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A 3D polymorphic Cu-based ultramicroporous MOF capable of CO2 Uptake and Conversion
Get PDFThe development of advanced porous sorbents for CO2 capture from gas mixtures remains pivotal for meeting net zeroemission targets by 2050. Among these, metal–organic frameworks (MOFs) continue to stand out due to their structural
tunability and high surface areas. Herein, we report a new ultramicroporous 3D physisorbent MOF, constructed from CuII
nodes and the multitopic 3,6-N-ditriazolyl-2,5-dihydroxy-1,4-benzoquinone anilato ligand (trz2An). This species, of
[Cu(trz2An)]·nH2O (n ≤ 3) general formula, crystallizes in two (monoclinic and orthorhombic) polymorphs. The existence of
two structurally related forms arises from a polysynthetic twinning mechanism involving short range ligand reorientation
within a single crystal domain. Despite such structural variability, comparative analysis of both polymorphs reveals no
significant differences in porosity metrics or gas sorption behavior. [Cu(trz2An)] displays high selectivity and separation
efficiency for N2/CO2 and CH4/CO2 mixtures, along with remarkable cycling stability. Furthermore, it shows promising
catalytic activity toward CO2 reduction reaction (CO2RR), which playes a key role into carbon utilization strategies,
particularly favouring the formation of ethylene — an industrially valuable product. These results highlight [Cu(trz2An)]·as a
regenerable, structurally resilient MOF, combining efficient gas separation and CO2 valorization and offering a compelling
blueprint for the design of next-generation, environmentally sustainable physisorbent
Mapping beam cross-section features to higher-order generalized variables using machine learning
Get PDFThe aim is to provide a numerical tool able to assess the accuracy of a set of generalized displacement variables for a given beam geometry. Furthermore, it can provide the most influential generalized variables for a given problem. The training dataset is built on the Carrera Unified Formulation and is based on a combination of fourth-order polynomial expansions. Convolutional and deep neural networks are used to correlate structural theories, geometries, materials, and accuracy. Dynamics problems are considered, and the accuracy is evaluated using natural frequencies. The trained network receives as inputs the problem features, such as the cross-section geometry and material, and a structural theory and estimates its accuracy. The results show that the proposed approach reliably predicts the accuracy of a structural theory. On the other hand, in evaluating the set of most influential generalized variables, the performance of the networks is poorer but still acceptable. In most cases, the accuracy of the natural frequencies is high if 60% of the total fourth-order terms are included; all terms up to the second-order are mandatory, and some third- and fourth-order terms are very influential
Morphed graphene as reinforcement for oil-well class G cement composites
Get PDFMorphed graphene (MG) has only recently been put forward as the perfect reinforcement composite material for structure composites due to its unique mechanical properties. This article addresses the possibility of applying MG as a toughener phase in composites of cement for oil-well. MG was synthesized from petroleum coke through control milling and incorporated into cement with varying concentrations (0.1–1%). The mechanical behavior of MG-reinforced cement demonstrated significant improvements, including enhanced fracture energy, flexural strength, and compression strength. Electron microscopy morphological analysis confirmed that MG effectively reduced porosity and improved particle cohesion
URDICO - Urban Dimension of Cohesion Policy and other EU Programmes: Policy Brief
No full textThis policy brief, based on the ESPON URDICO final report, examines how the urban dimension of EU Cohesion Policy has been implemented across eight European cities. It highlights how cities interact with national and regional authorities, align EU funds with local long-term agendas, and contribute to broader EU goals. Cohesion Policy, accounting for nearly one-third of the EU budget, aims to promote balanced territorial development and reduce disparities between regions. Cities play a central role as engines of economic growth and social innovation, yet their influence and capacity vary widely. Over time, the urban dimension has evolved from a marginal concern to a strategic focus, from the early URBAN I and II programmes to the introduction of Sustainable Urban Development (SUD), Integrated Territorial