The European Union’s transition toward climate neutrality is accelerating demand for lithium-ion batteries to electrify the automotive and household sectors. This makes the European region susceptible to vulnerabilities in material supply, end-of-life management, and recycling capacity. Despite growing research on battery circularity, existing models typically address single countries or isolated end-of-life pathways, lacking a comprehensive EU-wide, multi-pathway perspective. This study develops a system dynamics model to assess the long-term evolution of the vehicle and stationary battery market, end-of-life flows, and material recovery across all EU-27 countries up to 2050, integrating country-level heterogeneity and cathode chemistry transitions. The analysis quantifies how the interplay of extended use, remanufacturing, repurposing, and recycling shapes future battery demand, material dependency, and self-sufficiency. Results show that electric vehicles will dominate battery demand by 2050. Phase-out policies and high repurposing rates lower stationary demand, but increase reliance on imports for electric vehicle batteries. Collection and recycling capacity must expand substantially to meet regulatory targets, although recycling infrastructure remains concentrated in a few countries. Under coordinated expansion efforts, recovery of critical raw materials such as lithium, nickel, and cobalt could partially meet European self-sufficiency targets. The findings of this study highlight that excessive second-life deployment delays material recovery, whereas balanced integration of remanufacturing and recycling improves circularity and resource resilience. To meet European sustainability objectives, it is essential to implement flexible, chemistry-specific, and regionally integrated strategies. These strategies should connect battery design, collection, and recycling infrastructure to balance circular economy goals with resource security.
Recent advancements in eXtended Reality (XR) technologies have opened new opportunities for integrating virtual and physical environments, enabling natural immersive user experiences. This paper addresses the challenge of developing socially acceptable XR agents that can engage in complex, meaningful interactions across various social and public settings. Specifically, we propose a modular architecture for enhancing user-XR agent interaction, integrated into the framework of the Horizon Europe project “Socially-acceptable Extended Reality Models And Systems (SERMAS)”. The architecture is designed to ensure adaptability, scalability, and the integration of diverse communication modalities, including verbal and non-verbal cues. Its main components work together to enable seamless user detection and communication. In particular, the Detection module plays a key role in managing the agent’s awareness of the surrounding environment. Its functions include identifying user intentions, monitoring group dynamics, and inferring emotional states, thereby increasing responsiveness and enabling more contextually grounded behavior. In contrast, the Communication module employs Large Language Models for personalized verbal responses, and recognizes gestures and body language for enriched non-verbal communication. Together, these approaches guarantee contextually relevant, personalized, and emotionally intelligent interactions. The architecture supports scalability and the flexible integration or replacement of modules, fostering socially acceptable user-XR agent interactions. Its real-world applicability is demonstrated across three deployment scenarios, including a digital receptionist integrated with a physical robot, an XR-based security training system for journalists practicing safety-critical procedures, and a digital assistant supporting customers in a post-office environment. The functionality of the proposed system is presented through the implementation of the XR Agent interacting with users.
Ultra-lean spark-ignited hydrogen combustion is a proven technique for achieving near-zero pollutant emissions, along with high brake thermal efficiency. However, conventional small-bore 4-stroke engines are affected by a relevant reduction of their power density. The 2-stroke cycle offers a clear advantage, but it also needs an effort to extract its full potential. Among the various 2-stroke designs, the selected one features intake and exhaust poppet valves and external supercharging and/or turbocharging (no crankcase pump, standard lubrication). This solution has the major advantage of requiring minimal modifications compared to a conventional 4-stroke engine, except for the cylinder head and valves, which must be redesigned from scratch. The goal of this study is to explore the above-mentioned concept for an automotive application, delivering a maximum brake power of about 120 kW along with near-zero emissions. The study is particularly focused on the optimization of the scavenging and air-fuel mixing processes. Engine development was based on specific theory and state-of-the-art numerical simulation framework, combining both 0D/1D and 3D-CFD models. Combustion analysis was carried out through a quasi-dimensional model, embedded in the 0D/1D engine model and calibrated with experimental data. The numerical results show that the optimized design guarantees the formation of a strong counter-tumble vortex (tumble ratio = 3.1) into the combustion chamber, with a limited amount of short circuit of fresh charge (about 15%). Late direct hydrogen injection, when both exhaust and intake valves are closed, and high in-cylinder turbulence are the keys to provide an optimal fuel-air mixing at spark timing, avoiding any loss of fuel from the combustion chamber. Introducing the scavenging characteristics calculated by the 3D-CFD analysis into the 0D/1D engine model, the latter predicted that the proposed 3-cylinder 1.2 & ell; 2-stroke direct-injection spark-ignited hydrogen engine can easily fill the performance gap between hydrogen and Diesel, typically found on 4-strokes. Moreover, the 2stroke engine maintains the same excellent standards of efficiency and emissions of an reference 4-stroke 4cylinder 2.0 & ell; direct-injection spark-ignited hydrogen engine. The current study provides a foundation for the development of hydrogen valved 2-stroke engines and highlights key design features and challenges. Clearly, further research is needed to include accurate combustion modelling and evaluate real engine performance and emissions.
