Abstract: The illicit drug precursor market for the manufacture of amphetamine-type stimulants (ATS), mainly amphetamine, methamphetamine and methylenedioxymethamphetamine (MDMA), has emerged quickly in the last years. The evidence of a more complex and sophisticated drug market underlines the pressing need for new on-site methods to quickly detect precursors of synthetic drugs, with electrochemical analysis as a promising technique. Herein, the electrochemical fingerprints of ten common ATS precursors-3-oxo-2-phenylbutanenitrile (APAAN), 3-oxo-2-phenylbutanamide (APAA), methyl 3-oxo-2-phenylbutanoate (MAPA), benzyl methyl ketone (BMK), 1-(1,3-benzodioxol-5-yl)propan-2-one (PMK), ephedrine, pseudoephedrine, safrole, sassafras oil and piperonal- are reported for the first time. The electrochemical screening disclosed the redox inactivity of BMK, which is an essential starting material for the production of ATS. Therefore, the local derivatization of BMK at an electrode surface by reductive amination is presented as a feasible solution to enrich its electrochemical fingerprint. To prove that, the resulting mixture was analyzed using a set of chromatographic techniques to understand the reaction mechanism and to identify possible electrochemical active products. Two reaction products (i.e. methamphetamine and 1-phenylpropan-2-ol) were found and characterized using mass spectrometry and electrochemical methods. Subsequently, the optimization of the reaction parameters was carefully addressed to set the portable electrochemical sensing strategy. Ultimately, the analysis concept was validated for the qualitative identification of ATS precursors in seizures from a forensic institute. Overall, the electrochemical approach demonstrates to be a useful and affordable analytical tool for the early identification of ATS precursors to prevent trafficking and drug manufacture in clandestine laboratories.

Abstract: To overcome limiting anammox activity under sewage treatment conditions, a return-sludge nursery concept is proposed. This concept involves blending sludge reject water treated with partial nitritation with mainstream effluent to increase the temperature, N levels, and electrical conductivity (EC) of the anammox nursery reactor, which sludge periodically passes through the return sludge line of the mainstream system. Various nursery frequencies were tested in two 2.5 L reactors, including 0.5-2 days of nursery treatment per 3.5-14 days of the total operation. Bioreactor experiments showed that nursery increased nitrogen removal rates during mainstream operation by 33-38%. The increased anammox activity can be partly (35-60%) explained by higher temperatures. Elevated EC, higher nitrogen concentrations, and a putative synergy and/or unknown factor were responsible for 15-16%, 12-14%, and 10-36%, respectively. A relatively stable microbial community was observed, dominated by a “Candidatus Brocadia” member. This new concept boosted activity and sludge growth, which may facilitate mainstream anammox implementations based on partial nitritation/anammox or partial nitrification/denitratation/anammox.

Abstract: The goal of this study is to provide a rigorous tool to quantify the inequality of the leaf size distribution of an individual plant, thereby serving as a reference trait for quantifying plant adaptations to local environmental conditions. The tool to be presented and tested employs three components: (1) a performance equation (PE), which can produce flexible asymmetrical and symmetrical bell-shaped curves, (2) the Lorenz curve (i.e., the cumulative proportion of leaf size vs. the cumulative proportion of number of leaves), which is the basis for calculating, and (3) the Gini index, which measures the inequality of leaf size distribution. We sampled 12 individual plants of a dwarf bamboo and measured the area and dry mass of each leaf of each plant. We then developed a generalized performance equation (GPE) of which the PE is a special case and fitted the Lorenz curve to leaf size distribution using the GPE and PE. The GPE performed better than the PE in fitting the Lorenz curve. We compared the Gini index of leaf area distribution with that of leaf dry mass distribution and found that there was a significant difference between the two indices that might emerge from the scaling relationship between leaf dry mass and area. Nevertheless, there was a strong correlation between the two Gini indices (r2 = 0.9846). This study provides a promising tool based on the GPE for quantifying the inequality of leaf size distributions across individual plants and can be used to quantify plant adaptations to local environmental conditions.

