João T.V. Matos

Trends in data processing of comprehensive two-dimensional chromatography: State of the art☆

The operation of advanced chromatographic systems, namely comprehensive two-dimensional (2D) chromatography coupled to multidimensional detectors, allows achieving a great deal of data that need special care to be processed in order to characterize and quantify as much as possible the analytes under study. The aim of this review is to identify the main trends, research needs and gaps on the techniques for data processing of multidimensional data sets obtained from comprehensive 2D chromatography. The following topics have been identified as the most promising for new developments in the near future: data acquisition and handling, peak detection and quantification, measurement of overlapping of 2D peaks, and data analysis software for 2D chromatography. The rational supporting most of the data processing techniques is based on the generalization of one-dimensional (1D) chromatography although algorithms, such as the inverted watershed algorithm, use the 2D chromatographic data as such. However, for processing more complex N-way data there is a need for using more sophisticated techniques. Apart from using other concepts from 1D chromatography, which have not been tested for 2D chromatography, there is still room for new improvements and developments in algorithms and software for dealing with 2D comprehensive chromatographic data.

A 802.11p prototype implementation

This paper presents an IEEE 802.11p full-stack prototype implementation to data exchange among vehicles and between vehicles and the roadway infrastructures. The prototype architecture is based on FPGAs for Intermediate Frequency (IF) and base band purposes, using 802.11a based transceivers for RF interfaces. Power amplifiers were also addressed, by using commercial and in-house solutions. This implementation aims to provide technical solutions for Intelligent Transportation Systems (ITS) field, namely for tolling and traffic management related services, in order to promote safety, mobility and driving comfort through the dynamic and real-time cooperation among vehicles and/or between vehicles and infrastructures. The performance of the proposed scheme is tested under realistic urban and suburban driving conditions. Preliminary results are promising, since they comply with most of the 802.11p standard requirements.

A new chromatographic response function for assessing the separation quality in comprehensive two-dimensional liquid chromatography.

A new chromatographic response function (CRF(2D)) is proposed and tested for the estimation of the quality index of separation in comprehensive two-dimensional liquid chromatography (2D-LC) of complex organic mixtures. This objective function is based on the concept of peak purity for one-dimensional liquid chromatography, which has been redefined for 2D-LC. The new CRF(2D) also includes other separation quality criteria, namely the number of 2D peaks appearing in the chromatogram and the analysis time. To compute the peak purity for a given 2D peak, three important steps have been tackled in this study: (a) the development of an alternative algorithm for detecting 2D peaks automatically from real experimental 2D-LC data; (b) the application of a mathematical model to fit the obtained chromatographic data; and (c) the estimation of the volume of the overlapping region between two or more 2D peaks. The performance of the developed CRF(2D) was compared to that of an existing resolution measure, using simulated chromatograms. The capability of the new function to qualify the overall separation degree that it is attained under different chromatographic conditions was further assessed through a 2D-LC study of a mixture of four aromatic compounds.

Environmental Assessment of the Caveira Abandoned Mine (Southern Portugal): Part 1: Characterization of Metal Contaminated Soil

Mine activity in Portugal had a huge impact on the growth of the regions where it took place, like in the Iberian Pyrite Belt. Nowadays, most of these mines are abandoned, as is the case for the Caveira mine. Soil geochemistry indicates that high contents of Cu, Pb, Zn, As, Cd, and Hg occur in the soils collected near the tailings. Multiple Correspondence Analysis identifies two areas with high concentrations of Pb, As, Hg, Sb, Mo, and Tl. However, the results suggest a different geochemistry for each of the areas. The non-site-specific methods (Hazard Index and GLC guidelines) classify all the areas as contaminated. Metal fractionation in the soil phases is different for the several elements studied. The articulation of the metal fractionation results with the GLC guidelines reduces the area of soil contaminated by Pb, but not by As.

Profiling Water-Soluble Organic Matter from Urban Aerosols Using Comprehensive Two-Dimensional Liquid Chromatography

Comprehensive two-dimensional liquid chromatography (LC×LC) coupled with a diode array detector (DAD) has been used for the first time to investigate chemical heterogeneity and map the hydrophobicity versus molecular weight distribution of the most hydrophobic acid fractions in water-soluble organic matter (WSOM) from fine atmospheric aerosols collected over different seasons at a urban location. The use of LC×LC–DAD, combining the use of two independent separation mechanisms (per aqueous liquid chromatography [PALC] versus size-exclusion chromatography [SEC]), has shown a great potential for unraveling and resolving the heterogeneity of WSOM, further providing a deeper insight into how size-distinguished aerosol WSOM fractions differ in hydrophobicity during different seasonal events. The combination of PALC×SEC–DAD data with an already proposed data treatment procedure revealed that the WSOM samples collected during warm seasons are enriched in aliphatic structures, while those collected during colder seasons exhibit a higher degree of structures with conjugation of π-bonds (e.g., aromatics) alongside aliphatic structures. Copyright 2015 American Association for Aerosol Research

A simple approach to reduce dimensionality from comprehensive two-dimensional liquid chromatography coupled with a multichannel detector.

