CuxSnSx+1 (x = 2, 3) thin films grown by sulfurization of metallic precursors deposited by dc magnetron sputtering

We report the results of the growth of Cu-Sn-S ternary chalcogenide compounds by sulfurization of dc magnetron sputtered metallic precursors. Tetragonal Cu2SnS3 forms for a maximum sulfurization temperature of 350 ºC. Cubic Cu2SnS3 is obtained at sulfurization temperatures above 400 ºC. These results are supported by XRD analysis and Raman spectroscopy measurements. The latter analysis shows peaks at 336 cm-1, 351 cm-1 for tetragonal Cu2SnS3, and 303 cm-1, 355 cm-1 for cubic Cu2SnS3. Optical analysis shows that this phase change lowers the band gap from 1.35 eV to 0.98 eV. At higher sulfurization temperatures increased loss of Sn is expected in the sulphide form. As a consequence, higher Cu content ternary compounds like Cu3SnS4 grow. In these conditions, XRD and Raman analysis only detected orthorhombic (Pmn21) phase (petrukite). This compound has Raman peaks at 318 cm-1, 348 cm-1 and 295 cm-1. For a sulfurization temperature of 450 ºC the samples present a multi-phase structure mainly composed by cubic Cu2SnS3 and orthorhombic (Pmn21) Cu3SnS4. For higher temperatures, the samples are single phase and constituted by orthorhombic (Pmn21) Cu3SnS4. Transmittance and reflectance measurements were used to estimate a band gap of 1.60 eV. For comparison we also include the results for Cu2ZnSnS4 obtained using similar growth conditions.

Study of polycrystalline Cu2ZnSnS4 films by Raman scattering

Cu2ZnSnS4 (CZTS) is a p-type semiconductor that has been seen as a possible low-cost replacement for Cu(In,Ga)Se2 in thin film solar cells. So far compound has presented difficulties in its growth, mainly, because of the formation of secondary phases like ZnS, CuxSnSx+1, SnxSy, Cu2−xS and MoS2. X-ray diffraction analysis (XRD), which is mostly used for phase identification cannot resolve some of these phases from the kesterite/stannite CZTS and thus the use of a complementary technique is needed. Raman scattering analysis can help distinguishing these phases not only laterally but also in depth. Knowing the absorption coefficient and using different excitation wavelengths in Raman scattering analysis, one is capable of profiling the different phases present in multi-phase CZTS thin films. This work describes in a concise form the methods used to grow chalcogenide compounds, such as, CZTS, CuxSnSx+1, SnxSy and cubic ZnS based on the sulphurization of stacked metallic precursors. The results of the films’ characterization by XRD, electron backscatter diffraction and scanning electron microscopy/energy dispersive spectroscopy techniques are presented for the CZTS phase. The limitation of XRD to identify some of the possible phases that can remain after the sulphurization process are investigated. The results of the Raman analysis of the phases formed in this growth method and the advantage of using this technique in identifying them are presented. Using different excitation wavelengths it is also analysed the CZTS film in depth showing that this technique can be used as non destructive methods to detect secondary phases.

A multidimensional scaling analysis of musical sounds based on pseudo phase plane

This paper studies musical opus from the point of view of three mathematical tools: entropy, pseudo phase plane (PPP), and multidimensional scaling (MDS). The experiments analyze ten sets of different musical styles. First, for each musical composition, the PPP is produced using the time series lags captured by the average mutual information. Second, to unravel hidden relationships between the musical styles the MDS technique is used. The MDS is calculated based on two alternative metrics obtained from the PPP, namely, the average mutual information and the fractal dimension. The results reveal significant differences in the musical styles, demonstrating the feasibility of the proposed strategy and motivating further developments towards a dynamical analysis of musical sounds.

Multi-criteria design optimization study of solvent extraction in mixer–settler units

Solvent extraction is considered as a multi-criteria optimization problem, since several chemical species with similar extraction kinetic properties are frequently present in the aqueous phase and the selective extraction is not practicable. This optimization, applied to mixer–settler units, considers the best parameters and operating conditions, as well as the best structure or process flow-sheet. Global process optimization is performed for a specific flow-sheet and a comparison of Pareto curves for different flow-sheets is made. The positive weight sum approach linked to the sequential quadratic programming method is used to obtain the Pareto set. In all investigated structures, recovery increases with hold-up, residence time and agitation speed, while the purity has an opposite behaviour. For the same treatment capacity, counter-current arrangements are shown to promote recovery without significant impairment in purity. Recycling the aqueous phase is shown to be irrelevant, but organic recycling with as many stages as economically feasible clearly improves the design criteria and reduces the most efficient organic flow-rate.