Abstract: There is an urgent need for sensing strategies to screen perfluoroalkyl substances (PFAS) in aqueous matrices. These strategies must be applicable in large-scale monitoring plans to face the ubiquitous use of PFAS, their wide global spread, and their fast evolution towards short-chain, branched molecules. To this aim, the changes in fluorinated self-assembled monolayers (SAM) with different architectures (pinholes/defects-free and with randomized pinholes/defects) were studied upon exposure to both long and short-chain PFAS. The applicability of fluorinated SAM in PFAS sensing was evaluated. Changes in the SAM structures were characterised combining electrochemical impedance spectroscopy and voltam-metric techniques. The experimental data interpretation was supported by molecular dynamics simu-lations to gain a more in-depth understanding of the interaction mechanisms involved. Pinhole/defect-free fluorinated SAM were found to be applicable to long-chain PFAS screening within switch-on sensing strategy, while a switch-off sensing strategy was reported for screening of both short/long-chain PFAS. These strategies confirmed the possibility to play on fluorophilic interactions when designing PFAS screening methods.(c) 2022 Elsevier B.V. All rights reserved.

Abstract: Pretreatment is a critical step in the conversion of lignocellulose into biofuels and biochemicals. During pretreatment, the recalcitrance of lignocellulose is reduced, e.g. by removing lignin, thereby making the carbohydrates more accessible for enzymatic saccharification. Fungal delignification by white-rot fungi is a biotechnological alternative to chemical/physicochemical methods, which is carried out in solid-state fermentation with mild reaction conditions and without the formation of microbial inhibitors. However, fungal pretreatment presents some challenges, such as long pretreatment time, non-selective and low delignification, low enzymatic digestibility and feedstock sterilisation requirement, making its commercial implementation challenging compared to conventional methods. This study investigates the possibility of improving and characterising the solid-state fungal pretreatment of poplar wood by Phanerochaete chrysosporium. The individual and combined effects of MnSO4 and CuSO4 supplements on the delignification of sterilised wood are investigated using response surface methodology to improve the degree and selectivity of fungal delignification. Spore-inoculated solid-state fermentations are carried out for 4 weeks in sterile vented bottles. The mechanism of the concerted action of the metal ions on lignin degradation is then elucidated by relating fungal growth and ligninolytic enzyme activities to lignocellulose degradation as a function of pretreatment time. The optimised metal-supplemented system is then applied to the pretreatment of non-sterilised wood using different inoculation techniques (spores and pre-colonised substrate), nutrients (metal ions with or without glucose and sodium nitrate) and cultivation environments (sterile aerated bottles and open trays). The fermentations are then characterised using infrared spectroscopy, in particular NIR and ATR-FTIR spectroscopy, with the aim of developing rapid lignin quantification methods as an alternative to conventional wet chemical methods. Finally, the feasibility of producing fermentable sugars from sterilised and non-sterilised poplar wood using fungal pretreatment is evaluated through a techno-economic analysis. Supplementing the pretreatment system with 2.01 µmol CuSO4 and 0.77 µmol MnSO4 g-1 wood resulted in 1.9-fold higher lignin degradation, 2.3-fold higher delignification selectivity value and 2.9-fold higher glucose yield. The improved delignification could be explained by the concerted action of Mn2+ and Cu2+ ions, with Mn2+ ions inducing and Cu2+ prolonging manganese peroxidase production responsible for delignification. Fungal pretreatment at non-sterile conditions was obtained using trays in a simple solid-state fermentation set-up without sterile aeration. A 1:3 ratio of pre-colonised and untreated wood was applied for inoculation and only Cu2+, Mn2+ and sodium nitrate as supplements. Remarkably, this technology resulted in a comparably high glucose yield (28.51 ± 0.28%) to the traditional method using sterilised wood, sterile aeration and spores as inoculum, while reducing the amount of wood to be sterilised by 71.2%. Infrared spectroscopy-based methods with high coefficients of determination (R_CV

Abstract: This work aims to enhance the efficiency of integrated poultry waste management in bio-circular-green economy by maximizing the co-digestion of chicken manure and its digestate-grown biomass. In a series of batch assays, Napier grass (NG) was mixed with chicken manure (CM) at various proportions (100:0, 80:20, 60:40, 50:50, 40:60, 20:80 and 0:100) to identify co-substrate synergism, followed by physiochemical conditioning (size reduction and ultrasonication) of NG before co-digestion. Results indicated that NG mix of at least 80% was required to gain a full methanation potential of the individual substrates; no synergistic ratio above unity was found. However, the combined effect of size reduction and sonication was found to markedly improve the cosubstrate's biodegradability by 88.7%. The findings were then used to run continuous co-digestion at various operating regimes. In optimal continuous co-digestion condition, NG particle size of 0.6-2.4 mm combined with sonication intensity at 1111 kJ/kgTS improved biomethanation yield as high as 106.3%. Sub-thermophilic digestion at 45 degrees C was shown to give a higher and more stable CH4 yield than at 55 degrees C. Finally, it was also found that recycling liquid effluent at 40% to replace freshwater in feed, although showed no significant difference in CH4 yield (& alpha; = 0.05), noticeably increased system buffer capacity. This optimized biodegradation regime could give co-digestion waste management a higher overall plant efficiency and economic return.

