepared and tested in this study. We have also concluded that the Cu/hectorite-catalyzed soot combustion mechanism is based on the activation of the O2 molecule and not on the NO2-assisted soot combustion.

Isotopic study of ceria-catalyzed soot oxidation in the presence of NOx

The ceria-catalyzed soot oxidation mechanism has been studied by a pulse technique with labeled O2 in the absence and presence of NO, using ceria–soot mixtures prepared in the loose contact mode. In the absence of soot, the ceria-catalyzed oxidation of NO to NO2 takes place with ceria oxygen and not with gas-phase O2. However, the oxygen exchange process between gas-phase O2 and ceria oxygen (to yield back O2, but with oxygen atoms coming from ceria) prevailed with regard to the ceria-catalyzed oxidation of NO to NO2. Gas-phase O2 did not react directly with soot when pulsed to a soot–ceria loose contact mixture. Instead, ceria oxygen is transferred to soot (this step does not require gas-phase molecular oxygen to be present), and gas-phase O2 fills up the vacancies created on the oxide in a further step. The transfer of oxygen between ceria and soot occurred directly in the absence of NO. However, in the presence of NO, NO2 is expected to be additionally generated by ceria oxygen oxidation, which also reacts with soot. The main reaction products of the ceria-catalyzed soot oxidation reaction with NO/O2 were CO2 and NO. Additionally, evidence of the reduction of NOx to N2 was found.

Evidences of the Cerium Oxide-Catalysed DPF Regeneration in a Real Diesel Engine Exhaust

The active phase Ce0.5Pr0.5O2 has been loaded on commercial substrates (SiC DPF and cordierite honeycomb monolith) to perform DPF regeneration experiments in the exhaust of a diesel engine. Also, a powder sample has been prepared to carry out soot combustion experiments at laboratory. Experiments performed in the real diesel exhaust demonstrated the catalytic activity of the Ce–Pr mixed oxide for the combustion of soot, lowering the DPF regeneration temperature with regard to a counterpart catalyst-free DPF. The temperature for active regeneration of the Ce0.5Pr0.5O2-containing DPF when the soot content is low is in the range of 500–550 °C. When the Ce0.5Pr0.5O2-containing DPF is saturated with a high amount of soot, pressure drop and soot load at the filter reach equilibrium at around 360 °C under steady state engine operation due to passive regeneration. The uncoated DPF reached this equilibrium at around 440 °C. Comparing results at real exhaust with those at laboratory allow concluding that the Ce0.5Pr0.5O2-catalysed soot combustion in the real exhaust is not based on the NO2-assisted mechanism but is most likely occurring by the active oxygen-based mechanism.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Human Behaviour Recognition based on Trajectory Analysis using Neural Networks

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.

A Novel Prediction Method for Early Recognition of Global Human Behaviour in Image Sequences

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied from a prediction point of view. We propose a novel method able to early detect behaviour using a small portion of the input, in addition to the capabilities of it to predict behaviour from new inputs. Specifically, we propose a predictive method based on a simple representation of trajectories of a person in the scene which allows a high level understanding of the global human behaviour. The representation of the trajectory is used as a descriptor of the activity of the individual. The descriptors are used as a cue of a classification stage for pattern recognition purposes. Classifiers are trained using the trajectory representation of the complete sequence. However, partial sequences are processed to evaluate the early prediction capabilities having a specific observation time of the scene. The experiments have been carried out using the three different dataset of the CAVIAR database taken into account the behaviour of an individual. Additionally, different classic classifiers have been used for experimentation in order to evaluate the robustness of the proposal. Results confirm the high accuracy of the proposal on the early recognition of people behaviours.

Evaluation of sampling method effects in 3D non-rigid registration

Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.

Constrained self-organizing feature map to preserve feature extraction topology

In many classification problems, it is necessary to consider the specific location of an n-dimensional space from which features have been calculated. For example, considering the location of features extracted from specific areas of a two-dimensional space, as an image, could improve the understanding of a scene for a video surveillance system. In the same way, the same features extracted from different locations could mean different actions for a 3D HCI system. In this paper, we present a self-organizing feature map able to preserve the topology of locations of an n-dimensional space in which the vector of features have been extracted. The main contribution is to implicitly preserving the topology of the original space because considering the locations of the extracted features and their topology could ease the solution to certain problems. Specifically, the paper proposes the n-dimensional constrained self-organizing map preserving the input topology (nD-SOM-PINT). Features in adjacent areas of the n-dimensional space, used to extract the feature vectors, are explicitly in adjacent areas of the nD-SOM-PINT constraining the neural network structure and learning. As a study case, the neural network has been instantiate to represent and classify features as trajectories extracted from a sequence of images into a high level of semantic understanding. Experiments have been thoroughly carried out using the CAVIAR datasets (Corridor, Frontal and Inria) taken into account the global behaviour of an individual in order to validate the ability to preserve the topology of the two-dimensional space to obtain high-performance classification for trajectory classification in contrast of non-considering the location of features. Moreover, a brief example has been included to focus on validate the nD-SOM-PINT proposal in other domain than the individual trajectory. Results confirm the high accuracy of the nD-SOM-PINT outperforming previous methods aimed to classify the same datasets.

La nostalgia en la poesía de Andrés Neuman

Este Trabajo de Fin de Grado que pretendemos defender pretende analizar la poesía del escritor argentino Andrés Neuman, con el fin de demostrar que uno de sus temas reincidentes es el de la nostalgia. Para ello, hemos hecho una distinción de las distintas nostalgias que podemos llegar a encontrar, como son la nostalgia por Argentina, la nostalgia amorosa y, finalmente, la nostalgia por aquello que no ha ocurrido. Asimismo, este trabajo contiene una breve bio-bibliografía del autor, así como la explicación del tema escogido y una breve presentación de las obras que nos han servido para el análisis: Década de poesía 1997-2007 y No sé por qué y Patio de locos, con la finalidad de presentar y dar a conocer de manera general la poesía del autor. Como colofón del trabajo realizado se exponen las conclusiones obtenidas, y a continuación se recoge la bibliografía utilizada. Finalmente, cuenta con un anexo en el que recogemos todos aquellos poemas que hemos utilizado en el trabajo.

Active oxygen by Ce–Pr mixed oxide nanoparticles outperform diesel soot combustion Pt catalysts

A Ce0.5Pr0.5O2 mixed oxide has been prepared with the highest surface area and smallest particle size ever reported (125 m2/g and 7 nm, respectively), also being the most active diesel soot combustion catalyst ever tested under realistic conditions if catalysts forming highly volatile species are ruled out. This Ce–Pr mixed oxide is even more active than a reference platinum-based commercial catalyst. This study provides an example of the efficient participation of oxygen species released by a ceria catalyst in a heterogeneous catalysis reaction where both the catalyst and one of the reactants (soot) are solids. It has been concluded that both the ceria-based catalyst composition (nature and amount of dopant) and the particle size play key roles in the combustion of soot through the active oxygen-based mechanism. The composition determines the production of active oxygen and the particle size the transfer of such active oxygen species from catalyst to soot.