Elemental Anisotropic Growth and Atomic-Scale Structure of Shape-Controlled Octahedral Pt–Ni–Co Alloy Nanocatalysts

Multimetallic shape-controlled nanoparticles offer great opportunities to tune the activity, selectivity, and stability of electrocatalytic surface reactions. However, in many cases, our synthetic control over particle size, composition, and shape is limited requiring trial and error. Deeper atomic-scale insight in the particle formation process would enable more rational syntheses. Here we exemplify this using a family of trimetallic PtNiCo nanooctahedra obtained via a low-temperature, surfactant-free solvothermal synthesis. We analyze the competition between Ni and Co precursors under coreduction “one-step” conditions when the Ni reduction rates prevailed. To tune the Co reduction rate and final content, we develop a “two-step” route and track the evolution of the composition and morphology of the particles at the atomic scale. To achieve this, scanning transmission electron microscopy and energy dispersive X-ray elemental mapping techniques are used. We provide evidence of a heterogeneous element distribution caused by element-specific anisotropic growth and create octahedral nanoparticles with tailored atomic composition like Pt1.5M, PtM, and PtM1.5 (M = Ni + Co). These trimetallic electrocatalysts have been tested toward the oxygen reduction reaction (ORR), showing a greatly enhanced mass activity related to commercial Pt/C and less activity loss than binary PtNi and PtCo after 4000 potential cycles.

A methodology for evacuation route planning inside buildings using geospatial technology

Evacuation route planning is a fundamental task for building engineering projects. Safety regulations are established so that all occupants are driven on time out of a building to a secure place when faced with an emergency situation. As an example, Spanish building code requires the planning of evacuation routes on large and, usually, public buildings. Engineers often plan these routes on single building projects, repeatedly assigning clusters of rooms to each emergency exit in a trial-and-error process. But problems may arise for a building complex where distribution and use changes make visual analysis cumbersome and sometimes unfeasible. This problem could be solved by using well-known spatial analysis techniques, implemented as a specialized software able to partially emulate engineer reasoning. In this paper we propose and test an easily reproducible methodology that makes use of free and open source software components for solving a case study. We ran a complete test on a building floor at the University of Alicante (Spain). This institution offers a web service (WFS) that allows retrieval of 2D geometries from any building within its campus. We demonstrate how geospatial technologies and computational geometry algorithms can be used for automating the creation and optimization of evacuation routes. In our case study, the engineers’ task is to verify that the load capacity of each emergency exit does not exceed the standards specified by Spain’s current regulations. Using Dijkstra’s algorithm, we obtain the shortest paths from every room to the most appropriate emergency exit. Once these paths are calculated, engineers can run simulations and validate, based on path statistics, different cluster configurations. Techniques and tools applied in this research would be helpful in the design and risk management phases of any complex building project.

Lecciones aprendidas gamificando cuando aún no se llamaba gamificación

El término gamificación está de moda. Los gurús la sitúan como una tecnología emergente y disruptiva, que cambiará muchas de nuestras experiencias en campos tan alejados de los juegos como el empresarial, el marketing y la relación con los clientes. Y el entorno educativo no escapará a ello. En este artículo presentamos la experiencia de un grupo de profesores preocupados por la docencia, que llevamos años experimentando con los videojuegos y las experiencias lúdicas, y que de repente nos hemos encontrado con el término gamificación. Estas son las lecciones que hemos aprendido, que podemos enmarcar en el campo de la gamificación en educación, pero que derivan de una experiencia práctica, de un análisis desmenuzado y de una reflexión concienzuda. Pretendemos mostrar qué es lo realmente importante y qué puntos debemos tener en cuenta los profesores antes de lanzarnos al diseño gamificado de nuestra propuesta docente.

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.

Parametrized Architecture for Hough Transform Recursive Evaluation

Paper submitted to International Workshop on Spectral Methods and Multirate Signal Processing (SMMSP), Barcelona, España, 2003.