Electronic noses (E-noses) are devices capable of detecting and identifying Volatile Organic Compounds (VOCs) in a simple and fast method. In this work, we present the development process of an opto-electronic device based on sensing films that have unique stimuli-responsive properties, altering their optical and electrical properties, when interacting with VOCs. This interaction results in optical and electrical signals that can be collected, and further processed and analysed. Two versions of the device were designed and assembled. E-nose V1 is an optical device, and E-nose V2 is a hybrid opto-electronic device. Both E-noses architectures include a delivery system, a detection chamber, and a transduction system. After the validation of the E-nose V1 prototype, the E-nose V2 was implemented, resulting in an easy-to-handle, miniaturized and stable device. Results from E-nose V2 indicated optical signals reproducibility, and the possibility of coupling the electrical signals to the opt ical response for VOCs sensing.

The heterogenization of the highly active monovacant polyoxotungstate ([PW11O39]7 −, abbreviated as PW11) was achieved by preparing the corresponding long chain quaternary ammonium salt (ODA7PW11, ODA = CH3(CH2)17(CH3)3N). The complete cation exchange confers total heterogeneity to the monovacant catalyst while keeping its oxidative catalytic activity. In fact, the heterogeneous catalyst allowed for the complete desulfurization of a multicomponent model diesel (2000 ppm S) after 40 min of reaction, conciliating extraction (using BMIMPF6 solvent) and oxidation (ECODS process using H2O2 oxidant). The heterogeneous catalyst has shown a superior desulfurization performance when compared with the homogeneous quaternary ammonium TBAPW11 catalyst (TBA = (C4H9)4 N). Both hybrid catalysts have been successfully reused in consecutive ECODS cycles. Additionally, the long carbon chain cations provide a protective environment around the polyoxometalate allowing for ODA7PW11 to retain its heterogeneity and structure after the ECODS process.

In the present work composite membranes were produced by combining magnetic nanoparticles (NPs) with cellulose acetate (CA) membranes for magnetic hyperthermia applications. The non-woven CA membranes were produced by electrospinning technique, and magnetic NPs were incorporated by adsorption at fibers surface or by addition to the electrospinning solution. Therefore, different designs of composite membranes were obtained. Superparamagnetic NPs synthesized by chemical precipitation were stabilized either with oleic acid (OA) or dimercaptosuccinic acid (DMSA) to obtain stable suspensions at physiological pH. The incorporation of magnetic NP into CA matrix was confirmed by scanning and transmission electron microscopy. The results showed that adsorption of magnetic NPs at fibers’ surface originates composite membranes with higher heating ability than those produced by incorporation of magnetic NPs inside the fibers. However, adsorption of magnetic NPs at fibers’ surface can cause cytotoxicity depending on the NPs concentration. Tensile tests demonstrated a reinforcement effect caused by the incorporation of magnetic NPs in the non-woven membrane.

One strategy that has gained much attention in the last decades is the understanding and further mimicking of structures and behaviours found in nature, as inspiration to develop materials with additional functionalities. This review presents recent advances in stimuli-responsive gels with emphasis on functional hydrogels and microgels. The first part of the review highlights the high impact of stimuli-responsive hydrogels in materials science. From macro to micro scale, the review also collects the most recent studies on the preparation of hybrid polymeric microgels composed of a nanoparticle (able to respond to external stimuli), encapsulated or grown into a stimuli-responsive matrix (microgel). This combination gave rise to interesting multi-responsive functional microgels and paved a new path for the preparation of multi-stimuli “smart” systems. Finally, special attention is focused on a new generation of functional stimuli-responsive polymer hydrogels able to self-shape (shape-memory) and/or self-repair. This last functionality could be considered as the closing loop for smart polymeric gels.

In this paper the rheological characterization of Pluronic/water systems filled with alginate microparticles is presented. The rheological characterization of the Pluronic/water systems allowed for the choice of the best Pluronic concentration taking into account its applications as injectable hydrogels for tissue repair. The effect on the rheological behavior of the addition of alginate microparticles, to be loaded with the drug, was analyzed and the maximum concentration of microparticles determined.

