Screen-printed electrode based electrochemical detector coupled with ionic liquid dispersive liquid–liquid microextraction and microvolume back-extraction for determination of mercury in water samples

A novel approach is presented, whereby gold nanostructured screen-printed carbon electrodes (SPCnAuEs) are combined with in-situ ionic liquid formation dispersive liquid–liquid microextraction (in-situ IL-DLLME) and microvolume back-extraction for the determination of mercury in water samples. In-situ IL-DLLME is based on a simple metathesis reaction between a water-miscible IL and a salt to form a water-immiscible IL into sample solution. Mercury complex with ammonium pyrrolidinedithiocarbamate is extracted from sample solution into the water-immiscible IL formed in-situ. Then, an ultrasound-assisted procedure is employed to back-extract the mercury into 10 µL of a 4 M HCl aqueous solution, which is finally analyzed using SPCnAuEs. Sample preparation methodology was optimized using a multivariate optimization strategy. Under optimized conditions, a linear range between 0.5 and 10 µg L−1 was obtained with a correlation coefficient of 0.997 for six calibration points. The limit of detection obtained was 0.2 µg L−1, which is lower than the threshold value established by the Environmental Protection Agency and European Union (i.e., 2 µg L−1 and 1 µg L−1, respectively). The repeatability of the proposed method was evaluated at two different spiking levels (3 and 10 µg L−1) and a coefficient of variation of 13% was obtained in both cases. The performance of the proposed methodology was evaluated in real-world water samples including tap water, bottled water, river water and industrial wastewater. Relative recoveries between 95% and 108% were obtained.

Design of Activated Carbon/Activated Carbon Asymmetric Capacitors

Supercapacitors are energy storage devices that offer a high power density and a low energy density in comparison with batteries. Their limited energy density can be overcome by using asymmetric configuration in mass electrodes, where each electrode works within their maximum available potential window, rendering the maximum voltage output of the system. Such asymmetric capacitors are optimized using the capacitance and the potential stability limits of the electrodes, with the reliability of the design largely depending on the accuracy and the approach taken for the electrochemical characterization. Therefore, the performance could be lower than expected and even the system could break down, if a well thought out procedure is not followed. In this work, a procedure for the development of asymmetric supercapacitors based on activated carbons is detailed. Three activated carbon materials with different textural properties and surface chemistry have been systematically characterized in neutral aqueous electrolyte. The asymmetric configuration of the masses of both electrodes in the supercapacitor has allowed to cover a higher potential window, resulting in an increase of the energy density of the three devices studied when compared with the symmetric systems, and an improved cycle life.

An optimized pseudorandom generator using packed matrices

Most cryptographic services and information security protocols require a dependable source of random data; pseudorandom generators are convenient and efficient for this application working as one of the basic foundation blocks on which to build the required security infrastructure. We propose a modification of a previously published matricial pseudorandom generator that significantly improves performance and security by using word packed matrices and modifying key scheduling and bit extraction schemes. The resulting generator is then successfully compared to world class standards.

Optimal synthesis of thermally coupled distillation sequences using a novel MILP approach

This paper introduces a novel MILP approach for the design of distillation columns sequences of zeotropic mixtures that explicitly include from conventional to fully thermally coupled sequences and divided wall columns with a single wall. The model is based on the use of two superstructure levels. In the upper level a superstructure that includes all the basic sequences of separation tasks is postulated. The lower level is an extended tree that explicitly includes different thermal states and compositions of the feed to a given separation task. In that way, it is possible to a priori optimize all the possible separation tasks involved in the superstructure. A set of logical relationships relates the feasible sequences with the optimized tasks in the extended tree resulting in a MILP to select the optimal sequence. The performance of the model in terms of robustness and computational time is illustrated with several examples.

