A poly(methacrylic acid-co-ethylene glycol dimethacrylate)-based magnetic sorbent was used for the rapid and sensitive determination of tricyclic antidepressants and their main active metabolites in human urine. This material was characterized by magnetism measurements, zeta potential, scanning electron microscopy, nitrogen adsorption–desorption isotherms, and thermogravimetric analysis. The proposed analytical method is based on stir bar sorptive-dispersive microextraction (SBSDME) followed by liquid chromatography–tandem mass spectrometry. The main parameters involved in the extraction step were optimized by using the response surface methodology as a multivariate optimization method, whereas a univariate approach was employed to study the desorption parameters. Under the optimized conditions, the proposed method was properly validated showing good linearity (at least up to 50 ng mL⁻¹) and enrichment factors (13–22), limits of detection and quantification in the low ng L⁻¹ range (1.4–7.0 ng L⁻¹), and good intra- and inter-day repeatability (relative standard deviations below 15%). Matrix effects were observed for the direct analysis of urine samples, but they were negligible when a 1:1 v/v dilution with deionized water was performed. Finally, the method was successfully applied to human urine samples from three volunteers, one of them consuming a prescribed drug for depression that tested positive for clomipramine and its main active metabolite. Quantitative relative recoveries (80–113%) were obtained by external calibration. The present work expands the applicability of the SBSDME to new analytes and new types of magnetic sorbents. Graphical abstract

Microplastics (MPs) are recognised as emerging vectors for hydrophobic organic contaminants in aquatic environments due to their relatively large surface area and the diversity of their polymer chemistries compositions. This study investigates the sorption behaviour of two priority polycyclic aromatic hydrocarbons (PAHs), pyrene (PYR) and fluoranthene (FLU), onto six common MPs: poly(m-xylene adipamide) (PA-MXD6), high- and low-density polyethylene (HDPE, LDPE), polypropylene (PP), polyethylene terephthalate (PET), and polylactic acid (PLA). Sorption isotherms and kinetics were evaluated under simulated freshwater conditions at environmentally relevant concentrations (1–50 µg·L⁻¹). Despite the low MP concentration used (0.2 g·L⁻¹), over 80% of the initial PAH content was removed by polyolefins, and more than 50% by all other MPs. Sorption capacity was strongly dependent on particle surface area. Langmuir, Henry, and Freundlich isotherms models were fitted, with linear behaviour prevailing at low concentrations. Analysis using the Dubini–-Radushkevich model confirmed that sorption involves chemisorption contributions, mainly through π–π interactions and hydrophobic interactions (polyolefins). Mechanistically, molecular diffusion within the MP matrix was not governing the sorption process, as diffusion coefficients varied with particle size instead of polymer chemistry. Instead, sorption appears to be governed by PAH diffusion through the hydrodynamic boundary layer and subsequent retention on the MP surface. Empirically, kinetic data fitted the pseudo-second-order model, further supporting that the sorption process involves chemisorption. These findings highlight the role of MPs as vectors for PAHs in freshwater systems and their potential application in contaminant removal. Expressing sorption per unit surface area is recommended for accurate assessment. This work contributes to understanding the environmental behaviour of MPs and their implications for pollutant transport and toxicity.

This study presents a theoretical framework for modeling sorption and release kinetics of substances in polymeric materials with planar, cylindrical, and spherical geometries. Fick’s second law was expressed in dimensionless variables and solved numerically using a finite-difference approach to generate universal profiles for mass transfer. These profiles were fitted with double-exponential equations, yielding explicit expressions that allow for straightforward estimation of diffusion coefficients from experimental data. The method was validated using literature data for films, fibers, and microspheres, showing excellent agreement with reported values. Unlike classical analytical solutions, which are limited to planar systems under ideal conditions, the proposed approach is applicable to diverse geometries commonly employed in packaging, biomedical devices, controlled-release formulations, and environmental technologies.