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Hybrid bio-based epoxy vitrimers: balancing high performance and recyclability for sustainable innovation
No full textPublisher Copyright: © 2025 Elsevier B.V.The development of vitrimers has been gaining great interest lately, since the presence of dynamic covalent bonds in their structure allows the rearrangement of their topology, which leads them to combine the great properties characteristic of thermoset materials with the recyclability proper of thermoplastics. This duality is highly relevant for replacing conventional fossil-based epoxy resins with more sustainable alternatives. Moreover, the possibility of using bio-based precursors for their preparation is also an option in order to obtain an even more environmentally friendly material. In this work, partially and fully bio-based vitrimers were prepared using citric acid and two trifunctional epoxy resins: an aromatic fossil-based resin (GOA) and a linear bio-based resin (GGE). Fully bio-based systems exhibited very low glass transition temperatures (Tg ≤ 24 °C) and poor rigidity, limiting their applicability. However, hybrid systems that incorporated both epoxy resins achieved a remarkable balance between rigidity and ductility. In particular, the 0.7GOA/GGE formulation (71 wt% bio-based) cured at 120 °C exhibited a Tg of 43 °C, a flexural modulus of ∼2400 MPa, and a toughness over four times higher than the fully fossil-based counterpart. The recyclability of all systems was confirmed through thermo-mechanical and chemical routes, although higher GGE content required more severe conditions. All networks displayed shape-memory properties, demonstrating the versatility of these materials. These results highlight hybridization as an effective and scalable strategy to reconcile high bio-based content with strong mechanical performance and recyclability, positioning these vitrimers as sustainable candidates for advanced functional applications.Peer reviewe
SELFY - Self Assessment, Protection and Healing Tools for a Trustworthy and Resilient CCAM
Full text linkPublisher Copyright: © The Author(s) 2026.SELFY envisions an agnostic toolbox for the self-management of security and resilience of the CCAM (Connected, Cooperative and Automated Mobility) ecosystem, which can be easily deployed to extend the current Operational Design Domain (ODD), providing self-awareness, self-resilience and self-healing mechanisms and enhancing trust between stakeholders. SELFY is based on four pillars: Situational awareness, Resilience, Secure Data Sharing and Trust and provides three groups of tools. SACP (Situational Awareness and Collaborative Perception) tools aim at providing all CCAM actors with a comprehensive understanding of their environment, i.e., the perception of objects, such as other traffic participants and stationary objects. CRHS (Cooperative Resilience and Healing System) tools enable self-protection actions whenever a compromising situation is detected in relation to assets, vehicles, operations, or the system itself. TDMS (Trust and Data Management System) tools establish a secure and trusted environment for data in a collaborative and cooperative context, both for infrastructure and assets, as well as for citizen’s data, such as drivers or pedestrians with special attention to privacy considerations. By defining a collaborative environment between the different tools to respond to new threats, risks and attacks SELFY facilitates the comprehension of new challenges in the cybersecurity aspect of CCAMs.Peer reviewe
Novel PROXYL catholyte materials for high voltage aqueous organic redox flow batteries
No full textPublisher Copyright: © 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.Herein, a new family of PROXYL derivatives is presented as candidate catholyte materials for Aqueous Organic Redox Flow Batteries (AORFBs). The use of PROXYL based nitroxyl radicals, compounds featuring a 5-member ring bearing the active site, is explored. A non-symmetric pyrroline intermediate is introduced as a key building block to access a variety of highly soluble compounds with different structural motifs. Extensive characterization including solubility, redox potential, kinetics and cycling stability, complemented by computational studies, serves to establish correlations between functionalization and catholyte performance. The internal double bond on the pyrroline-N-oxyl is responsible for a 110 mV increase in the redox potential (0.91 V vs. SHE) of PROXYL derivates. Importantly, in addition to the presence of electron-withdrawing groups, solvation energy influences the redox potential across different structures. The charge population serves to get insights into the stability of PROXYL charged and discharged species. The cell performance of the most promising compounds bearing quaternary ammonium moieties is tested heading towards high voltage flow batteries and demonstrating excellent capacity retention (>99.98 % per cycle for 700 cycles). This work provides further insights into the understanding of molecular design of organic active materials for flow batteries and confirms the potential of unexplored PROXYL derivatives.Peer reviewe
From Concept to Reality: Augmented PDI Solutions Supporting Connected, Cooperative and Automated Mobility in Madrid
Full text linkPublisher Copyright: © The Author(s) 2026.The work described in this paper provides valuable insight into the novel PDI solutions to be developed for CCAM support within the Horizon Europe-funded AUGMENTED CCAM project. To this aim, two different test sites are being prepared in Madrid, Spain, for the implementation and demonstration of four cutting-edge solutions: Equipped Vulnerable Road Users (VRU) protection; Traffic Management Optimization based on Probe Vehicle Data (PVD) from CCAM; Emergency Vehicle approaching; and Ad-hoc on-demand unmanned aerial vehicle (UAV) based VRU protection for closed environments. This document unveils how the proposed services underline the vast potential of CCAM when synergized with advanced Infrastructure support, which is not only limited to the extension of the Operational Design Domain of Connected and Automated Vehicles. This approach also demonstrates PDI’s capacity to significantly enhance road safety, traffic efficiency and sustainability. Additionally, the importance of the Digital Twin is highlighted as an indispensable element for advanced traffic management and comprehensive infrastructure monitoring.Peer reviewe