Abstract: In the recent advances towards more sustainable global energy supply, H2 is a possible alternative for large scale energy storage. In this view, Liquid Organic Hydrogen Carriers (LOHC) are a class of molecules that allow for easier long term energy storage compared to conventional H2 technologies. CFD simulations were used to showcase the hydrodynamics of the dehydrogenation of a LOHC in a new reactor unit, via a cold flow mock-up study. This reactor was designed to allow for a swirling motion of the liquid carrier material, favouring the removal of H2 gas from the flow and forcing the equilibrium of the reaction towards dehydrogenation, as well as to keep the catalyst particles in motion. The CFD simulations were validated qualitatively with experimental operation of the reactor, in a system with identical dimensionless numbers (Reynolds and Stokes), in order to use less costly products during the prototyping phase.

Abstract: Pretreatment is crucial for the conversion of lignocellulose to biofuels. Unlike conventional chemical/physicochemical methods, fungal pretreatment uses white-rot fungi and mild reaction conditions. However, challenges, including substrate sterilization, long duration, and low sugar yields associated with this method, contribute to lower techno-economic performance, an aspect that has rarely been investigated. This study aimed to evaluate the feasibility of fungal pretreatment of nonsterilized poplar wood. Various factors, including inoculum types, fermentation supplements, and cultivation methods, were investigated to optimize the process. A techno-economic assessment of the optimized processes was performed at a full biorefinery scale. The scenario using nonsterilized wood as a substrate, precolonized wood as an inoculum, and a 4 week pretreatment showed a 14.5% reduction in sugar production costs (€2.15/kg) compared to using sterilized wood. Although the evaluation of nonsterilized wood pretreatment showed promising cost reductions, fungal pretreatment remained more expensive than conventional methods due to the significant capital investment required.

Abstract: Illicit drug consumption constitutes a great concern worldwide due to its increased spread and abuse, and the negative consequences exerted on society. For instance, 3,4-methylenedioxymethamphetamine (MDMA), a synthetic amphetamine-type substance, was abused by 20 million people worldwide in 2020. This psychoactive substance exerts a myriad of effects on the human body being dangerous for the consumer’s health. Besides, MDMA has been used in the treatment of some psychiatric conditions. Therefore, the development of wearable devices for MDMA sensing in biological fluids is of great importance for forensic toxicology (e.g., monitoring of patients with suspected or known MDMA consumption) as well as for therapeutic management of patients. Herein, we report the development of a wearable electrochemical platform based on a hollow microneedle (MN) array sensor for the monitoring of MDMA in the interstitial fluid by square-wave voltammetry. First, the holes of the MN array were modified with conductive pastes to devise a MN patch with a three-electrode system. Subsequently, the functionalization of the working electrode with nanomaterials enhanced MDMA detection. Thereafter, analytical parameters were evaluated exhibiting a slope of 0.05 µA µM−1 within a linear range from 1 to 50 µM and a limit of detection of 0.75 µM in artificial interstitial fluid. Importantly, critical parameters such as selectivity, piercing capability, temperature, reversibility and stability were assessed. Overall, the obtained MN sensor exhibited excellent analytical performance, making it a promising tool for MDMA tracking in interstitial fluid for individuals on probation or under therapeutic treatment.