Non-invasive and fast diagnostic tools based on volatolomics hold great promise in the control of infectious diseases. However, the tools to identify microbial volatile organic compounds (VOCs) discriminating between human pathogens are still missing. Artificial intelligence is increasingly recognised as an essential tool in health sciences. Machine learning algorithms based in support vector machines and features selection tools were here applied to find sets of microbial VOCs with pathogen-discrimination power. Studies reporting VOCs emitted by human microbial pathogens published between 1977 and 2016 were used as source data. A set of 18 VOCs is sufficient to predict the identity of 11 microbial pathogens with high accuracy (77%), and precision (62–100%). There is one set of VOCs associated with each of the 11 pathogens which can predict the presence of that pathogen in a sample with high accuracy and precision (86–90%). The implemented pathogen classification methodology supports future database updates to include new pathogen-VOC data, which will enrich the classifiers. The sets of VOCs identified potentiate the improvement of the selectivity of non-invasive infection diagnostics using artificial olfaction devices.

Fuel poverty is a recognized and increasing problem in several European countries. A growing body of literature covers this topic, but dedicated analysis for Portugal are scarce despite the high perception of this condition. This paper contributes to fill this knowledge gap focusing on a European southern city while bringing new datasets and analysis to the assessment of this topic; consumer groups identification and to policy discussion. Daily electricity smart meters' registries were combined with socio-economic data, collected from door-to-door surveys, to understand the extent and the determinants of energy consumption for two contrasting consumer groups (herein called fuel poverty and fuel obesity groups). The analysis is based on the amount and annual profile of electricity consumption and was complemented with building energy simulations for relevant building typologies in those groups, to identify heating and cooling thermal performance gaps. The existence of these gaps allowed confirming and/or discarding the initial hypothesis of the poverty or obesity conditions. Results disclose socio-economic variables, as income, and consumers' behavior as key determinants of electricity consumption. It was identified a severe lack of thermal comfort levels inside households of both groups, either in cooling (98% for fuel poverty and 87% for fuel obesity) and heating seasons (98% for fuel poverty and 94% for fuel obesity). Major conclusion refers that electricity consumption cannot be used alone to segment consumer groups. This assessment may serve to support energy policy measures and instruments targeted to different consumers' groups. For example, distinct campaigns and differentiated incentives may apply to achieve energy efficiency and reduction while keep or improve indoor comfort levels.

In this work 2H NMR spectroscopy and 1H NMR relaxometry and diffusometry were used to characterise water order and dynamics in cellulose acetate/silica asymmetric membranes. Two hydrated membranes were characterised allowing the identification of extra ordering of the water molecules and the presence in each membrane of up to two spectral components with different degrees of order and different T1 values. The mechanism behind this order increase was ascribed to the rapid exchange of the water molecules between the pore walls and its interior. T1 relaxometry dispersions allowed for the identification of the relevant mechanisms of pore-confined water motion, with rotations mediated by translational displacements (RMTD) as the dominant mechanism in the low frequency region. Using the RMTD low cut off frequency along with the in situ directly measured diffusion constant it was possible do determine characteristic lengths of correlated water motion in both membranes studied, which fall in ranges compatible with typical pore dimensions in similar membranes.

The present work addressed the challenges of identifying applicable Non-Destructive Testing (NDT) techniques suitable for inspection and materials characterization techniques for Wire and Arc Additive Manufacturing (WAAM) parts. With the view of transferring WAAM to the industry and qualifying the manufacturing process for applications such as structural components, the quality of the produced parts needs to be assured. Thus, the main objective of this paper is to review the main NDT techniques and assess the capability of detecting WAAM defects, for inspection either in a monitoring, in-process or post-process scenario. Radiography and ultrasonic testing were experimentally tested on reference specimens in order to compare the techniques capabilities. Metallographic, hardness and electrical conductivity analysis were also applied to the same specimens for material characterization. Experimental outcomes prove that typical WAAM defects can be detected by the referred techniques. The electrical conductivity measurement may complement or substitute some destructive methods used in AM processing.