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In the quest for more efficient solar thermal systems, accurately determining the thermal emittance of low-emissive materials is crucial in determining the power losses. This paper describes the calorimetric method designed to precisely measure the thermal emittance of Selective Solar Absorbers (SSAs) to be used in High Vacuum Flat Plate Collectors (HVFPCs). The method’s capability is demonstrated through the successful correction of thermal emittance values for copper samples of varying sizes, including dimensions down to 49 cm2. Results highlight the method’s potential to significantly reduce measurement errors associated with small-size and/or low-emittance samples, providing a path forward to improve the design and efficiency of SSAs. This research marks a significant step in advancing solar thermal technology by enabling emittance measurements with a precision better than 0.003, which is essential for the development of high-performance solar thermal absorbers. The method has also been applied to correct the thermal emittance value of SSA measured in previous measurement campaigns, and it allows a better estimation of the SSA efficiency conversion curve.

Degradation issues correlated to microstructural changes are the main obstacles to solid oxide fuel cell and electrolyser applications, making their identification and understanding fundamental steps. Coupling experimental activities with modelling, this work analyses the state-of-the-art Ni-YSZ (Yttria-Stabilized Zirconia)/YSZ/CGO (Cerium Gadolinium Oxide)/LSCF (Lanthanum Strontium Cobalt Ferrite)-CGO-based cell after 1000 h of galvanostatic electrolysis operation at fixed temperature and high steam composition in the inlet gas. Following a multiscale approach, the system behaviour is characterized through electrochemical impedance spectra and polarization curves as well as studying microstructure evolution, with a focus on Ni-cermet functional layer in view of Ni instability detected as the main degradation cause. A comparison with a cell consisting of the same initial geometrical structure and materials but aged in fuel cell mode allows to highlight the influence of operating mode and parameters on Ni-YSZ microstructure. Ni particle size and phase fraction variations experimentally observed on the electrode surface are correlated to water content and applied polarization simulated local values. Ni uneven distribution at the electrolyte interface and particle coarsening, above all, lead to an increase in polarization loss under electrolysis and fuel cell mode, respectively, since both penalise the charge transfer reaction and migration.

Dataset supporting publication of manuscript_GCB-B-RA-24-138

In this study, innovative polyurethane (PUR)-based aerogels were developed and reinforced with silica (SiO2) particles derived from rice husk through two distinct treatments: acid digestion (AD) and sol-gel (SG). These materials address the dual challenge of valorizing agricultural by-products and improving acoustic insulation properties. Acoustic characterization using impedance tube methods revealed a homogeneous internal structure, as evidenced by the consistent absorption rates on both sides of the aerogels. PUR aerogels doped with 1 wt% SG (SiO2_SG1), 2 wt% AD (SiO2_AD2), and 1 wt% AD (SiO2_AD1) achieved the highest absorption coefficients, outperforming traditional materials at specific frequencies, while 2 wt% SG (SiO2_SG2) exhibited the lowest absorption rate. Transmission loss measurements further demonstrated that SiO2_SG1 achieved superior performance at low frequencies, while SiO2_SG2 excelled at high frequencies, highlighting the tunable acoustic behavior of these aerogels. Compared to conventional insulation materials, these aerogels combine lightweight properties, high porosity, and sustainable synthesis, offering a cost-effective and eco-friendly alternative for building applications. This work demonstrates a significant step forward in the integration of bio-based resources into high-performance acoustic materials, bridging the gap between sustainability and functionality in material design.

Anion exchange membrane water electrolyser showing the chemical structure of hydroxyl-conductive 2D hBN-based anion exchange membrane (AEM). The developed AEMs exhibit high hydroxyl conductivity, superior mechanical and electrochemical stability.

Third-generation biofuels are currently a promising alternative for energy production, since electricity prices have risen sharply and the search for alternative energy sources to fossil fuels has become a necessity. The use of the anaerobic digestion process for the production of biomethane from microalgae has been studied over the years and has reached a certain degree of maturity, becoming the most straightforward way to obtain energy from microalgae without the need for a previous drying or extraction phase, thus eliminating the costs associated with these operations. Microalgae also show a high potential to grow in different media, including wastewater, as well as a high capacity for nutrient absorption and carbon dioxide fixation, which aid in decarbonization. These characteristics, combined with biomethane production, can contribute to achieving a satisfactory bioenergy production in a circular economy model. Peer reviewed 2 Tablas

In this paper, a new methodology for fault detection and diagnosis in photovoltaic systems is proposed. This method employs a novel Euclidean distance-based tree algorithm to classify various considered faults. Unlike the decision tree, which requires the use of the Gini index to split the data, this algorithm mainly relies on computing distances between an arbitrary point in the space and the entire dataset. Then, the minimum and the maximum distances of each class are extracted and ordered in ascending order. The proposed methodology requires four attributes: Solar irradiance, temperature, and the coordinates of the maximum power point (Impp, Vmpp). The developed procedure for fault detection and diagnosis is implemented and applied to classify a dataset comprising seven distinct classes: normal operation, string disconnection, short circuit of three modules, short circuit of ten modules, and three cases of string disconnection, with 25%, 50%, and 75% of partial shading. The obtained results demonstrate the high efficiency and effectiveness of the proposed methodology, with a classification accuracy reaching 97.33%. A comparison study between the developed fault detection and diagnosis methodology and Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbors algorithms is conducted. The proposed procedure shows high performance against the other algorithms in terms of accuracy, precision, recall, and F1-score.

The Arctic climate system is in great distress, warming faster than the rest of the world and transforming more rapidly than previously anticipated. Sustained and harmonized multidisciplinary observations at key locations are needed to fill knowledge gaps and evaluate the ongoing climate change impacts on the complex Arctic marine system. For more than a decade, the Distributed Biological Observatory (DBO) has functioned as a “detection array” for ecosystem changes and trends in the Pacific sector of the Arctic Ocean. This long-term collaborative initiative builds on active involvement of scientists conducting in situ observations within marine disciplines to systematically document how the arctic marine ecosystem is transforming with environmental change. The DBO concept is currently being expanded into other sectors of the Arctic, including Davis Strait and Baffin Bay, the Atlantic Arctic gateway area, and the East Siberian Sea. Through increased collaboration and joint practices, findings from these regional areas can leverage to pan-Arctic perspectives and improve our understanding of the entire Arctic Ocean. Common practices are now being developed, including key phenomena and relevant indicators to study. Also, we strive towards harmonized routines for sampling, analysis and data sharing to increase the comparability across both disciplines and regions, and to improve the usability of our in-situ observations also for the modelling and remote sensing scopes. An ambition is, moreover, to expand from today's predominantly open-sea coverage towards coastal regions, to the benefit of both local communities and researchers. The process of establishing a pan-Arctic DBO network is to a large part facilitated by the EU Horizon project Arctic PASSION (2022-2025). Here, we present the latest developments and shared priorities, as well as our vision of how to incorporate our efforts into other parallel processes aiming to strengthen the pan-Arctic observing system towards, during and beyond the upcoming IPY.