Abstract: Exposure to air pollution, such as particulate matter (PM), causes adverse health effects, particularly to the respiratory tract and cardiovascular system. PM is the collective name for all kinds of particles ranging from small particles and liquid droplets, which contain organic compounds, acids and metals, to soil or dust particles. One distinguishes PM10, PM2.5 and PM0.1, which have aerodynamic particle sizes smaller than 10, 2.5 and 0.1 µm, respectively. It is mainly the latter that is the most harmful, as PM0.1 penetrates deep into the respiratory system and carries relatively more toxic substances than the other PM fractions. Over a 15-year period, PM concentrations in European member states have fallen by about 30%. Nevertheless, the World Health Organisation (WHO) air quality guidelines, which became stricter in 2021, are exceeded in most places around the world. Particularly in cities, excessive levels of PM are measured and it is here that PM mitigation should be investigated. For this, the implementation of urban green infrastructure, including trees, shrubs, green roofs and green walls, is being looked at. Plants hinder airflow and remove PM from the air by deposition on their leaves and branches. This process is known as dry deposition. Plants can capture PM very efficiently, due to their complex structure of leaves and branches. Green walls offer significant advantages over other types of urban green infrastructure because they can grow on the huge available wall area and, because they do not hinder air circulation, as we sometimes see with trees. Green walls are believed to have a much greater, untapped potential to reduce PM pollution. However, a literature review showed that we do not know the quantitative impact of green walls and lack the tools and/or general methodology to do so. The objective of this thesis is therefore to develop a method for assessing PM removal by green walls, based on predictive models and based on relevant parameters that are experimentally determined. Computational fluid dynamics (CFD) is a numerical method to simulate airflow in complex environments such as cities. These models can also simulate the vegetation-wind interaction in detail and are interesting tools to assess the effect of green walls on PM concentrations in real environments. It is important to first study the aerodynamic effect of green walls and parameterise it correctly in CFD models. Plants decrease the wind speed and create turbulence through a combination of viscous and form drag, which are determined by the permeability (K) and drag coefficient (Cd), respectively. Wind tunnel experiments were conducted with three commonly found climbers (Hedera helix, Parthenocissus tricuspidata and Parthenocissus quinquefolia) and the variation of leaf area density was investigated for two of them. It was observed that the air resistance depended on plant species, leaf area density and wind speed. The difference between the plant species was assigned to the functional leaf size (FLS), the ratio of the largest circle within the boundaries of the leaf to the total leaf area. FLS is likely associated with other morphological characteristics of plants that, when considered collectively, provide a more comprehensive representation of leaf complexity. The pressure and velocity measurements obtained were used to optimise the permeability and drag coefficient in a CFD model. At wind speeds below 0.6 m s-1, the resistance was mainly determined by viscous drag and a larger leaf size resulted in a higher viscous drag. At wind speeds above 1.5 m s-1, form drag was dominant and the parameterised Cd decreased with increasing wind speed due to the sheltering effect of successive plant elements. The leaf area density had a significant effect on K and Cd and, is therefore an important plant parameters in CFD models. The main conclusion here is that the common practice of using a constant Cd to model the influence of plants on the air flow leads to deviations from reality. Wind tunnels are highly suitable to study the impact of green walls on PM concentration under controlled environmental conditions. For this purpose, a new wind tunnel setup was built and great attention was paid to obtaining a uniform air flow. Thus, based on CFD models, appropriate flow controllers were chosen, consisting of honeycombs and screens with different mesh sizes. New PM generation devices and measuring equipment were installed and set up appropriately. Devices were available for generating and measuring ultrafine dust (<0.1 µm, i.e. PM0.1) and fine dust (<0.3 µm, i.e. PM0.3) consisting of soot particles, and, on the other hand, fine dust with particle sizes smaller than 2.5 (PM2.5) and 10 µm (PM10) consisting of 'Arizona fine test dust'. With the new wind tunnel setup, it was possible to measure the influence of Hedera helix (common ivy), grown in a planter against a climbing aid, on the PM concentration and this was expressed by a collection efficiency, i.e. the difference in concentration in front and behind the plants normalised for the incoming concentration. The collection efficiency of H. helix depended on the particle size of the PM and wind speed. The collection efficiency decreased when the particle size increased from 0.02 to 0.2 µm and increased again for particle sizes above 0.3 µm. The collection efficiency also increased with increasing wind speed, especially for particle sizes > 0.03 µm. On the other hand, relative humidity and the type of PM (soot or dust) did not significantly affect the collection efficiency. The main objective of this study was to obtain an optimised size-resolved deposition model. Dry deposition occurs through several mechanisms, in particular gravity, diffusion, impaction and interception, and the subsequent resuspension of deposited PM back to the environment. The modelling of these mechanisms