Photocatalytic oxidation of propene in gas phase at low concentration by optimized TiO2 nanoparticles

In the present study, nanocrystalline titanium dioxide (TiO2) was prepared by sol–gel method at low temperature from titanium tetraisopropoxide (TTIP) and characterized by different techniques (gas adsorption, XRD, TEM and FTIR). Variables of the synthesis, such as the hydrolyzing agent (acetic acid or isopropanol) and calcination temperatures (300–800 °C), were analyzed to get uniform size TiO2 nanoparticles. The effect that these two variables have on the structure of the resultant TiO2 nanoparticles and on their photocatalytic activity is investigated. The photocatalytic activities of TiO2 nanoparticles were evaluated for propene oxidation at low concentration (100 ppmv) under two different kinds of UV light (UV-A ∼ 365 nm and UV-C ∼ 257.7 nm) and compared with Degussa TiO2 P-25, used as reference sample. The results show that both hydrolyzing agents allow to prepare TiO2 nanoparticles and that the hydrolyzing agent influences the crystalline structure and its change with the thermal treatments. Interestingly, the prepared TiO2 nanoparticles possess anatase phase with small crystalline size, high surface area and higher photocatalytic activity for propene oxidation than commercial TiO2 (Degussa P-25) under UV-light. Curiously, these prepared TiO2 nanoparticles are more active with the 365 nm source than with the 257.7 nm UV-light, which is a remarkable advantage from an application point of view. Additionally, the obtained results are particularly good when acetic acid is the hydrolyzing agent at both wavelengths used, possibly due to the high crystallinity, low anatase phase size and high surface oxygen groups’ content in the nanoparticles prepared with it, in comparison to those prepared using isopropanol.

Towards a real-time 3D object recognition pipeline on mobile GPGPU computing platforms using low-cost RGB-D sensors

In this project, we propose the implementation of a 3D object recognition system which will be optimized to operate under demanding time constraints. The system must be robust so that objects can be recognized properly in poor light conditions and cluttered scenes with significant levels of occlusion. An important requirement must be met: the system must exhibit a reasonable performance running on a low power consumption mobile GPU computing platform (NVIDIA Jetson TK1) so that it can be integrated in mobile robotics systems, ambient intelligence or ambient assisted living applications. The acquisition system is based on the use of color and depth (RGB-D) data streams provided by low-cost 3D sensors like Microsoft Kinect or PrimeSense Carmine. The range of algorithms and applications to be implemented and integrated will be quite broad, ranging from the acquisition, outlier removal or filtering of the input data and the segmentation or characterization of regions of interest in the scene to the very object recognition and pose estimation. Furthermore, in order to validate the proposed system, we will create a 3D object dataset. It will be composed by a set of 3D models, reconstructed from common household objects, as well as a handful of test scenes in which those objects appear. The scenes will be characterized by different levels of occlusion, diverse distances from the elements to the sensor and variations on the pose of the target objects. The creation of this dataset implies the additional development of 3D data acquisition and 3D object reconstruction applications. The resulting system has many possible applications, ranging from mobile robot navigation and semantic scene labeling to human-computer interaction (HCI) systems based on visual information.

Successful functionalization of superporous zeolite templated carbon using aminobenzene acids and electrochemical methods

A novel and selective electrochemical functionalization of a highly reactive superporous zeolite templated carbon (ZTC) with two different aminobenzene acids (2-aminobenzoic and 4-aminobenzoic acid) was achieved. The functionalization was done through potentiodynamic treatment in acid media under oxidative conditions, which were optimized to preserve the unique ZTC structure. Interestingly, it was possible to avoid the electrochemical oxidation of the highly reactive ZTC structure by controlling the potential limit of the potentiodynamic experiment in presence of aminobenzene acids. The electrochemical characterization demonstrated the formation of polymer chains along with covalently bonded functionalities to the ZTC surface. The functionalized ZTCs showed several redox processes, producing a capacitance increase in both basic and acid media. The rate performance showed that the capacitance increase is retained at scan rates as high as 100 mV s−1, indicating that there is a fast charge transfer between the polymer chains formed inside the ZTC porosity or the new surface functionalities and the ZTC itself. The success of the proposed approach was also confirmed by using other characterization techniques, which confirmed the presence of different nitrogen groups in the ZTC surface. This promising method could be used to achieve highly selective functionalization of highly porous carbon materials.