Multiresidue pesticides analysis in soils using modified QuEChERS with disposable pipette extraction and dispersive solid-phase extraction

QuEChERS original method was modified into a new version for pesticides determination in soils. The QuEChERS method is based on liquid–liquid portioning with ACN and was followed by cleanup step using dispersive SPE and disposable pipette tips. Gas chromatographic separation with MS detection was carried out for pesticides quantification. The method was validated using recovery experiments for 36 multiclass pesticides. Mean recoveries of pesticides at each of the four spiking levels between 10–300 µg/kg of soil ranged from 70–120% for 26 pesticides with RSD values less than 15%. The method achieved low limit of detection less than 7.6 µ g/kg. Matrix effects were observed for 13 pesticides. Matrix effects were compensated by using matrix-matched calibration. The method was applied successfully using d-SPE or DPX in the analysis of the pesticides in soils from organic farming and integrated pest management.

Energy-conscious tasks partitioning onto a heterogeneous multi-core platform

Modern multicore processors for the embedded market are often heterogeneous in nature. One feature often available are multiple sleep states with varying transition cost for entering and leaving said sleep states. This research effort explores the energy efficient task-mapping on such a heterogeneous multicore platform to reduce overall energy consumption of the system. This is performed in the context of a partitioned scheduling approach and a very realistic power model, which improves over some of the simplifying assumptions often made in the state-of-the-art. The developed heuristic consists of two phases, in the first phase, tasks are allocated to minimise their active energy consumption, while the second phase trades off a higher active energy consumption for an increased ability to exploit savings through more efficient sleep states. Extensive simulations demonstrate the effectiveness of the approach.

Multi-criteria optimization manipulator trajectory planning

In the last twenty years genetic algorithms (GAs) were applied in a plethora of fields such as: control, system identification, robotics, planning and scheduling, image processing, and pattern and speech recognition (Bäck et al., 1997). In robotics the problems of trajectory planning, collision avoidance and manipulator structure design considering a single criteria has been solved using several techniques (Alander, 2003). Most engineering applications require the optimization of several criteria simultaneously. Often the problems are complex, include discrete and continuous variables and there is no prior knowledge about the search space. These kind of problems are very more complex, since they consider multiple design criteria simultaneously within the optimization procedure. This is known as a multi-criteria (or multiobjective) optimization, that has been addressed successfully through GAs (Deb, 2001). The overall aim of multi-criteria evolutionary algorithms is to achieve a set of non-dominated optimal solutions known as Pareto front. At the end of the optimization procedure, instead of a single optimal (or near optimal) solution, the decision maker can select a solution from the Pareto front. Some of the key issues in multi-criteria GAs are: i) the number of objectives, ii) to obtain a Pareto front as wide as possible and iii) to achieve a Pareto front uniformly spread. Indeed, multi-objective techniques using GAs have been increasing in relevance as a research area. In 1989, Goldberg suggested the use of a GA to solve multi-objective problems and since then other researchers have been developing new methods, such as the multi-objective genetic algorithm (MOGA) (Fonseca & Fleming, 1995), the non-dominated sorted genetic algorithm (NSGA) (Deb, 2001), and the niched Pareto genetic algorithm (NPGA) (Horn et al., 1994), among several other variants (Coello, 1998). In this work the trajectory planning problem considers: i) robots with 2 and 3 degrees of freedom (dof ), ii) the inclusion of obstacles in the workspace and iii) up to five criteria that are used to qualify the evolving trajectory, namely the: joint traveling distance, joint velocity, end effector / Cartesian distance, end effector / Cartesian velocity and energy involved. These criteria are used to minimize the joint and end effector traveled distance, trajectory ripple and energy required by the manipulator to reach at destination point. Bearing this ideas in mind, the paper addresses the planning of robot trajectories, meaning the development of an algorithm to find a continuous motion that takes the manipulator from a given starting configuration up to a desired end position without colliding with any obstacle in the workspace. The chapter is organized as follows. Section 2 describes the trajectory planning and several approaches proposed in the literature. Section 3 formulates the problem, namely the representation adopted to solve the trajectory planning and the objectives considered in the optimization. Section 4 studies the algorithm convergence. Section 5 studies a 2R manipulator (i.e., a robot with two rotational joints/links) when the optimization trajectory considers two and five objectives. Sections 6 and 7 show the results for the 3R redundant manipulator with five goals and for other complementary experiments are described, respectively. Finally, section 8 draws the main conclusions.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