Improving the Uptake of Climate Change Adaptation in the Decision-Making Processes of Road Authorities; Output of the ICARUS Project
Full text linkPublisher Copyright: © The Author(s) 2026.The integration of climate change and resilience considerations into the decision-making processes of National Road Administrations (NRAs) represents a delicate balancing act between ambition and pragmatism. A critical question is how to establish and execute a decision case for resilience through adaptation, finding equilibrium between service level requirements for the road network and the costs and benefits associated with enhancing resilience. The ICARUS project, funded by the Conference of European Directors of Roads (CEDR) emphasizes the importance of striking the right balance between service levels and costs, analogous to the mythologic figure Icarus flying neither too high nor too low. While European NRAs acknowledge the impact of climate change on their assets and operations, the full integration of adaptation strategies remains a formidable challenge. The ICARUS project aims to bridge this gap by advancing the state of the art in climate change resilience assessments, impact evaluation, cost-benefit assessments, and the implementation of nature-based solutions, while providing practical guidance on how to use these methods for building the decision case and use in the daily processes of road authorities.Peer reviewe
Compact Fluorine-Doped Multimode Fiber Sensor for Refractometry in the Visible Spectrum
No full textPublisher Copyright: © 1989-2012 IEEE.We present the design and experimental validation of a compact refractive index sensor based on a multimode-fluorine-doped-multimode (MFM) fiber structure. The sensor exploits modal interference effects in the visible spectrum by incorporating a FG105LCA multimode fiber segment with a fluorine-doped cladding. By varying the length and diameter of the central fiber segment, we achieve a significant shift in the attenuation peaks, enabling a high-resolution and compact design. Experimental results demonstrate a maximum sensitivity of 137.07 nm/RIU and a sensitivity of the wavelength shift to the refractive index up to 41.66 nm/RIU. Furthermore, a miniaturized reflective configuration using a 15 mm segment is proposed, offering both performance and integration advantages.Peer reviewe
Symbolic Regressor: An Interpretability Tool for Non-intrusive Load Monitoring
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.Multiple sources of worries such as economic constraints and the dangers of climate change have moved society towards the process of optimizing the use of their electricity. However this approach towards energy consumption has become a source of uncertainty and worry as load monitoring becomes the norm. In order to overcome the privacy concerns techniques on Non-Intrusive Load Monitoring have been in development since the 1980s. In the field of load disaggregation applications of NILM there is constant reference to three topics to be improved on, results, interpretability and responsiveness. This paper investigates the role symbolic regression tools in the field of NILM, both as a singular tool of disaggregation and as a support instrument of deep learning models more common in the literature, such as LSTM, to improve on their prediction capabilities and adding a layer of interpretability to the results. The experimentation of this document offer two different solutions with various degrees of success depending on the proposed scenario although with quantifiable improvement over the established baseline.Peer reviewe
Positioning of a cable-driven parallel robot at better than 250 μm using multilateration and photogrammetric measurement systems
Full text linkPublisher Copyright: © 2025Improving the positioning accuracy of cable-driven parallel robots (CDPRs) is crucial for industrial applications. These robots, operating in large volumes and handling heavy loads, have an accuracy limited by several factors, such as variations in ambient temperature or changes of the load being transported, which affect the mechanical structure of the robot or the tensions in the cables. For instance, CoGiRo is a CDPR of dimensions of 11 m × 15 m × 6 m able to move a platform weighing up to 500 kg. Its resolution is a few tens of micrometres, but its positioning, estimated from the winch encoders, lacks accuracy. To accurately place the CoGiRo mobile platform in the desired position and orientation, this paper proposes to use multilateration and photogrammetric measurement systems in a collaborative way. Photogrammetry continuously measured the poses of the mobile platform with worst-case coordinate uncertainties in the depth direction moving away from the cameras, with 0.2 mm being typical for all lines of sight, dropping to 0.5 mm where lines of sight were blocked by occlusion. The photogrammetric system reported poses at 2 Hz to the multilateration system, enabling it to align its stations on the distant targets and measure static poses of the platform with an estimated uncertainty typically less than 70 μm for the position coordinates and less than 110 μrad for the orientation angles. Multilateration measurements were then used by CoGiRo to reduce its positioning errors to less than 250 μm. The technique was validated using a practical assembly of two square-shaped metallic parts equipped with 10 independent capacitive distance sensors that allowed us to demonstrate part alignment to better than 250 μm.Peer reviewe
Quantum approximated cloning-assisted density matrix exponentiation
Full text linkPublisher Copyright: © 2025 authors. Published by the American Physical Society. Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI.Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the embedding techniques based on Hamiltonian simulation techniques enable the loading of matrices into quantum computers. A representative example of these methods is the Lloyd-Mohseni-Rebentrost (LMR) protocol, which efficiently implements matrix exponentiation when multiple copies of a quantum state are available. However, this is a quite ideal setup, and in a realistic scenario, the copies are limited and the noncloning theorem prevents one from producing more exact copies in order to increase the accuracy of the protocol. Here, we propose a method to circumvent this limitation by introducing imperfect quantum copies, which significantly improve the performance of the LMR when the eigenvectors are known.Peer reviewe