was described by \citet{Zhang2001} and \citet{Petroff2010}. The data obtained from the wind tunnel experiments allowed validating these deposition models. It was for the first time that deposition of real PM on green walls was studied. The different PM deposition mechanisms were found to be strongly dependent on particle size and wind speed. The models of \citet{Zhang2001} and \citet{Petroff2010} each matched PM concentration measurements for only certain particle sizes. Therefore, a combination of the two models was investigated and the root mean square error was lower by on average 3.5% (PM < 0.03 µm) and 46% (PM > 0.03 µm) compared to the original models at wind speeds greater than 1.5 m s-1. For wind speeds less than 1.5 m s-1, the optimised model did not differ from the original models. The optimised model was able to meet the imposed criteria for air quality models, where a correct model exhibits low deviation from measurements ('normalised mean square error' < 1.5), low bias ('fractional bias' between -0.3 and 0.3) and high R2. In comparison, the R$2$ of the optimised model was 0.57, while that of Zhang et al. (2001) and Petroff et al. (2010) was 0.23 and 0.31, respectively. The optimised model was however characterised by a high scatter, with the fraction of modeled results located within a factor of two of the measurements being lower than 50. A model study with a green façade oriented parallel to the incoming airflow showed that deposition by interception and impaction reduced remarkably, but that the orientation had no effect on deposition by Brownian diffusion. A promising green wall form for PM mitigation is the living wall system (LWS). LWS consist of supporting structures with substrate to grow plants in and can be planted with a variety of plant species. This allows to select plant species with optimal characteristics to achieve PM deposition. These characteristics refer to the macro- and microstructure of the leaves, and research has been conducted mainly on these. On the other hand, the influence of the supporting structure and substrate on PM concentrations has rarely been studied. With the new wind tunnel setup, LWS from different manufacturers were tested for their ability to capture PM. The setups were subjected for three hours to an air flow with a low PM concentration (resuspension phase) and then for three hours to an air flow to which additional PM was added (deposition phase). Some setups were able to decrease the PM concentration during both phases, while others just caused the concentration to increase. Some systems were able to reduce particulate matter concentration during both phases, namely LWS consisting of planters (-2% and -4% for PM0.1 and PM2.5, respectively) and textile cloths (-23% and -5% for PM0.1 and PM2.5, respectively). While other systems actually resulted in an increase in concentration especially LWS existing textile fabrics consisting of geotextiles (+11% for both PM fractions) and with moss as substrate (+2% and +5% for PM0.1 and PM2.5, respectively). This highlights the importance of careful selection of suspension systems to reduce particulate matter concentrations. Further research is therefore needed on the materials used in these systems in relation to their particulate content, as well as on plant development in these systems. In addition to air measurements, measurements were taken of the amount of PM deposited on the leaves and suspension system of LWS. This allowed the difference in PM resuspension and deposition between plant species to be investigated. The amount of deposited particulate matter was determined based on 'saturation isothermal remanent magnetisation' (SIRM), a measure of magnetisable particulate matter. This was possible because the added 'Arizona fine test dust' contained iron oxide. However, no significant difference was observed between the SIRM values measured before the wind tunnel experiment, after resuspension and after deposition. This suggested that the iron oxide content in the Arizona fine test dust was too low to measure a significant difference in the SIRM values on leaves after three hours. The plant species did give rise to different SIRM values ranging between 5 and 260 µ A. In particular, SIRM values above 26 µ A were observed for the plant species that were grouped due to their significantly higher accumulation of PM. 'Specific leaf area' (SLA), specifically the ratio of the one-sided 'fresh' leaf area to its dry mass, was the significant leaf characteristic. SLA correlated with leaf complexity. In particular, plant species with elongated leaves were characterized by low SLA, high FLS and high complexity and showed significantly higher SIRM values. Finally, the optimised size-resolved deposition model was also tested in an urban model to get an idea of the impact of a green wall on PM concentrations in a so-called 'street canyon'. These are narrow streets with high buildings on both sides, making air pollution more persistent. To this end, an ideal scenario was tested in which a green wall was introduced along both sides of the street over a length of about 270 m. The model result showed a decrease in PM2.5 and PM10 of 46 ± 12% and 52 ± 14%. This result is of course for a very optimal scenario where the green wall covers the entire building façades. Since this is not feasible in reality, other ways of promoting contact between green walls and polluted air can be explored. The insights obtained illustrate that the use of climbing plants can be a cost-effective and environmentally friendly solution to reduce PM concentrations. Moreover, the findings showed that models can be used to investigate the impact of green walls on PM levels. These findings fit within the broader context of designing healthy and sustainable urban environments and developing innovative solutions based on solid scientific knowledge.