Robotic palletizing requires the rapid generation of optimal packing plans and the corresponding robot programs within the tight time constraints imposed by mass customization and factory intralogistics. In this context, while the bin packing problem has been extensively studied in the literature, practical engineering tools that support flexible batch palletizing, from optimal packing definition to validated robot execution, remain limited. In this regard, the present paper proposes an integrated simulation framework that guides engineers in defining an optimal robotic palletizing process through a structured sequence of steps. Starting from the 3D model of an existing palletizing station and its input product mix, the framework, implemented as a set of interconnected Python modules within the RoboDK simulation platform, supports automated generation and assessment of actionable packing layouts, simulation-based verification of the robotic process, and generation of executable robot code that can be automatically transferred to the robotic palletizing cell within a Digital Twin oriented approach. An efficient heuristic method is introduced to solve 3D packing instances for box-type items on standard Europallets. The problem is initially formulated as a sequence of 2D packing problems solved through a Guillotine plus Best Fit strategy, iterating across layers to maximize pallet filling while improving load balancing. The framework is validated across multiple scenarios on an industrially representative case study involving a KUKA palletizing robot, a conveyor feeding system, and two auxiliary buffer pallets. Finally, an instruction streaming module enabling online execution of the validated code on the KUKA controller is presented. Overall, the results confirm the effectiveness of the proposed framework in accelerating process planning, virtual validation and programming activities while maintaining packing quality in realistic industrial scenarios.
Ethanol emitters often consisting of a petroleum-based sachet filled with silica dioxide have been used as packaging inserts to prevent postharvest disease growth, thereby extending produce shelf life. Due to concerns about the environmental and health impacts of plastics, bio-based, biodegradable, and non-toxic materials are desired in packaging. This study aimed to develop an environmentally friendly ethanol emitter consisting of ethanol-releasing shellac-coated bagasse paperboard and validate its effectiveness against fungal growth in packaged strawberries. Bagasse paperboard (BP) coated with single to multiple layers of shellac with trapped ethanol were developed using the bar coating technique and assessed for ethanol release using gas chromatography as affected by layering, temperature, time, and water-rich products. The in-vitro effectiveness assessment of the new ethanol emitter was performed using Botrytis cinerea and Penicillium spp., grown on Petri dishes within bioassay systems with and without the emitter for 7 days at 23 ºC. The best performing emitter released up to 14,179 μL L−1 of ethanol vapor in a Pseudo-Fickian diffusion release pattern, reducing the growth of Botrytis by > 98% for 7 days and Penicillium by 50% for 4 days inside the bioassay systems. A 5-day shelf-life study of strawberries, infected with Botrytis cinerea and stored in sealed plastic packages on BP, showed that surface decay was reduced by 30% and internal decay was even more impacted in the presence of ethanol-releasing shellac-coated BP. The emitter also delayed strawberry darkening and had no effect on respiration, transpiration, and firmness. This study demonstrates the potential of a bio-based/biodegradable and non-toxic ethanol emitter on extending strawberry shelf life.