Investments (ITI), and Community-Led Local Development (CLLD) in 2014–2020. These tools enabled cities to develop place-based, integrated strategies, supported by multi-level governance and dedicated funding. The 2021–2027 programming period reinforced these mechanisms, increasing urban earmarking and expanding the focus on climate, digital transformation, and social resilience. Nonetheless, challenges remain, including uneven administrative capacity, varying financial access, and limited autonomy for local authorities. URDICO’s findings illustrate both the potential and the constraints of urban-centred cohesion strategies, offering insights and recommendations to strengthen the role of cities in the post-2027 EU policy framework
Assessment of phase change materials for thermal energy storage in battery systems for heavy-duty vehicle applications
Get PDFThermal management is vital for the performance, safety, and longevity of heavy-duty vehicles (HDVs). This study evaluates phase change materials (PCMs) for passive battery thermal management, identifying n-octadecane as the best commercial option due to its 25–32 °C melting range, high latent heat (222.2 J/g), and stability. Tests using a thermal energy storage (TES) setup showed conduction-dominated heat transfer when solid and convection-enhanced transfer when liquid. Higher heat-transfer-fluid (HTF) flow rates had little effect on charge/discharge time but significantly increased TES thermal power, reaching a ratio of 56 at 3 L/min—3.5× higher than without PCM. Integrating PCM boosted gravimetric specific power to 0.056 kW/kg (3.5× improvement) and volumetric specific power to ~68 kW/m3 (6× improvement). Overall, PCM-integrated TES modules show strong potential for scalable HDV battery or cabin cooling solutions
Natural ventilation of a room-atrium building with opposing wind: a deterministic and stochastic analysis
No full textNatural ventilation is key for reducing energy demand and ensuring indoor air quality. We study the deterministic and stochastic dynamics of a naturally ventilated system where a room with a steady buoyancy source connects to an unforced atrium (an arrangement representative of many real buildings). The buoyant fluid accumulates at the ceiling of both spaces. A stratification arises, inducing the stack effect which drives the ventilation of the system. We consider the occurrence of an opposing wind. Firstly, a constant wind is imposed, and the steady states are analysed for different atrium geometries. It is known that when no external wind occurs the atrium may either enhance or worsen the ventilation of the room depending on its geometry. We find that for any geometry the atrium enhances the ventilation for a wind velocity large enough. Secondly, stochastic fluctuations are introduced in the wind velocity. These induce a ‘noise-induced transition’: the mean position of the interface between warm and cold layers lies below that observed under constant wind. This phenomenon was already known for single-room systems; however, we find that the room-atrium system is less sensitive to this effect and to variations in the coefficient of variation of wind velocit
Assimilating WIVERN windpseudo-observations in WRF model: an application to the outstanding case of the Medicane Ianos
Get PDFAccurate weather forecasts are important to our daily lives. Wind, cloud and precipitation are key drivers of the Earth's water and energy cycles, and they can also pose weather-related threats, making the task of numerical weather prediction (NWP) models particularly challenging and important.
The Wind Velocity Radar Nephoscope (WIVERN) mission will be the first space-based mission to provide global vertical profiles of winds within clouds, and to deliver simultaneous observations of winds, clouds, and precipitation with unprecedented resolution and coverage. The mission has been selected as the European Space Agency's (ESA) Earth Explorer 11 within the Future Earth Observation (FutureEO) programme. Its data could be beneficial to several sectors: improving our knowledge of weather phenomena, validate climate statistics, and enhancing NWP performance. This paper aims to contribute to the last point by analyzing the impact of assimilating WIVERN Line of Sight (LoS) winds on NWP performance for the high-impact case study of Medicane Ianos, which occurred between 15 and 21 September 2020 in the central Mediterranean and made landfall on the west coast of Greece.
To this end, we generate WIVERN pseudo-observations, that are assimilated in the Weather Research and Forecasting (WRF) model run at moderate horizontal resolution (4 km).
