Publications

Abstract This study investigates spatial distribution and chemical elemental composition screening in soils in Rome (Italy) using X-ray fluorescence analysis. Fifty-nine soil samples were collected from various locations within the urban areas of the Rome municipality and were analyzed for 19 elements. Multivariate statistical techniques, including nonlinear mapping, principal component analysis, and hierarchical cluster analysis, were employed to identify clusters of similar soil samples and their spatial distribution and to try to obtain environmental quality information. The soil sample clusters result from natural geological processes and anthropogenic activities on soil contamination patterns. Spatial clustering using the k-means algorithm further identified six distinct clusters, each with specific geographical distributions and elemental characteristics. Hence, the findings underscore the importance of targeted soil assessments to ensure the sustainable use of land resources in urban areas.

Abstract This work aims to conduct a Life Cycle Assessment (LCA) of seamless leggings produced by a Portuguese textile company, following a “cradle-to-gate” approach. This includes all life cycle stages from raw material production to the packaging of the seamless leggings, ready to leave the company gate. Primary data for the foreground processes were obtained from the actual industrial practices of the Portuguese company, complemented by data from the ecoinvent V3.5 life cycle inventory database and literature sources, primarily for the background processes. The ReCiPe 2016 Midpoint (E) V1.02 methodology was employed to evaluate potential environmental impacts, using the SimaPro V8.5.2 LCA software. Results indicate that the production and spinning of fibers have the highest environmental impacts, mainly due to their high energy consumption. Dyeing operations are more impactful than confection operations, particularly contributing to water use and freshwater ecotoxicity. Therefore, efforts to reduce overall environmental impacts should initially focus on these life cycle stages. Switching the electricity source from the national grid mix to entirely photovoltaic energy resulted in a significant reduction in several environmental impact categories, including a 30% reduction in global warming potential. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract Borophene, a monolayer of boron atoms, belongs to intensively studied two-dimensional beyond-graphene materials. The B36 borophene nanoflake is a finite size model system, containing a hexagonal vacancy similar to the ones present in (312 and chi 3 borophene sheets. The hydrogen binding performance of B36 decorated with various transition metal atoms is investigated using density functional theory and quantum theory of atoms in molecules. Hydrogen is considered to become one of the crucial energy sources in future, hence, a search for effective hydrogen storage materials is of urge importance. Obtained results suggest that B36 decorated with Co, Ni, Fe, and Cu possess strong affinity to bind the H2 molecule via formation of eta 2-dihydrogen bonds. Among them, the strongest H2 binding is found for Co- and Ni-decorated B36. Furthermore, B36 decorated with Sc and Ti behave like H-H bond breakers while B36 decorated with Zn possess only negligible affinity to bind H2 molecule. The stability of the B36 decorated with Co and Ni is verified by ab initio molecular dynamics. The presented data may also serve as a basis for reference in future large-scale computational studies of borophene-based materials.

Abstract Heat capacity, a crucial physical property for chemical processes, is often understudied in Deep Eutectic Solvents (DESs), which in turn are promising green alternatives to environmentally hazardous conventional solvents. This work addresses this gap by developing a machine learning model to predict DES heat capacity and identify key structural features influencing it. We employed a dataset of 530 DESs with corresponding experimental heat capacity values. Quantum-chemical COSMO-RS-based descriptors, capturing detailed information about DES structures, were calculated for each data point. Various machine learning algorithms, namely k-Nearest Neighbours (kNN), Random Forests (RF), Neural Network Multilayer Perceptron (MLP), and Support Vector Machines (SVM) were explored alongside a linear model (Multiple Linear Regression, MLR). Hyperparameter optimisation ensured all models were fine-tuned for optimal performance. The most successful model, based on the MLP technique, achieved remarkably low Average Absolute Relative Deviation (AARD) values of 0.500 % and 3.999 % for the training and test sets, respectively. This signifies a significant improvement in prediction accuracy compared to traditional methods. Furthermore, by applying a SHapley Additive exPlanations (SHAP) analysis, we identified the most crucial structural factors within DES components that govern their heat capacity. This comprehensive investigation offers valuable insights that can pave the way for an efficient design of novel DESs in the future. © 2024 The Author(s)

Abstract The development of simple, selective, and cost-effective methods for quantification of bovine serum albumin (BSA) is currently very important for assessing milk quality (and safety). In this work, a new surface plasmon resonance (SPR) sensor was developed, consisting of imprinted hydrogel-based nanoparticles (nanoMIPs) immobilized on gold platforms, to quantify BSA in bovine milk. The nanoMIPs prepared for recognition of BSA were synthesized by the precipitation polymerization approach, using a synthetic BSA epitope (VVSTQTALA) as template. The spherical MIP nanoparticles (NPs) had an average size of 60 nm. The binding studies performed revealed that the binding affinity of the prepared nanoMIPs to BSA (KD = 7.1 × 10−6 mol L−1) was comparable to that obtained by a natural BSA antibody (KD = 2.5 × 10−6 mol L−1). The plasmonic sensor incorporating the MIP nanomaterials achieved a limit of detection (LOD) of 1.02 × 10−6 mol L−1 (0.068 mg mL−1) and a limit of quantification (LOQ) of 3.39 × 10−6 mol L−1 (0.225 mg mL−1), over a linear range from 2.0 × 10−6 mol L−1 to 1.5 × 10−5 mol L−1. Moreover, the selectivity studies revealed a significant sensor response towards casein and a negligible response towards vancomycin. In the end, the optical sensor was tested against commercial milk samples, showing promising viability for detection of BSA as the value reported by the plasmonic sensor ((1.0 ± 0.1) × 10−4 mol L−1) was very close to that obtained by size exclusion-high-performance liquid chromatography (SEC-HPLC). © 2025 The Author(s)

