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Dual-Side Selective Harmonic Elimination Technique for Voltage Source Converters Interfacing DC Microgrids and AC Networks
No full textPublisher Copyright: © 1982-2012 IEEE.Voltage source converters (VSCs) are commonly employed to interface dc and ac networks in dc microgrid (dcMG) systems. However, when the dc-side current harmonics introduced by these VSCs interact with inherent dcMG system resonances, the dcMG system stability and power quality will deteriorate. To address this issue, this article proposes a cost-effective dual-side selective harmonic elimination pulse-width modulation (DSSHE-PWM) technique for two-level VSCs. The proposed DSSHE-PWM simultaneously eliminates harmonics introduced by the VSC in both the ac-side voltages and the dc-side current. To achieve this, first, the correlation between the VSC modulation and the dc-side current harmonics is investigated. Subsequently, the corresponding ac-side voltage harmonics that create the concerned dc-side current harmonics are identified. These voltage harmonics are then incorporated into an optimization problem to generate switching patterns for the VSC. The effectiveness of the proposed technique in improving the power quality and stabilizing the dcMG system is validated with both simulation and experimental results.Peer reviewe
Understanding the impact of additives on cobalt leaching efficiency using a citric acid-based deep eutectic solvent
Full text linkPublisher Copyright: © 2025 The Royal Society of Chemistry.Recovery of critical metals such as cobalt from secondary sources is an effective way to reduce the supply risk of metals that are necessary in clean energy technologies, but such recovery processes need to be more benign. Hence, this study presents new insights into leaching cobalt using deep eutectic solvents under mild conditions. The role of ethylene glycol (EG) and water as additives in cobalt leaching was investigated using a mixture containing citric acid (CA):choline chloride (ChCl) in 1 : 1 molar ratio. While the water concentration and Co leaching efficiency were directly related, that was not the case for the EG content. A larger amount of EG in the mixture (CA : ChCl : EG from 1 : 1 : 0.3 to 1 : 1 : 4 molar ratio) decreased the cobalt leaching efficiency, which was attributed to the presence of EG in different coordination forms, as suggested by FTIR spectroscopy. The optimal solvent mixture CA : ChCl : EG (1 : 1 : 1.1) led to leaching efficiencies of 43% cobalt and 65% lithium from lithium cobalt oxide (LiCoO2) at 60 °C for 48 h. Although lithium(I) was the key to increasing the leaching efficiency, we also observed that the presence of lithium(I) in the leachate could negatively impact the electrochemical reduction process. This may be due to the different speciation of cobalt(ii) in the presence and absence of lithium(I), as indicated by NMR spectroscopy.Peer reviewe
Exploring the application of quantum technologies to industrial and real-world use cases
Full text linkPublisher Copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.Recent advancements in quantum computing are leading to an era of practical utility, enabling the tackling of increasingly complex problems. The goal of this era is to leverage quantum computing to solve real-world problems in fields such as machine learning, optimization, and material simulation, using revolutionary quantum methods and machines. All this progress has been achieved even while being immersed in the noisy intermediate-scale quantum era, characterized by the current devices’ inability to process medium-scale complex problems efficiently. Consequently, there has been a surge of interest in quantum algorithms in various fields. Multiple factors have played a role in this extraordinary development, with three being particularly noteworthy: (i) the development of larger devices with enhanced interconnections between their constituent qubits, (ii) the development of specialized frameworks, and (iii) the existence of well-known or ready-to-use hybrid schemes that simplify the method development process. In this context, this manuscript presents and overviews some recent contributions within this paradigm, showcasing the potential of quantum computing to emerge as a significant research catalyst in the fields of machine learning and optimization in the coming years
OASEES: Leveraging DAO-Based Programmable Swarms for Optimized Edge-to-Cloud Data Processing