A framework for memory contention analysis in multi-core platforms

The last decade has witnessed a major shift towards the deployment of embedded applications on multi-core platforms. However, real-time applications have not been able to fully benefit from this transition, as the computational gains offered by multi-cores are often offset by performance degradation due to shared resources, such as main memory. To efficiently use multi-core platforms for real-time systems, it is hence essential to tightly bound the interference when accessing shared resources. Although there has been much recent work in this area, a remaining key problem is to address the diversity of memory arbiters in the analysis to make it applicable to a wide range of systems. This work handles diverse arbiters by proposing a general framework to compute the maximum interference caused by the shared memory bus and its impact on the execution time of the tasks running on the cores, considering different bus arbiters. Our novel approach clearly demarcates the arbiter-dependent and independent stages in the analysis of these upper bounds. The arbiter-dependent phase takes the arbiter and the task memory-traffic pattern as inputs and produces a model of the availability of the bus to a given task. Then, based on the availability of the bus, the arbiter-independent phase determines the worst-case request-release scenario that maximizes the interference experienced by the tasks due to the contention for the bus. We show that the framework addresses the diversity problem by applying it to a memory bus shared by a fixed-priority arbiter, a time-division multiplexing (TDM) arbiter, and an unspecified work-conserving arbiter using applications from the MediaBench test suite. We also experimentally evaluate the quality of the analysis by comparison with a state-of-the-art TDM analysis approach and consistently showing a considerable reduction in maximum interference.

Serpentine bacteria influence metal translocation and bioconcentration of Brassica juncea and Ricinus communis grown in multi-metal polluted soils

The aim of this study was to assess the effects of inoculation of rhizosphere or endophytic bacteria (Psychrobacter sp. SRS8 and Pseudomonas sp. A3R3, respectively) isolated from a serpentine environment on the plant growth and the translocation and accumulation of Ni, Zn, and Fe by Brassica juncea and Ricinus communis on a multi-metal polluted serpentine soil (SS). Field collected SS was diluted to 0, 25, 50, and 75% with pristine soil in order to obtain a range of heavy metal concentrations and used in microcosm experiments. Regardless of inoculation with bacteria, the biomass of both plant species decreased with increase of the proportion of SS. Inoculation of plants with bacteria significantly increased the plant biomass and the heavy metal accumulation compared with non-inoculated control in the presence of different proportion of SS, which was attributed to the production of plant growth promoting and/or metal mobilizing metabolites by bacteria. However, SRS8 showed a maximum increase in the biomass of the test plants grown even in the treatment of 75% SS. In turn, A3R3 showed maximum effects on the accumulation of heavy metals in both plants. Regardless of inoculation of bacteria and proportion of SS, both plant species exhibited low values of bioconcentration factor (<1) for Ni and Fe. The inoculation of both bacterial strains significantly increased the translocation factor (TF) of Ni while decreasing the TF of Zn in both plant species. Besides this contrasting effect, the TFs of all metals were <1, indicating that all studied bacteria–plant combinations are suitable for phytostabilization. This study demonstrates that the bacterial isolates A3R3 and SRS8 improved the growth of B. juncea and R. communis in SS soils and have a great potential to be used as inoculants in phytostabilization scenarios of multi-metal contaminated soils.

Quasi-periodic Gaits in Multi-legged Robots

5th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines

Energy analysis of Multi-legged Locomotion Systems

4th International Conference on Climbing and Walking Robots - From Biology to Industrial Applications

Decentralized Target Tracking based on Multi-Robot Cooperative Triangulation

Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

Simulation Environment for Multi-Robot Cooperative 3D Target Perception

4th International Conference, SIMPAR 2014, Bergamo, Italy, October 20-23, 2014