Complex numbers-partial least-squares applied to the treatment of electrochemical impedance spectroscopy data

Engineering boron and nitrogen codoped carbon nanoarchitectures to tailor molecularly imprinted polymers for PFOS determination

Per- and polyfluoroalkyl substances (PFAS) have gained significant attention as emerging contaminants due to their persistence, abundance, and adverse health effects. Consequently, the urgent need for ubiquitous and effective sensors capable of detecting and quantifying PFAS in complex environmental samples has become a priority. In this study, we present the development of an ultrasensitive molecularly imprinted polymer (MIP) electrochemical sensor tailored by chemically vapour-deposited boron and nitrogen codoped diamond-rich carbon nanoarchitectures for the selective determination of perfluorooctanesulfonic acid (PFOS). This approach allows for a multiscale reduction of MIP heterogeneities, leading to improved selectivity and sensitivity in PFOS detection. Interestingly, the peculiar carbon nanostructures induce a specific distribution of binding sites in the MIPs that exhibit a strong affinity for PFOS. The designed sensors demonstrated a low limit of detection (1.2 μg L^-1) and exhibited satisfactory selectivity and stability. To gain further insights into the molecular interactions between diamond-rich carbon surfaces, electropolymerised MIP, and the PFOS analyte, a set of density functional theory (DFT) calculations was performed. Validation of the sensor's performance was carried out by successfully determining PFOS concentrations in real complex samples, such as tap water and treated wastewater, with average recovery rates consistent with UHPLC-MS/MS results. These findings demonstrate the potential of MIP-supported diamond-rich carbon nanoarchitectures for water pollution monitoring, specifically targeting emerging contaminants. The proposed sensor design holds promise for the development of in situ PFOS monitoring devices operating under relevant environmental concentrations and conditions.

Three-dimensional voltammetry: Use of chronoamperometric E-t-i data to achieve second-order advantage

This work studied the use of three-dimensional voltammetry, particularly potential-time-current (E-t-i) data, on the development of electroanalytical methods. E-t-i data was obtained by taking chronoamperograms at potentials applied as pulses on a staircase waveform. By using this three-way kind of data and appropriate calibration algorithms, the possibility of achieving the second-order advantage was evaluated in the determination of ferrocyanide in the presence of the uncalibrated interference hydroquinone as a model system. The determination of acetaminophen in urine samples, where ascorbic acid and uric acid play the major roles as interferents was also studied. Parallel factor analysis (PARAFAC) and multivariate curve resolution alternating least-squares (MCR-ALS) were the algorithms employed in this work. Both algorithms successfully achieved the second-order advantage by correctly predicting the concentrations of the validation synthetic samples. Excellent predictions were obtained in the direct analysis of acetaminophen-spiked urine samples by E-t-i data and MCR-ALS.