Karine L. Marques

Application of quantum dots as analytical tools in automated chemical analysis: A review

Colloidal semiconductor nanocrystals or quantum dots (QDs) are one of the most relevant developments in the fast-growing world of nanotechnology. Initially proposed as luminescent biological labels, they are finding new important fields of application in analytical chemistry, where their photoluminescent properties have been exploited in environmental monitoring, pharmaceutical and clinical analysis and food quality control. Despite the enormous variety of applications that have been developed, the automation of QDs-based analytical methodologies by resorting to automation tools such as continuous flow analysis and related techniques, which would allow to take advantage of particular features of the nanocrystals such as the versatile surface chemistry and ligand binding ability, the aptitude to generate reactive species, the possibility of encapsulation in different materials while retaining native luminescence providing the means for the implementation of renewable chemosensors or even the utilisation of more drastic and even stability impairing reaction conditions, is hitherto very limited. In this review, we provide insights into the analytical potential of quantum dots focusing on prospects of their utilisation in automated flow-based and flow-related approaches and the future outlook of QDs applications in chemical analysis.

A multi-pumping flow system for chemiluminescent determination of ammonium in natural waters

A multi-pumping flow system with improved mixing conditions is proposed for chemiluminescent determination of ammonium in natural waters. The system includes a gas-diffusion unit, a Y-connector made of sintered glass particles (100–200 mesh), and a chemiluminometric detector. System configuration, flow rates, reagent concentrations, pH, and reactor lengths were optimized. The analytical curve is linear from 0.3 to 5.0 mg L−1 N-NH4, and the detection limit is estimated as 0.02 mg L−1 at the 99.7% confidence level. The system handles about 50 samples per hour, requires 3.1 µg of active chlorine and 0.11 mg of luminol per determination, and yields precise results (RSD<1.2%, n = 10) in agreement with those obtained by the spectrophotometric indophenol blue method.

Chemiluminometric evaluation of melatonin and selected melatonin precursors’ interaction with reactive oxygen and nitrogen species

Melatonin is a hormone, a derivative of tryptophan, that possesses a potent scavenging capacity for the most reactive and dangerous free radicals, being an important protection against oxidative stress. In this work, an automated flow-based procedure for assessment of melatonin, tryptophan, and 5-hydroxytryptophan scavenging capacity was developed. The presented methodology involved a multi-pumping flow system and exploited the ability of selected compounds to inhibit the chemiluminescence reaction of luminol with hydrogen peroxide, hydroxyl radical, and peroxynitrite anion. The system was based on the use of several solenoid actuated micro-pumps as the only active components of the flow manifold. This enabled the reproducible insertion and efficient mixing of very low volumes of sample and reagents as well as the transportation of the sample zone toward detection for monitoring the chemiluminometric response. Furthermore, the high versatility of the proposed multi-pumping flow system allowed the implementation of distinct reactions for the in-line generation of the different reactive species assayed without requiring physical reconfiguration. The results obtained demonstrated that 5-hydroxytryptophan is the most potent scavenger, followed by melatonin and tryptophan. The developed multi-pumping flow system exhibited good measurement precision (relative standard deviations typically <2%, n=10), low operational costs, and low reagent consumption.

Application of Pulsed Flow Analysis for Chemiluminescent Screening of Fluoxetine Counterfeit Pharmaceuticals

Abstract A chemiluminometric methodology for fluoxetine determination based on its antioxidant scavenger effect on the fast chemiluminescence reaction between luminol and hypochlorite, is proposed. The developed procedure was implemented in a fully automated multi‐pumping flow system, combining the excellent mixing characteristics of the pulsed flow with chemiluminescence detection, resulting on a sensitive, simple, and fast procedure for fluoxetine determination in pharmaceutical formulations. Linear calibration plots for fluoxetine hydrochloride concentrations of up to 10 mg l−1 (r=0.9995, n=7) were obtained, with an r.s.d<2% (n=10). Detection limit (3 σ) was 0.31 mg l−1 and the sampling rate was about 136 determinations per h.

Ciprofloxacin and Norfloxacin Spectrophotometric Determination in a Fully Automated Multi-Pumping Flow System

A flow-based methodology for the spectrophotometric determination of ciprofloxacin and norfloxacin, based on the oxidation with N-bromosuccinimide in acidic medium, was developed. The proposed procedure was implemented in a multi-pumping flow system, which provided excellent mixing conditions due to the pulsed flow produced by solenoid micro-pumps actuation, resulting on a sensitive, simple, fast, and versatile analytical method. Linear calibration plots were obtained for ciprofloxacin and norfloxacin concentrations ranging from 5 to 70 mg L−1 with an R.S.D < 2.2% (n = 10). Detection limits (3σ) were 0.27 mg L−1 and 0.99 mg L−1 for norfloxacin and ciprofloxacin, respectively.

Determination of phenylglyoxylic acid in urine using a multi-pumping flow system

In this work a simple, fast and fully automated analytical methodology for the spectrophotometric determination of phenylglyoxylic acid is proposed. Phenylglyoxylic acid is a metabolite of styrene that is excreted in urine, being used as an indicator of styrene occupational exposure. The developed procedure was based on the phenylglyoxylic acid ability to inhibit the formation of the peroxovanadium cation produced by the reaction between vanadate and H2O2. The analytical process was implemented in a multi-pumping flow system that employs multiple solenoid actuated micro-pumps as the only active components. This enabled the reproducible insertion and efficient mixing of low volumes of sample and reagents as well as the transportation of the sample zone towards detection. Thus an easily controlled, low cost, compact and reliable analytical system was implemented. A linear working range for phenylglyoxylic acid concentrations up to 700 mg L−1 (r 2 = 0.995, n = 7), was obtained, with a detection limit of 37 mg L−1. The system handles about 43 determinations per hour yielding precise results (relative standard deviation < 5%, n = 10). The developed methodology was applied to the determination of phenylglyoxylic acid in urine samples and the obtained results were in agreement with those furnished by the comparison method with relative percentage deviations lower than 6.6%.

Mathematical modeling of dispersion in single interface flow analysis.

This work describes the optimization of the recently proposed fluid management methodology single interface flow analysis (SIFA) using chemometrics modelling. The influence of the most important physical and hydrodynamic flow parameters of SIFA systems on the axial dispersion coefficients estimated with the axially dispersed plug-flow model, was evaluated with chemometrics linear (multivariate linear regression) and non-linear (simple multiplicative and feed-forward neural networks) models. A D-optimal experimental design built with three reaction coil properties (length, configuration and internal diameter), flow-cell volume and flow rate, was adopted to generate the experimental data. Bromocresol green was used as the dye solution and the analytical signals were monitored by spectrophotometric detection at 614 nm. Results demonstrate that, independent of the model type, the statistically relevant parameters were the reactor coil length and internal diameter and the flow rate. The linear and non-linear multiplicative models were able to estimate the axial dispersion coefficient with validation r(2)=0.86. Artificial neural networks estimated the same parameter with an increased accuracy (r(2)=0.93), demonstrating that relations between the physical parameters and the dispersion phenomena are highly non-linear. The analysis of the response surface control charts simulated with the developed models allowed the interpretation of the relationships between the physical parameters and the dispersion processes.