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Mesoporous carbon derived from lignin sulfonate as a sustainable cathode for high-performance aluminium batteries
No full textInternational audienceThe development of sustainable and efficient energy storage systems is crucial for addressing the growing global energy demand. This study investigates the potential of mesoporous carbon derived from lignin sulfonate as a cathode material for aluminium batteries. Lignin sulfonate, a by-product of the paper industry, was used as a precursor to synthesize mesoporous carbon through a facile and eco-friendly activation process. The resulting carbon material exhibited a high specific surface area of ∼ 2259 m2/g and a well-defined balance of micro- and meso- porosity, making it a promising cathode material for high-performance aluminium batteries. Electrochemical characterization showed that the mesoporous carbon cathode delivered an impressive specific capacity of 91 mAh/g at 1.0 A/g current density even after 7000 cycles with excellent cycling stability. It delivered superior rate capabilities of 105, 89, 80, 72, 67, 63, 90, and 105 mAh/g at 0.1, 1.0, 2.0, 3.0, 4.0, 5.0, 1.0, and 0.1 A/g current rates, respectively. The use of lignin-sulfonate as a precursor to prepare mesoporous carbon opens up a new sustainable way for improving the electrochemical performance of carbon-based cathode materials for aluminium batteries
Contribution of microscale stochastic truss models to investigate the macroscale elasticity constants of porous ceramics
No full textInternational audienceThis paper deals with modelling the mechanical behaviour of silica-alumina open-cell porous ceramics obtained by viscous flow sintering. The modelling approach is based on the similarity of the material microstructure to a truss of sintering bridges connecting alumina particles. This makes it possible to use two-node elements, leading to a low computational cost. The method includes the building of a random packing of spheres (alumina particles) and the setup of connections between their centres (silica sintering bridges). An equivalent stiffness is then assigned to each bridge, based on the material parameters. The macroscale elasticity constants have been derived from the natural frequencies of such micrometric cylindrical volume elements made of thousands of particles. The reliability of the underlying assumptions is discussed and the dependence to the material parameters is emphasized. The method is suitable to handle more complex behaviours, which opens the door to fracture modelling
Phase Equilibrium Study of Ethane + Perfluorohexane System across Temperatures from (292.89 to 317.92) K and Pressures from (0.513 to 4.913) MPa
No full textInternational audienceThis study provides comprehensive experimental vapour-liquid equilibrium data for a system composed of perfluorohexane and ethane at four temperatures (292.89 to 317.92) K and pressures spanning from (0.513 to 4.913) MPa. The experimental investigation was achieved using a "static-analytic" equipment fitted with a capillary sampler for the equilibrium phases.The expanded uncertainties in the measurement of temperatures, pressures and mole fractions were determined to be within 0.04 K, 0.003 MPa and less than 0.03, respectively. The phase equilibrium data were successfully modelled via the phi-phi approach using two sets of thermodynamic models, i.e., the Peng-Robinson equation of state with the Wong-Sandler mixing rule or the Soave-Redlich-Kwong equation of state with the predictive Soave-Redlich-Kwong mixing rule. The parameters of both models were adjusted using the ordinary least-squares objective function. The PR-MC-WS-NRTL model slightly outperforms the SRK-MC-PSRK-NRTL model in representing experimental data, with both models showing minor differences and Bias P, Bias y and AAD y values within 1%, while AAD P values exceed 1% but remain nearly identical for both. A comparison of the VLE data for the C₂ H₆ + C₆ F₁₄ and the CO 2 + C 6 F 14 systems reveals that C₆ F₁₄ exhibits strong selectivity for C₂ H₆ over CO₂ at high pressures.</p
A rheological law to describe powder agitation in a lab-scale paddle mixer: Shear band observation and dimensional analysis
No full textInternational audienceThis work adopts an in-system rheological approach to analyse powder flow behaviour in dense flows under mechanical agitation. For this purpose, an empirical law has been developed to assess powder rheology within a laboratory mixing setup, focusing on interactions between the paddles and the powder bed in dense flow. This model, is an empirical law, based on the μ(I)-rheology-like framework derived from dimensional analysis and shear band visualization. It reveals good predictive capabilities for powders of similar particle shapes but different sizes across various filling ratios. This approach addresses challenges in measuring complex powder parameters, such as the effective friction coefficient μeff , establishing a practical and easily applicable model that facilitates the scaling up of mixing processes and allows for better anticipation of forces exerted on the paddles.Comparisons with Hatano’s equation showed a good fit with the rheological framework, particularly for deep powder beds. Better evaluation of the shear band width and reconsideration of normal stress assumptions may be the way forward to improve the accuracy of this μ(I)-rheology