No full textPublisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.As traditional linear models stagnate decision-making and data federation, there’s a pressing need for a novel, swarm-based cloud-edge computing approach to enhance European data sovereignty and foster a sustainable, circular economy across various market sectors. To that end, the EU-backed OASEES project identifies a need for an innovative, inclusive, and disruptive approach to the cloud-to-edge continuum, swarm programmability, and data federation over GAIA-X. This paper underscores the actual challenges associated with managing and orchestrating edge infrastructure and services, thereby harnessing the potential of edge processing and federated learning. Moreover, it delves into the core features of the OASEES approach, taking into account technological challenges anticipated in system development. We also explore the integration of multi-tenant, interoperable, secure, and trustworthy deployments into the cloud-to-edge paradigm, in line with the conference’s scope. Briefly, we discuss several vertical edge applications with substantial market impact, demonstrating how our approach partially addresses the existing gaps and contributes to a decentralized AI ecosystem.Peer reviewe
Hydrogen Station Model Design Using Functional Mock-Up Units and Metaheuristics Optimization
Full text linkPublisher Copyright: © The Author(s) 2025.Hydrogen-powered heavy-duty vehicles will transform the logistics landscape, but their extensive adoption presents substantial challenges. Matching hydrogen demand with supply, scaling up infrastructure, controlling carbon emissions targets, and integrating with renewable energy sources are significant obstacles to overcome. This paper addresses these challenges by modeling a hydrogen station for heavy-duty vehicle fleets using Matlab-Simulink software. The hydrogen station components proposed are individually modeled: (1) the electrolyzer model generates hydrogen and oxygen by electrolysis consuming water and electricity; (2) the hydrogen reformer model generates hydrogen and carbon dioxide through steam methane reforming or ethanol reforming; (3) the hydrogen storage tank; and (4) carbon capture and storage. These models were compiled into functional mock-up units (FMU) to facilitate further exploration. This paper incorporates metaheuristic optimization techniques to address the design complexities and enhance the performance of hydrogen stations under various operating conditions. Multiple optimization objectives have been considered, including reducing carbon emissions and reducing the total monetary cost. Furthermore, several critical constraints are integrated to ensure realistic scenarios. These constraints include the accumulated hydrogen production that meets daily demand and the limitations in resource consumption. Finally, the combination of the FMU approach with metaheuristics techniques demonstrates the potential for the optimal hydrogen infrastructure design.Peer reviewe
Neuromuscular Interfacing for Advancing Kinesthetic and Teleoperated Programming by Demonstration of Collaborative Robots
No full textPublisher Copyright: © 2008-2011 IEEE.This study addresses the challenges of Programming by Demonstration (PbD) in the context of collaborative robots, focusing on the need to provide additional degrees of programming without hindering the user's ability to demonstrate trajectories. The study proposes the use of a wearable human-robot interface based on surface Electromyography (sEMG) to measure the forearm's muscle co-contraction level, enabling additional programming inputs through hand stiffening level modulations without interfering with voluntary movements. Vibrotactile feedback enhances the operator's understanding of the additional programming inputs during PbD tasks. The proposed approach is demonstrated through experiments involving a collaborative robot performing an industrial wiring task. The results showcase the effectiveness and intuitiveness of the interface, allowing simultaneous programming of robot compliance and gripper grasping. The framework, applicable to both teleoperation and kinesthetic teaching, demonstrated effectively in an industrial wiring task with a 100% success rate over the group of subjects. Furthermore, the presence of vibortactile feedback showed an average decrease of programming errors of 33%, and statistical analyses confirmed the subjects' ability to correctly modulate co-contraction levels. This innovative framework augments programming by demonstration by integrating neuromuscular interfacing and introducing structured programming logics, providing an intuitive human-robot interaction for programming both gripper and compliance in teleoperation and kinesthetic teaching.Peer reviewe
Nutritional evaluation of high-value alternative proteins extracted from legume defective seeds
