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Hyaluronic acid aerogels: nanostructured, bio-based materials for biomedical applications
No full textInternational audienceIntroductionBio-aerogels are a special class of highly porous, dry, nanostructured polysaccharide materials with a low density and high internal surface area.1 They can be prepared by removing the liquid from a polysaccharide gel by drying it with supercritical (sc) CO2. Thanks to their unique properties, bio-aerogels have attracted interest as biomaterials in the last decade. Among the various polysaccharides, hyaluronic acid (HA) is an especially promising candidate for the preparation of biomedical aerogels. HA, a linear anionic polysaccharide, is part of the natural extracellular matrix and exhibits important functional and structural roles in the body, for example during tissue regeneration.2 In this contribution, the preparation of physically crosslinked HA aerogels and processing-structure-properties correlations are highlighted.Experimental methodsHA gels were prepared from HA solutions using the freeze-thaw (FT) induced gelation method. HA dry materials were then made via solvent exchange and drying with scCO2. The properties of the materials (e.g. specific surface area, density, porosity and morphology) were investigated as a function of processing parameters (e.g. HA concentration in solution, solution pH, number of FT cycles and non-solvent).Results and discussionIt was found that the HA solution pH plays a key role in the aerogel formation, as not all pH values resulted in materials with a high specific surface area.3 A pH value of 2.5, the HA isoelectric point, allowed for the formation of aerogels at all of the conditions assessed. HA aerogels were obtained with a low density ( 85%). SEM images demonstrated the presence of meso- and macroporosity. The variation of other parameters (e.g. HA concentration) also had an effect on final material properties, but less pronounced. Thanks to their high porosity and hydrophilicity, HA aerogels rapidly absorbed PBS with the maximum absorption (four times the polymer mass) reached after 15 minutes.ConclusionHA aerogels are promising biomaterials with tunable properties and internal structure that may find application as e.g. wound dressings
Advancing C3S Energy Services in support to Europe’s energy transition: co-development of the Pan-European Climate Database with ENTSO-E
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Image generation of short glass fibre composite microstructures : from control to optimization and damage prediction
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Biomethanol Production from Renewable Sources and CO2 Derived from Biogas
No full textInternational audienceMethanol is a key chemical and fuel component, with increasing interest in renewable methanol production to reduce reliance on fossil fuels and mitigate carbon emissions. This study presents a sustainable process for methanol production from biogas, integrating biogas upgrading, methane steam reforming and CO2 hydrogenation. A physical separation process using cold methanol at high pressure is implemented before the reforming and hydrogenation stages to selectively capture and purify CO2 from biogas. The methane-rich stream undergoes reforming to produce syngas, supplying the hydrogen required for CO2 hydrogenation and enhancing process efficiency. The overall process is modeled in Aspen Plus V12.1 to analyze system configurations and process parameters. The research framework evaluates the potential of biogas-derived methanol as a scalable and sustainable fuel alternative, supporting the transition to carbon-neutral chemical production. Additionally, a sensitivity analysis was conducted for both methane reforming and catalytic methanol synthesis reactions, aiming to identify optimal parameters for maximizing methanol production. This study investigates the efficiency and environmental impact of a biogas-based methanol production process, emphasizing CO2 utilization and overall process performance. The CO2 conversion efficiency reaches 99.22 %, with an overall process CO2 conversion of 53.29 %. The process achieves net direct CO2 emissions of -260.52 kmol/h, meaning it actively removes CO2 from the atmosphere, and its carbon intensity is only 255.52 g CO2 per kilogram of methanol-representing an overall direct emission reduction of up to 85 %. Copyright © 2025, AIDIC Servizi S.r.l
Endogenizing metal and mineral intensity in an integrated assessment model, a long-term study with TIAM-FR.