Abstract: The development of porous metal materials with pore geometries and sizes at the nanoscale offers promising opportunities for the development of smart responsive interfaces for separation and catalytic applications and as building blocks for complex composite materials. Dealloying is an innovative technique based on selective removal of a sacrificial metal from a metal alloy to engineer surface textures and pores across significant thicknesses. Dealloyed structures may be processed over large scales and for a range of source alloys, offering unprecedented manufacturing opportunities. This review presents the operations and challenges of dealloying routes and discusses avenues for process optimizations and improvements, aiming at the development of scalable nanoporous materials. The potential of dealloyed materials for catalytic and sensing applications is expanded and benchmarked against reference materials. Future prospects and applications of dealloyed materials toward surface reactivity control and pore architecture development are highlighted.

Abstract: Phenols are considered as toxic pollutants and their discharge into the environment by industries is regulated by a concentration limit. As these limits are in the low mg L−1 to µg L−1-range, sensitive methods are necessary to detect these phenols. Here, aqueous industrial phenolic samples throughout a cleaning process were analyzed by two novel electrochemical sensors. Both the photoelectrochemical (PEC) sensor and the square wave voltammetric (SWV) sensor could successfully follow the decrease of the concentration of phenols along the industrial cleaning process. The discharge sample (μg L−1) could only be analyzed by the PEC sensor and not by the SWV sensor, as the phenolic concentration was close to the LOD of the latter. With HPLC-diode array detector (DAD) measurements, classical phenols such as phenol (PHOH), hydroquinone, resorcinol and o-cresol could be identified in the industrial samples, and their presence could be linked to the electrochemical responses. At last, the performance of the PEC and SWV sensors were compared with commercial colorimetric and chemical oxygen demand (COD) test kits. This comparison demonstrated the high sensitivity of the PEC sensor in the μg L−1 concentrated phenolic samples. Together with the identification of the redox peaks through HPLC-DAD analysis, the SWV sensor can be a powerful tool in the qualitative analysis of mg L−1 concentrated phenolic samples due to its speed, simplicity and absence of laborious sample pre-treatment steps.

Abstract: The increasing illicit production, distribution and abuse of amphetamine (AMP) poses a challenge for law enforcement worldwide. To effectively combat this issue, fast and portable tools for the on-site screening of suspicious samples are required. Electrochemical profile (EP)-based sensing of illicit drugs has proven to be a viable option for this purpose as it allows rapid voltammetric measurements via the use of disposable and low-cost graphite screen-printed electrodes (SPEs). In this work, a highly practical paraformaldehyde (PFA)-coated sensor, which unlocks the detectability of primary amines through derivatization, is developed for the on-site detection of AMP in seized drug samples. A potential interval was defined at the sole AMP peak (which is used for identification of the target analyte) to account for potential shifts due to fluctuations in concentration and temperature, which are relevant factors for on-site use. Importantly, it was found that AMP detection was not hindered by the presence of common diluents and adulterants such as caffeine, even when present in high amounts. When inter-drug differentiation is desired, a simultaneous second test with the same solution on an unmodified electrode is introduced to provide the required additional electrochemical information. Finally, the concept was validated by analyzing 30 seized AMP samples (reaching a sensitivity of 96.7 %) and comparing its performance to that of commercially available Raman and Fourier Transform Infrared (FTIR) devices.

Abstract: In the present work, the resolution and quantification of mixtures of different opiate compounds in the presence of common cutting agents using an electronic tongue (ET) is evaluated. More specifically, ternary mixtures of heroin, morphine and codeine were resolved in the presence of caffeine and paracetamol. To this aim, an array of three carbon screen-printed electrodes were modified with different ink-like solutions of graphite, cobalt (II) phthalocyanine and palladium, and their responses towards the different drugs were characterized by means of square wave voltammetry (SWV). Developed sensors showed a good performance with good linearity at the mu M level, LODs between 1.8 and 5.3 mu M for the 3 actual drugs, and relative standard deviation (RSD) ca. 2% for over 50 consecutive measurements. Next, a quantitative model that allowed the identification and quantification of the individual substances from the overlapped voltammograms was built using partial least squares regression (PLS) as the modeling tool. With this approach, quantification of the different drugs was achieved at the mu M level, with a total normalized root mean square error (NRMSE) of 0.084 for the test subset.