Effects of cutting conditions in turning of annealed and treated Ti6Al4V titanium alloy: modelling and optimization using GA and MOAVOA methods
No full textInternational audienceTitanium alloys, renowned for their exceptional strength, corrosion resistance, and lightweight properties, play a crucial role in numerous mechanical engineering applications. This study addresses the machining complexities of titanium alloy Ti6Al4V by focusing on dry turning operations under varying hardness conditions. Two distinct hardness levels 32 HRC and 38 HRC are investigated using uncoated carbide tools. Experimental parameters including cutting speed, feed rate, and depth of cut are systematically varied to assess their effects on machining performance metrics such as surface roughness, cutting forces, power consumption, and tool wear. Through comprehensive experimentation and mathematical modeling, this research aims to explain the influence of material hardness on machining behavior and optimize process parameters for enhanced efficiency and quality. Ultimately, a multi-objective optimization was conducted and discussed regarding multi-objective artificial Vultures optimization algorithm “MOAVOA” and multi-objective optimization genetic algorithm “GA” methods. The MOAVOA algorithm has demonstrated highly satisfactory results in addressing multi-objective optimization problems and has outperformed the genetic algorithm. The results from the MOAVOA algorithm optimization indicate that the optimal cutting conditions, which achieve a balance between surface roughness (Ra), cutting force (Fz), and cutting power (Pc), fall within the following ranges: cutting speed (Vc) of 90.5–115.32 m/min, feed rate (f) of 0.08–0.81 mm/rev, and depth of cut (ap) of 0.103–0.166 mm for the treated workpieces examined. The findings offer valuable insights into the machinability of Ti6Al4V and provide practical recommendations for improving machining processes in mechanical engineering applications
Upcycling of cardboard into highly porous materials
No full textInternational audiencePaper and cardboard comprise about 20% of municipal solid waste [1]. Although recycling is a viable solution, its effectiveness is constrained by cellulose fiber degradation, which limits reuse to only three to five cycles before virgin fibers are required to maintain material quality [2]. This highlights the necessity for innovative methods to upcycle these materials into high-value products, such as bio-aerogels. Cellulose-based bio-aerogels possess remarkable properties, including high porosity (>90%), open-pore nanostructures, specific surface areas of 200–400 m²/g, and low density (0.05–0.2 g/cm³). These characteristics render them highly suitable for a broad spectrum of applications, including thermal insulation, catalysis, drug delivery, electrochemical processes, adsorption, separation, and the food industry [3]. Aerogel production involves drying a gel while preserving its porous structure, with the drying process defining the final properties [4]. Additionally, carbonization under a protective atmosphere can further enhance functionality, yielding carbon aerogels with expanded applications.This study explores the conversion of cellulose fibers obtained from paper and cardboard into bio-aerogels and carbon aerogels, with a focus on evaluating the influence of different drying techniques - supercritical CO₂ and evaporative low vacuum drying - on material structural and functional properties. Microcrystalline cellulose was used as a reference and pulp fibers were dissolved in an 8% NaOH-water solution, with supercritical CO₂ drying incorporating a recycling loop to enhance sustainability. Subsequent carbonization was employed to produce carbon aerogels. The research systematically analyzed the effects of drying methods and carbonization on key properties such as density, specific surface area, and morphology. The findings aim to optimize production processes and enhance aerogel performance for diverse industrial applications.Acknowledgements: The authors are grateful to the Occitanie Region and ANR (PEPR "Recyclage, recyclabilité, ré-utilisation des matières" and “Investissements d’Avenir” program, ANR-18-EURE-0021 project) for funding.References:[1]“What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050,” Sep. 2018, doi: 10.1596/978-1-4648-1329-0.[2]N. J. Schenk, H. C. Moll, and J. Potting, “The Nonlinear Relationship between Paper Recycling and Primary Pulp Requirements: Modeling Paper Production and Recycling in Europe,” J. Ind. Ecol., vol. 8, no. 3, pp. 141–162, Jul. 2004, doi: 10.1162/1088198042442379.[3]T. Budtova, “Cellulose II aerogels: a review,” Cellulose, vol. 26, no. 1, pp. 81–121, Jan. 2019, doi: 10.1007/s10570-018-2189-1.[4]S. Zhao, W. J. Malfait, N. Guerrero‐Alburquerque, M. M. Koebel, and G. Nyström, “Biopolymer Aerogels and Foams: Chemistry, Properties, and Applications,” Angew. Chem. Int. Ed., vol. 57, no. 26, pp. 7580–7608, Jun. 2018, doi: 10.1002/anie.201709014