Full text linkPublisher Copyright: © 2025 Elsevier LtdThe high protein content of legumes, including P. vulgaris, L. culinaris, L. albus, and P. sativum, is increasingly valued in food formulations, driving interest in utilizing their by-products. This study evaluates the nutritional quality and applications of four legume protein concentrates derived from defective seeds. Analysis included amino acid composition, antinutrient presence, and in vitro digestion, along with structural analysis. Proximate composition, pigment, mineral, and bioactivity assays were also conducted. All concentrates surpassed 70 % protein concentration and presented a well-balanced amino acid profile meeting the requirements for healthy individuals. Bean concentrate exhibited elevated levels of trypsin inhibitor (53.27 ± 0.19 TIU/mg) and total phenolic compounds (0.82 ± 0.02 mg GAE/g), while pea concentrate showed the highest phytic acid content (2.67 ± 0.02 %). Bean concentrate displayed superior structural stability and lower in vitro protein digestibility (∼20 %), compared to the other concentrates (60–70 %). These findings optimize legume defective seeds utilization in plant-based products, addressing sustainability and enhancing nutritional value.Peer reviewe
Laser threshold magnetometry with a combined laser diode, nitrogen-vacancy center cavity
No full textPublisher Copyright: © 2025 SPIE.Nitrogen-vacancy centers (NV) in diamond are promising quantum systems for magnetic field sensing. The sensitivity and the linearity of such a quantum sensor can be greatly improved by using stimulated emission of the NV centers in the concept of laser threshold magnetometry (LTM), which is projected to reach the fT/sqrt(Hz) regime. Previous implementations of NV centers in optical cavities relied on external seed lasers, pulsed operation, or sensing via NV-absorption. In our work, we combine the NV centers with a second gain medium, a laser diode, within the same cavity, achieving self-sustainable continuous-wave lasing. This approach compensates the intrinsic losses of the cavity and the diamond, through a fixed additional gain below the threshold of the laser system. A continuous-wave laser threshold and a linewidth narrowing is observed with increasing pump power on the NV centers of the combined laser system. An improved laser system shows a magnetic field-dependent laser threshold, which is the basis for improved-sensitivity NV magnetometry via LTM.Peer reviewe
Combining physics-based and data-driven methods in metal stamping
No full textPublisher Copyright: © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.This work presents a methodology for combining physical modeling strategies (FEM), machine learning techniques, and evolutionary algorithms for a metal stamping process to ensure process quality during production. Firstly, a surrogate model or metamodel is proposed to approximate the behavior of the simulation model for different outputs in a fraction of time. Secondly, based on the surrogate model, multiple soft sensors that estimate different quality measures of the stamped part departing from the draw-ins are proposed, which enables their integration into the process. Lastly, evolutionary algorithms are used to estimate the latent blank characteristics and for the prescriptions of process parameters that maximize the quality of the stamped part. The obtained numerical results are promising, with relative errors around 2 2% in most cases and outperforming a naive method. This methodology aims to be a decision support system that moves towards zero defects in the stamping process from the process conception phase.Peer reviewe
A multi-level IIOT platform for boosting mines digitalization
Full text linkPublisher Copyright: © 2024This paper presents an innovative IIoT multi-level platform tailored to address the specific needs of the mining domain. The platform has been conceptualized and built in the context of the illuMINEation European project. For this purpose, mining specific use cases have been designed such as promoting underground safe areas, performing efficient mining operations or boosting predictive maintenance approaches. Then, specific requirements have been identified and, as a result, the platform has been developed. It consists of four-level layered platform: (1) edge devices layer to manage several sensors deployed in the mines; (2) edge box layer to provide in-mine operations such as filtering, streaming and processing; (3) fog layer which offers an overall perspective of each mine; and (4) cloud layer to centralize the data of all the mines and to provide powerful processing capabilities. In addition, the platform is robustly secured in terms of protecting communications confidentiality and access control and also provides a toolbox aimed at manipulating 3D complex images to obtain operable mine-domain novel user interfaces. Finally, a platform validation is proposed where three different use cases are explained to better show and demonstrate the capabilities of the platform.Peer reviewe