Results show that assimilating WIVERN into the WRF model has a positive impact on the prediction of the Medicane trajectory. Specifically, assimilating WIVERN just once reduces the trajectory forecast error by about 40 %. The data assimilation of WIVERN pseudo-observations affects not only the storm's trajectory but also its physical characteristics. It is also shown that the assimilation improves the prediction of precipitation and surface winds, and has the potential to improve our resilience to severe weather events by enabling better forecasts of storm impacts. Finally, we present the results of two sensitivity experiments in which the background and observation errors were changed. The results show greater sensitivity to changes in the background error matrix
Bio-based cellulose-filled vitrimers for 3D printing via liquid deposition modeling: Rheological tuning and environmental assessment
Get PDFTo address the need for sustainable materials in 3D printing applications, a bio-based vitrimer was developed using an epoxy resin derived from cardanol and cystamine as a cross-linker. Cystamine was chosen due to its dynamic disulfide bonds, bio-based nature and highly reactive aliphatic amine groups, enabling rapid network formation under mild thermal conditions. Microfibrillated cellulose (MFC) and ultrafine cellulose (UFC) were used as bio-based fillers and rheology modifiers to formulate printable pastes. The curing process was thoroughly investigated by DSC and FTIR-ATR, confirming efficient cross-linking under the selected conditions. Thermal and structural properties of the vitrimers were characterized by gel content, swelling, and heat resistance analyses. The printability of the pastes via Liquid Deposition Modeling was evaluated through rheological analysis, and a concentration of 13 wt% MFC and 13 wt% UFC was identified as the optimal compromise between shear-flow behavior and post-print structural integrity. Simple and more complex geometries were printed and then cured at 30–80 °C, ensuring high shape fidelity (87.0 %). The vitrimer behavior was confirmed by stress-relaxation experiments, showing an overall activation energy in the range of 63–65 kJ mol−1, and by successful mechanical recyclability. Finally, a preliminary Life Cycle Assessment underscored the potential of these materials for sustainable additive manufacturing
Identification of primary and secondary resonances: experimental continuation and broadband data-based modeling
Get PDFThis paper presents a comparative study of two sets of techniques for identifying primary and secondary resonances in nonlinear dynamic systems: experimental continuation and broadband data-based modeling. The former refers to methods integrating control and continuation processes to empirically derive the bifurcation diagram of a nonlinear system. These approaches do not require a model, but the need for a controller introduces complexity in the experiments. Conversely, broadband data-based modeling uses wide-spectrum excitation data to develop a nonlinear model of the system. Proper model validation is crucial in this process to ensure accurate results. In this work, the comparison is carried out using two different setups: an electronic Duffing system and a thin-walled nonlinear beam. The findings demonstrate that both methods, when properly applied, can effectively identify not only primary resonances, but also the more challenging secondary ones. Measuring and predicting these resonances constitutes an ambitious task for data-based approaches. Moreover, the direct comparison between experimental continuation and broadband data-based techniques highlights the complementary strengths and limitations of each approach, providing new insights and perspectives on the identification of nonlinear resonances
Fragmentation and energy dissipation in rockfall: Effects of block shape and non-collinear impact dynamics
Get PDFUnderstanding fragmentation and energy dissipation during rockfall events is essential for accurate hazard assessment and predictive modelling. To date, most experimental studies have used spherical specimens, primarily because of their geometric simplicity and ease of repeatable testing. This work investigates the dynamic behaviour of angular block shapes, i.e., cubes, prisms, and slabs, which more closely resemble natural rock geometries, through free-fall drop tests up to 10 m/s, complemented by static splitting tests to explore potential links with dynamic response. These geometries often result in non-collinear impacts with multiple contact points and prolonged impact durations, significantly influencing the likelihood of fragmentation and post-impact dynamics. The study examines how block geometry, impact orientation and location (face, edge, vertex) affect failure patterns and energy restitution. Results show that fragmentation probability strongly depends on geometry: slabs fragmented in 33% of tests, prisms in 50%, while cubes only at the highest velocity. Static tests revealed geometry- and loading condition- dependent tensile strength, with prisms showing the highest median value (2.3 MPa) and slabs the lowest (1.1 MPa). Fragmentation severity also varied, with slabs producing finer fragments compared to prisms. For intact specimens, apparent restitution coefficients ranged from 0.13 (prisms) to 0.39 (cubes), significantly lower than spheres (0.34), and impact durations were up to two orders of magnitude longer than for spherical blocks. The results highlight the complex interplay between block geometry, impact conditions, and energy dissipation, providing shape-dependent metrics for improving rockfall trajectory models