New approach for 3D printing of cellulose solutions and making aerogels from them
No full textInternational audiencePolysaccharide-based 3D printed objects are promising materials with customized shapes for life science applications. A classical approach is to use gelation to stabilize the shape of printed solution. To vary solution rheological properties, nanocellulose is often used. In this work, we developed a new approach allowing printing dissolved cellulose with no crosslinking and no additives, only by varying solution rheological properties and adjusting cellulose solubility. These printed cellulose objects were then transformed into aerogels, lightweight and nanostructured materials. In addition, we demonstrated that this approach can be applied not only to neat reference cellulose, but also to dissolved cellulose textile.Microcrystalline cellulose and viscose textile were dissolved in ionic liquid. By adjusting cellulose solubility, solution viscoelastic properties were varied with the goal to obtain yield-stress fluid. The printed objects were of various shapes, composed of many layers and self-standing. The solvent was then washed out by a non-solvent, and cellulose was dried with supercritical CO2. 3D printed cellulose aerogels obtained from MCC and viscose possess porosity higher than 90%, a specific surface area around 250 m²/g and a low density (< 0.2 g/cm3).The developed approach opens new easy ways of printing cellulose solutions and valorizing waste textile.AcknowledgmentsWe are grateful to Institut Carnot MINES and PSL for the financial support of this work. We thank Julien Jaxel (PERSEE, MINES Paris) for supercritical drying
Towards an AI-Agent-Based Framework for Agile Business Process Management
No full textInternational audienceThe traditional approaches in dynamic and collaborative environments that use Business Process Management (BPM) methodologies usually lack the ability to adapt to real-time changes in case of heavy human involvement in repetitive processes. The agility of social BPM is, however, still limited because of a lack of context-sensitive tool support. This paper proposes a mapping framework that leverages conversational AI agents on a social media platform to enhance BPM agility. AI-driven conversational agents are mapped to the respective phases of the BPM lifecycle to provide real-time guidance, recommendations, and context-sensitive feedback. The agents’ collaborative features enable inclusive co-construction, interactive task execution, and continuous monitoring of the processes. That allows dynamic adaptation of the processes in case of changes so that tasks remain aligned with the users’ needs and contextual demands. This framework is developed through an exploratory approach that integrates literature review, deductive design, and use case-based evaluation. This framework could bridge gaps in the current BPM practices by integrating BPM, AI, and social media, thereby offering a new model for agile and collaborative business process management
Développement d’un modèle cinétique et thermodynamique pour l’étude de la lixiviation d’un minerai latéritique
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Optimisation de la planification opératoire par la prédiction des durées : Une application dans une clinique Belge
No full textInternational audienceL’optimisation de la planification des blocs opératoiresest un enjeu stratégique pour l’efficience des ressources etla qualité des soins. Cette étude explore l’utilisation del’apprentissage automatique pour améliorer la précisiondes prévisions des durées opératoires. En collaborationavec le CHC Liège, nous avons appliqué une méthodologiebasée sur l’analyse de données hospitalières couvrantplus de 68 405 interventions chirurgicales. Cette approchecombine différentes techniques d’apprentissage automatiqueafin de proposer un cadre prédictif robuste et performant.L’objectif est de fournir des prévisions fiablespermettant une gestion optimisée des blocs opératoireset une meilleure allocation des ressources. L’étude proposed’intégrer de nouvelles variables cliniques et organisationnellespour améliorer la robustesse des prédictions.Les résultats montrent une réduction notable des erreursde prédiction et une meilleure fiabilité des estimations,permettant une gestion optimisée des blocs opératoireset une allocation fiable des ressources