Comprehensive two-dimensional liquid chromatographic (LC×LC) systems play an ever increasing role in separation and characterization of complex samples. When coupled with multichannel detectors, such as the diode array detector, these LC×LC systems become especially useful for non-target analysis and identification of patterns based on the information extracted from those complex samples. Nevertheless, due to the large amount of data generated by these systems, the extraction of useful information for the identification of patterns still is one of the major drawbacks for a wider application of this technique. As a preliminary step in data treatment, we have developed a simple and fast way to deal with this large amount of multi-dimensional data by identifying the three-dimensional (3D) regional maxima of each chromatographic peak generated in a LC×LC-DAD system: retention times at the peak maximum in the first- and second-dimensions and the wavelength of the maximum UV absorption. This dataset is then used to build a 3D fingerprinting of the given sample, which alongside the 3D fingerprinting of other samples, can be used to identify different patterns associated with the specific properties of every sample under study. The applicability of the developed methodology was further assessed by performing a non-target LC×LC-DAD analysis of four Portuguese red wine samples.

Two chemically distinct light-absorbing pools of urban organic aerosols: A comprehensive multidimensional analysis of trends.

The chemical and light-absorption dynamics of organic aerosols (OAs), a master variable in the atmosphere, have yet to be resolved. This study uses a comprehensive multidimensional analysis approach for exploiting simultaneously the compositional changes over a molecular size continuum and associated light-absorption (ultraviolet absorbance and fluorescence) properties of two chemically distinct pools of urban OAs chromophores. Up to 45% of aerosol organic carbon (OC) is soluble in water and consists of a complex mixture of fluorescent and UV-absorbing constituents, with diverse relative abundances, hydrophobic, and molecular weight (Mw) characteristics between warm and cold periods. In contrast, the refractory alkaline-soluble OC pool (up to 18%) is represented along a similar Mw and light-absorption continuum throughout the different seasons. Results suggest that these alkaline-soluble chromophores may actually originate from primary OAs sources in the urban site. This work shows that the comprehensive multidimensional analysis method is a powerful and complementary tool for the characterization of OAs fractions. The great diversity in the chemical composition and optical properties of OAs chromophores, including both water-soluble and alkaline-soluble OC, may be an important contribution to explain the contrasting photo-reactivity and atmospheric behavior of OAs.

Organic Pollutants in Soils

The occurrence and fate of organic pollutants (OPs) in soils have been the subject of intensive research for many years, mostly due to the urgent need to answer the challenge of better managing soils quality. The purpose of this review is to provide a brief account on the sources and pathways of OPs in soils, their implication in soil pollution, and the effect of soil composition, particularly the importance of carbonaceous geosorbents (i.e., soil organic matter and black carbon), in limiting organic pollution in soils. This chapter also reviews the most relevant fit-for-purpose analytical strategies for determining OPs and their transformation products in soils. The principal aim of this review is to provide the soil research community with insights into the key issues and important analytical resources that can be used advantageously for investigating OPs in soils.

Compact Multilayer Yagi-Uda Based Antenna for IoT/5G Sensors

To increase the capacity and performance of communication systems, the new generation of mobile communications (5G) will use frequency bands in the mmWave region, where new challenges arise. These challenges can be partially overcome by using higher gain antennas, Multiple-Input Multiple-Output (MIMO), or beamforming techniques. Yagi-Uda antennas combine high gain with low cost and reduced size, and might result in compact and efficient antennas to be used in Internet of Thins (IoT) sensors. The design of a compact multilayer Yagi for IoT sensors is presented, operating at 24 GHz, and a comparative analysis with a planar printed version is shown. The stacked prototype reveals an improvement of the antenna’s main properties, achieving 10.9 dBi, 2 dBi more than the planar structure. In addition, the multilayer antenna shows larger bandwidth than the planar; 6.9 GHz compared with 4.42 GHz. The analysis conducted acknowledges the huge potential of these stacked structures for IoT applications, as an alternative to planar implementations.