Abstract The lower refractive index sensitivity (RIS) of plasmonic nanoparticles (NP) in comparison to their plasmonic thin films counterparts hindered their wide adoption for wavelength-based sensor designs, wasting the NP characteristic field locality. In this context, high aspect-ratio colloidal core-shell Ag@Au nanorods (NRs) are demonstrated to operate effectively at telecommunication wavelengths, showing RIS of 1720 nm/RIU at 1350 nm (O-band) and 2325 nm/RIU at 1550 nm (L-band), representing a five-fold improvement compared to similar Au NRs operating at equivalent wavelengths. Also, these NRs combine the superior optical performance of Ag with the Au chemical stability and biocompatibility. Next, using a side-polished optical fiber, we detected glyphosate, achieving a detection limit improvement from 724 to 85 mg/L by shifting from the O to the C/L optical bands. This work combines the significant scalability and cost-effective advantages of colloidal NPs with enhanced RIS, showing a promising approach suitable for both point-of-care and long-range sensing applications at superior performance than comparable thin film-based sensors in either environmental monitoring and other fields.

Abstract In this study, we describe the development of hydrogel formulations composed of micelles loading two natural antioxidants-resveratrol and rutin-and the evaluation of the effect of a by-product on the rheological and textural properties of the developed semi-solids. This approach aims to associate the advantages of hydrogels for topical administration of drugs and of lipid micelles that mimic skin composition for the delivery of poorly water-soluble compounds in combination therapy. Biomimetic micelles composed of L-alpha-phosphatidylcholine loaded with two distinct polyphenols (one non-flavonoid and one flavonoid) were produced using hot shear homogenisation followed by the ultrasonication method. All developed micelles were dispersed in a carbomer 940-based hydrogel to obtain three distinct semi-solid formulations, which were then characterised by analysing the thermal, rheological and textural properties. Olive pomace-based hydrogels were also produced to contain the same micelles as an alternative to respond to the needs of zero waste and circular economy. The thermograms showed no changes in the typical profiles of micelles when loaded into the hydrogels. The rheological analysis confirmed that the produced hydrogels achieved the ideal properties of a semi-solid product for topical administration. The viscosity values of the hydrogels loaded with olive pomace (hydrogels A) proved to be lower than the hydrogels without olive pomace (hydrogels B), with this ingredient having a considerable effect in reducing the viscosity of the final formulation, yet without compromising the firmness and cohesiveness of the gels. The texture analysis of both hydrogels A and B also exhibited the typical behaviour expected of a semi-solid system.

Abstract Bioluminescence (BL) and chemiluminescence (CL) are remarkable processes in which light is emitted due to (bio)chemical reactions. These reactions have attracted significant attention for various applications, such as biosensing, bioimaging, and biomedicine. Some of the most relevant and well-studied BL/CL systems are that of marine imidazopyrazine-based compounds, among which Coelenterazine is a prime example. Understanding the mechanisms behind efficient chemiexcitation is essential for the optimization and development of practical applications for these systems. Here, the CL of a fluorinated Coelenterazine analog was studied using experimental and theoretical approaches to obtain insight into these processes. Experimental analysis revealed that CL is more efficient under basic conditions than under acidic ones, which could be attributed to the higher relative chemiexcitation efficiency of an anionic dioxetanone intermediate over a corresponding neutral species. However, theoretical calculations indicated that the reactions of both species are similarly associated with both electron and charge transfer processes, which are typically used to explain efficiency chemiexcitation. So, neither process appears to be able to explain the relative chemiexcitation efficiencies observed. In conclusion, this study provides further insight into the mechanisms behind the chemiexcitation of imidazopyrazinone-based systems.

Abstract Micro- and nanoplastics (MNPs) are an important atmospheric aerosol constituent. However, there still needs to be a standard procedure for their sampling and size fractionation, which is an obstacle to the aggregation and critical analysis of results obtained by different research groups. This review focuses on the sampling and fractionation methodologies used for MNPs. Moreover, a streamlined, simplified methodology for sampling and fractionation is proposed.

Abstract <jats:p>Green carbon-based materials (GCM), i.e. carbon materials produced using renewable biomass or recycled wastes, ought to be used in order to processes become sustainable and carbon neutral. Carbon nanomaterials, like for example carbon dots and nanobichar families, and carbon materials, like for example activated carbon and biochar substances, are sustainable materials with great potential to be used in different technology applications. In this review, the following four applications were selected, and the works published in the last two years (since 2022) critically reviewed: agriculture; water treatment; energy management; and, carbon dioxide reduction and sequestration. GCM improved the performance of the technological applications under revision and play an important role in the sustainability of the processes, contributing to the mitigation of the climate change, namely by reducing emission and increase sequestration of CO2eq..</jats:p>