XANES speciation of mercury in three mining districts – Almadén,Asturias (Spain), Idria (Slovenia)

The mobility, bioavailability and toxicity of mercury in the environment strongly depend on the chemical species in which it is present in soil, sediments, water or air. In mining districts, differences in mobility and bioavailability of mercury mainly arise from the different type of mineralization and ore processing. In this work, synchrotron‐based X‐ray absorption near‐edge spectroscopy (XANES) has been taken advantage of to study the speciation of mercury in geological samples from three of the largest European mercury mining districts: Almadén (Spain), Idria (Slovenia) and Asturias (Spain). XANES has been complemented with a single extraction protocol for the determination of Hg mobility. Ore, calcines, dump material, soil, sediment and suspended particles from the three sites have been considered in the study. In the three sites, rather insoluble sulfide compounds (cinnabar and metacinnabar) were found to predominate. Minor amounts of more soluble mercury compounds (chlorides and sulfates) were also identified in some samples. Single extraction procedures have put forward a strong dependence of the mobility with the concentration of chlorides and sulfates. Differences in efficiency of roasting furnaces from the three sites have been found.     

Time shift correction in second-order liquid chromatographic data with iterative target transformation factor analysis

When the generalized rank annihilation method (GRAM) is applied to liquid chromatographic data with diode-array detection, an important problem is the time shift of the peak of the analyte in the test sample. This problem leads to erroneous predictions. This time shift can be corrected if a time window is selected so that the chromatographic profile of the analyte in the test sample is trilinear with the peak of the analyte in the calibration sample. In this paper we present a new method to determine when this condition is met. This method is based on the curve resolution with iterative target transformation factor analysis (ITTFA). The calibration and test matrices are independently decomposed into profiles and spectra, and aligned before GRAM is applied. Here we study two situations: first, when the calibration matrix has one analyte and second, when it has two analytes. When the calibration matrix has two analytes, we selectively determine the time window for the analyte to be quantified. There were considerably fewer prediction errors after correction.     

Unveiling the relevance of the redox character of nitroaromatic and nitroheteroaromatic compounds as potential medicines

This review discusses the state of the art, challenges, and perspectives in recent applications of nitroaromatics and nitroheteroaromatics, which are redox-bio-activated drugs or leads, in Medicinal Chemistry. It deals mainly with the electrochemical approach toward the electron transfer-based molecular mechanisms of drug action, drug design, estimation and measurement of redox potentials, correlation of physicochemical and pharmacological data, and electrochemical studies of the main representatives of nitro-containing prodrugs, along with approaches to combat their toxicity issues, aiming at a better therapeutic profile. Electrochemical investigation plays essential roles, being strategic in the design and discovery of potential medicines.     

Relation between morphology and conductivity in TiO2 nanotube arrays: an electrochemical impedance spectrometric investigation

Two types of TiO₂ nanotubular arrays were obtained by anodisation of a titanium foil, in two different solutions containing fluoride ions. For the first type which has rough tube walls, impedance measurements in the dark showed the presence of a localised surface state which was related to adsorbed molecular water. Under UV illumination, this adsorbed molecular water was photo-dissociated. Moreover, an increase of 2 orders of magnitude for the limiting capacitance of the space charge layer was observed, simultaneously with the disappearance of the localised state and with a 100-time increase of the carrier density associated with hydrogen insertion. The second type of layer was characterised by smoother tube walls, a high doping level (10²⁰?cm^?3) in the dark, a lack of localised states and no long-lasting photo-induced effect. In this case, the width of the space charge layer became rapidly higher than the half-thickness of the tube walls, when the applied potential increased. Therefore, the walls were progressively depleted under anodic polarisation, passing from a situation where the tubes were totally active in the cathodic range towards a situation where the contribution of the tube walls could be neglected.     

Effect of non-significant proportional bias in the final measurement uncertainty

The trueness of an analytical method can be assessed by calculating the proportional bias of the method in terms of apparent recovery. If the apparent recovery does not differ significantly from one, the analytical method has not a significant bias. If this is the case, the bias is neglected and the uncertainty associated with this bias is included in the uncertainty budget of results. However, when assessing trueness there is always a probability of incorrectly concluding that the proportional bias is not significant. Therefore, the uncertainty of results may be underestimated. In this paper, we study how non-significant bias affects the uncertainty of analytical results. Moreover, we study how to avoid the underestimation of uncertainty by including the non-significant bias calculated in the uncertainty budget. To answer these questions, we have used the Monte-Carlo method to simulate the process of estimating the apparent recovery of a biased analytical method and, subsequently, the future results this method provides. The results of the simulation show that non-significant bias may underestimate the uncertainty of analytical results when bias contributes in more than 20% to the overall uncertainty. Uncertainty is specially underestimated when bias contributes in more than 50% to the overall uncertainty.