No full textInternational audienceAchieving the energy transition is synonymous with large deployment of low-carbon technologies, which implies an intensification of material uses in the power generation sector. This work aims to add a ”material module” to the integrated assessment model TIAM-FR. Material data is exported from the EcoInvent 3.11 life-cycle inventory database. Then, we study several types of scenarios : carbon-constrained scenarios, material-constrained scenarios based on historical metal and mineral production, and material-constrained scenarios based on potential geopolitical conflicts that could affect production and trade. TIAM-FR provides an optimal energy system for each scenario, as well as investment costs and trade organization
Application de l'ACV à l'écoconception de projets urbains
No full textInternational audienceL'analyse de cycle de vie est appliquée à l'échelle des bâtiments depuis plus de trente ans et est partiellement intégrée dans la réglementation pour les bâtiments neufs. Elle est moins souvent appliquée à l'écoconception des projets urbains bien qu'il existe des outils correspondants à cette démarche.Après un rappel méthodologique concernant l'application de l'ACV à cette échelle, cette communication présente trois applications de l'ACV à des projets urbains associant rénovation, déconstruction, construction neuve et requalification. L'objectif est d'illustrer l'applicabilité de la méthode sur des projets réels pour orienter les décisions de conception vers les pratiques les plus vertueuses. Il s'agit ensuite de présenter les perspectives de recherche à cette échelle. Dans chaque cas, l'approche a dû être adaptée aux spécificités des projets et différentes variantes de conception ont été proposées pour minimiser les impacts environnementaux
Numerical simulation of the delamination behavior of photovoltaic modules
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Benchmark-Based Study of CPU/GPU Power-Related Features Through JAX and TensorFlow
No full textInternational audienceEnergy has become a critical resource in the modern computing landscape, making power management a central focus in High-Performance Computing (HPC) and Artificial Intelligence (AI). While power management techniques like Dynamic Voltage and Frequency Scaling (DVFS), Power Capping, and ACPI/P-State CPU governors are well-established, their effectiveness is significantly influenced by the high-level structure of software frameworks. This paper presents a comprehensive empirical study of this interplay, evaluating the three aforementioned power management techniques on a dual-socket Intel Xeon “Ice Lake” CPU, a single-socket AMD EPYC “Zen3” CPU, and an NVIDIA A100 GPU. We run a suite of computational kernels using both TensorFlow and JAX to expose how framework-specific design choices mediate hardware-level power controls. Our results reveal that the best strategy for energy efficiency is highly context-dependent and relies on the specific combination of hardware, workload, and framework. We find that DVFS is the most effective on both Intel Xeon and AMD EPYC platforms, delivering significant Energy-Delay Product (EDP) reductions with minimal performance loss. In contrast, Power Capping is the most efficient technique for NVIDIA A100. A key finding is the notable influence of the software stack; for instance, JAX exhibits operational instability at the lowest GPU frequencies on the A100, while there is no limitation with TensorFlow under identical conditions. Our findings provide operational platform-specific guidance for practitioners, expose crucial robustness considerations for framework developers, and highlight the necessity of considering the software stack as an active variable in energy-aware computing
MadNCL: A GPU Implementation of Algorithm NCL for Large-Scale, Degenerate Nonlinear Programs
No full textWe present a GPU implementation of Algorithm NCL, an augmented Lagrangian method for solving large-scale and degenerate nonlinear programs. Although interior-point methods and sequential quadratic programming are widely used for solving nonlinear programs, the augmented Lagrangian method is known to offer superior robustness against constraint degeneracies and can rapidly detect infeasibility. We introduce several enhancements to Algorithm NCL, including fusion of the inner and outer loops and use of extrapolation steps, which improve both efficiency and convergence stability. Further, NCL has the key advantage of being well-suited for GPU architectures because of the regularity of the KKT systems provided by quadratic penalty terms. In particular, the NCL subproblem formulation allows the KKT systems to be naturally expressed as either stabilized or condensed KKT systems, whereas the interior-point approach requires aggressive reformulations or relaxations to make it suitable for GPUs. Both systems can be efficiently solved on GPUs using sparse \ldlt factorization with static pivoting, as implemented in NVIDIA cuDSS. Building on these advantages, we examine the KKT systems arising from NCL subproblems. We present an optimized GPU implementation of Algorithm NCL by leveraging MadNLP as an interior-point subproblem solver and utilizing the stabilized and condensed formulations of the KKT systems for computing Newton steps. Numerical experiments on various large-scale and degenerate NLPs, including optimal power flow, COPS benchmarks, and security-constrained optimal power flow, demonstrate that MadNCL operates efficiently on GPUs while effectively managing problem degeneracy, including MPCC constraints
Non-aging and thermal superinsulating bio-based composite aerogels
No full textInternational audienceAerogels are solid materials with nanometer-scale pores showing interesting properties (e.g., nanostructured network, high porosity, low density, and high specific surface area) for a range of applications. The field of aerogels based on natural resources, such as polysaccharides, is gaining more and more attention due to the need for sustainable alternatives to conventional, non-renewable counterparts. Among bio-based aerogels, pectin aerogels possess a density of around 0.1 g/cm 3 and a very fine network with meso-and small macropores. Thanks to these properties, pectin aerogels are perfect candidates for thermal insulation applications since they exhibit extremely low thermal conductivity at room conditions (0.015 -0.020 W m -1 K -1 ). As a drawback, pectin aerogels are highly hygroscopic: they adsorb moisture from the air leading to network collapse and loss of the initial properties (so called "aging").In this work, "composite" approach was applied to prevent material aging. Hydrophobization of pectin aerogels was achieved via deposition of polyurea on pectin fibrils. The influence of synthesis parameters on the material properties was investigated. Density and thermal conductivity were monitored over time at high relative humidity. Polyurea homogeneously coated the skeletal network of pectin aerogel, resulting in materials with high water contact angles and very low thermal conductivity (down to 0.015 W m -1 K -1 ) at ambient conditions. The pectin/polyurea composite aerogels exhibited stable thermal conductivity (0.015 W m -1 K -1 ), during more than 10 months at 25°C and 80% relative humidity.</div