Hexavalent chromium Cr(VI) is a highly toxic groundwater contaminant. In this study, we demonstrate a selective electrochemical process tailored for removal of Cr(VI) using a hybrid MOF@rGO nanomaterial synthesized by in situ growth of a nanocrystalline, mixed ligand octahedral metal−organic framework with cobalt metal centers, [Co 2 (btec)-(bipy)(DMF) 2 ] n (Co-MOF), on the surface of reduced graphene oxide (rGO). The rGO provides the electric conductivity necessary for an electrode, while the Co-MOF endows highly selective adsorption sites for CrO 4 2− . When used as an anode in the treatment cycles, the MOF@rGO electrode exhibits strong selectivity for adsorption of CrO 4 2− over competing anions including Cl − , SO 4 2− , and As(III) and achieves charge efficiency (CE) >100% due to the strong physisorption of CrO 4 2− by Co-MOF; both electro-and physisorption capacities are regenerated with the reversal of the applied voltage, when highly toxic Cr(VI) is reduced to less toxic reduced Cr species and subsequently released into brine. This approach allows easy regeneration of the nonconducting Co-MOF without any chemical addition while simultaneously transforming Cr(VI), inspiring a novel electrochemical method for highly selective degradation of toxic contaminants using tailor-designed electrodes with high affinity adsorbents.

This paper presents the simulation environment for the EIDOS (EquIpment Destined for Orientation and Safety) architecture applied to wildfire fighting operations. The development of this environment involves a multidisciplinary study, in which we have to handle several different types of information (geographical data, vegetation models, fire models, etc.) and devices (sensors, aerial vehicles, and mobile devices). Therefore, the simulation tool is actually composed of several independent and interconnected modules. Motivation and scopeForest fires represent one of the main causes of environmental degradation in many countries. Moreover, very often the people working directly on their extinction and residing in the area affected by the fire is in serious danger. With the final goal of reducing the risk to which these people are exposed, and increasing the efficacy of wildfire fighting operations, recently we have proposed the EIDOS system [4]. This architecture is based on the use of a WSN (wireless sensor network), which is deployed over the area affected by the fire, and is able to provide the fire-fighters with critical information in real time, contributing to increment their safety.Several recent works propose using WSNs for firefighting. As an example, FireNet [2] focuses on fire rescue in urban areas. In this proposal, each fire-fighter carries a Crossbow Mica2/MicaZ [1] (attached with a sensor board), that is able to sense data and forward packets to the sink node (located in the incident commander vehicle). Another representative proposal may be FireWxNet [7], which presents a complex tiered architecture for wildfire environments. In almost all these proposals, the purpose of the sensor network consists in just acquiring environmental data. Then, this information is gathered in a central server (for example a PC), where it is displayed, stored in a database, processed, used as input for some fire prediction software, or sent to a remote location.However, in the EIDOS system, the information collected by the network is processed by the sensors themselves in a collaborative way, with the aim of obtaining information about the localization of the active fire fronts and their evolution along the time. Finally, the result of this processing can be transmitted either to the people working in fighting operations (equipped with mobile devices), or to a base station.Although we plan to build a real prototype bringing together the subsystems we are designing, the initial phase of the EIDOS development will be carried out over a simulation environment. This platform will allow us to analyze and refine the behavior of our proposals. In this paper, we provide a description of this simulation environment.Next, the architecture and functionality of the EIDOS system are introduced. Then, an outlook of the simulator tool is presented, and the modules composing it are detailed. Finally, some conclusions are given, and future work is proposed. EIDOS system ArchitectureAt a glance, the EIDOS system consists of three types ...

Device localization or positioning is a key issue in wireless sensor networks applications. One solution widely used to estimate the position of a node in the network consists in using the intersection of coverage areas. For the sake of simplicity, these areas have traditionally been modeled by rectangles, assuming some extra inaccuracy. In this paper we propose a localization algorithm based on hexagonal intersection. Results show that the only substitution of the geometric shape provides better results in the localization of the devices composing the network.

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